Horticulture

Surface area-proportional growth could arise if nutrient/waste exchange across the plasma membrane is a limiting factor for growth. We observed that red light-illuminated optoBem1 cells also exhibited a change in DNA content over time. While most cells maintained a ploidy of 2N or less during the first 3 h of Bem1 disruption, a population of 4N cells appeared following 6 h of arrest , consistent with prior reports suggesting that after Bem1 disruption, some arrested cells eventually leak through the cell cycle block and undergo DNA endoreduplication. To ensure that the surface area-proportional growth was not an artifact of increased ploidy, we set out to generate ‘giant yeast’ via a second, non-optogenetic method: disruption of Cdk1/Cdc28 using the temperature-sensitive allele cdc28-13 . Unlike optoBem1 cells, nearly all cdk1-ts cells at the restrictive temperature arrest in G1 without undergoing further DNA replication. We found that cdk1-ts cells grown at the restrictive temperature to induce arrest in G1 also exhibited a linear increase in cell diameter, consistent with growth proportional to surface area . However, cdk1-ts were unable to maintain this rate of growth over the entire 12-h time-course: After reaching a volume of 500–700 μm3 , cell growth stalled . Taken together, our results from both optoBem1 and cdk1-ts cells indicate that the isotropic growth rate during G1 is proportional to surface area over a wide range of cell sizes.

DNA endoreduplication does not appear to affect this overall growth rate but may be required to sustain it beyond a critical cell size, giving rise to the robust continued growth of optoBem1 cells. It has been shown in other organisms, for example, that DNA endoreduplication enables large increases in cell size. One possibility by which our findings can be reconciled with prior observations of exponential growth in wild type budding yeast is that cells become surface area-limited at sizes just above that of wild type cells, thereby inducing a shift from volume proportional growth to surface area-proportional growth.Cell size control pathways exist to correct for deviations from a set-point size, yet most previously-identified size control pathways specifically operate on cells that are born too small, delaying cell cycle progression to enable further growth to occur. Because the light and temperature-shift stimuli with which we prepared ‘giant’ yeast are fully reversible, we reasoned that we could monitor the return to a steady-state size distribution after releasing giant cells from their block. We prepared giant optoBem1 cells by incubating them in red light for 8 h and monitored them by live-cell microscopy after releasing them into infrared light. Strikingly, we found that cell populations rapidly returned to their unperturbed state , with individual daughter cells reaching the set-point volume in as few as three rounds of division .Return to the set-point size is not driven by cell shrinking,hydroponic nft system as giant mothers maintained their maximum volume over multiple rounds of budding .

Instead, the giant mothers are eventually diluted out as successive generations are born, an effect that is especially prominent in cell populations at least 10 h post-Bem1 release . In these populations, size distributions have a single mode near the set-point volume but exhibit long tails towards larger volumes . Our observation that cell size recovers after only a few generations strongly supports the existence of size control acting on large cells and demonstrates that size homeostasis across a cell population is robust even to extreme increases in cell volume.Quantitatively monitoring cell growth in yeast—as well bacterial, archaeal, and mammalian cells—has shown that the behavior of many organisms is consistent with an adder that monitors size across an entire cell cycle to correct for deviations in cell size and maintain size homeostasis in the population. However, a recent study argued that in budding yeast, the adder behavior could arise from independent regulation of pre- and post-Start events, without a cell needing to keep track of its added volume across all cell cycle phases, and may fail under various perturbations. To test whether adder-based mechanisms could account for size control in giant yeast, we quantified inter division volume change in successive cell division cycles after releasing optoBem1 cells into infrared light. For this experiment we prepared optoBem1 cells that also expressed fluorescently-labeled septin rings, which enabled us to time both bud emergence and cytokinesis and thus separate pre-Start and postStart size regulation . The ‘adder’ model predicts that the cell volume at division should be proportional to cell volume at birth with a slope of. Indeed, for unperturbed cells, we found that cell volume at division was linearly related to volume at birth with a slope of 1.19 . However, we found that the adder model poorly explained the cell size relationships in our giant cells, where the volume at division was related to volume at birth with a slope of 1.73 .

This relationship was also evident when individual cells were tracked over time: the interdivision volume change, Δ, was positively correlated with the volume at birth . This size-dependent volume change occurred entirely during S/G2/M phase, as cells added a minimal volume during G1 that did not vary with cell size . We also performed analogous experiments in cdk1-ts giant cells that were shifted back to the permissive temperature. These experiments revealed a similar relationship: large cells grew more than small cells, exhibiting a linear relationship between volume at division and volume at birth with a slope of 1.70 . These results are broadly consistent with recent work showing that although size control in unperturbed cells resembles an adder-based mechanism, no mechanistic adder regulates volume addition across the entire cell cycle. Our data also suggest that any size regulation limiting the growth of large cells is likely a consequence of regulation in S/G2/M, as growth during G1 is negligible.If an adder is unable to explain size homeostasis in giant yeast, what regulatory mechanisms or growth laws might operate on the daughters of giant cells during S/G2/M? Two possibilities include a bud ‘sizer’, where bud growth would be restricted after reaching a critical size; and a bud ‘timer’ in which cytokinesis would occur at a fixed duration following the beginning of S/G2/M . Such ‘sizers’ and ‘timers’ have been proposed to operate in a variety of biological systems. To distinguish between these possibilities, we tracked the timing of bud emergence and cytokinesis by septin ring appearance and disappearance, respectively,nft channel following reactivation of Bem1 in giant optoBem1 cells . Daughter volume strongly correlated with mother volume , inconsistent with a bud sizer mechanism. Our prior observation that the inter division volume change scales positively with cell birth size further argues against a bud sizer for cell volume control. In contrast, our data were consistent with a timer specifying the duration of S/G2/M: the time from bud emergence to cytokinesis did not vary as a function of mother cell volume and took average 95 min across cells of all volumes .Similar experiments performed using cdk1-ts cells were consistent with our observations in optoBem1 cells, revealing a size-independent duration of budding. However, we observed one notable difference: the duration of the size-invariant bud timer in giant cdk1-ts cells was substantially longer than that of giant optoBem1 cells . As Cdk1 is a key driver of mitosis in eukaryotes, the increased duration of the bud timer in cdk1-ts cells may arise from the need to refold or synthesize new Cdk1 molecules to complete S/G2/M following a shift from the restrictive to permissive temperature. Furthermore, even when grown at the permissive temperature, the doubling time of cdk1-ts cells is longer than an isogenic wild type strain , suggesting that cdk1-ts may not be able to fully complement CDK1. In summary, we find that a timer specifying a constant budding duration describes how a cell population founded by ‘giant’ cells returns to their set-point volume. Although mother and daughter sizes are correlated across a broad size range, daughters are always born smaller than mother cells. After cytokinesis, daughter cells remaining larger than the set-point volume exhibit a G1 phase with virtually no growth and bud rapidly, leading to a geometric shrinking in successive generations . Indeed, a back-of-the-envelope calculation demonstrates that if newly-budded daughters are each 50% smaller than their mothers, a 32-fold decrease in cell volume can be achieved in 5 generations .

Assuming a 100 min doubling time , a return to the set-point size would take ~8 h. A fixed budding time, even in the absence of active molecular size sensors in S/G2/M, is sufficient to buffer against persistence of abnormally large cell sizes in the population. We also note that the bud duration timer we describe is quite complementary to G1-phase size sensors such as Whi5, which compensate for a small size at birth by elongating G1 phase.Our conclusions are derived from cells prepared using two independent perturbations: optogenetic inactivation of the Bem1 polarity factor and a temperature-sensitive cdk1 allele. Importantly, each of these perturbations targets distinct cellular processes and thus produces distinct physiological defects. Cells lacking Bem1 activity exhibit weakened cells walls and undergo successive rounds of DNA endoreduplication following their initial arrest in G1 . In contrast, loss of Cdk1 does not produce such defects but its disruption requires incubating cells at 37˚C, which may broadly activate environmental stress response pathways. Furthermore, cdk1-ts may not fully complement CDK1, even at the permissive temperature . That each of these perturbations reveals similar mother-daughter size correlations as well as a size-invariant bud timer strongly supports the generality of our conclusions. The bud timer we describe here is consistent with prior work suggesting that the duration of budding tends to be invariant to changes in growth rates. However, such a timer need not be a dedicated biochemical circuit to sense budding duration, compare it to a set-point, and dictate the transition to cytokinesis. Its existence could simply arise due to the time required by independent cellular processes that coincide with bud growth, such as the combined duration of S-phase or mitosis. Nevertheless, one observation suggests more complex regulation: the duration of the size-invariant bud timer is markedly longer in enlarged cdk1-ts vs. optoBem1 cells , yet mother-daughter sizes are nearly identical in these two backgrounds . These data suggest that the duration of the bud timer may be inter-related to Cdk1 activity and cells’ growth rate during S/G2/M. Recent work has found that mitosis and bud growth rate are closely coordinated and that cells may extend the duration of mitosis to compensate for slow growth that occurs under poor nutrient conditions. Dissecting the dependencies between growth rate, Cdk1 activity and the duration of post-Start events presents a promising direction for future study.All yeast strains used are isogenic to an ‘optoBem1’ strain which was created in the w303 genetic background and contained exogenous PhyB-mCherry-Tom7 with endogenous Bem1 C-terminally tagged with mCherry-PIF, as previously described. The cdc28-13 strain was a kind gift from David Morgan. A pACT1-CDC10-eGFP expression vector was created by Gibson assembly, with the CDC10 expression cassette inserted between the NotI and XmaI sites of the pRS316 vector. For the experiments described in Figs 3 and 4; Fig D, E, F, and G in S1 Fig; and S2 Fig; the indicated vector was transformed into our optoBem1 or cdk1-ts strain and selection was maintained by growing yeast in synthetic complete media lacking uracil . For all other experiments, yeast were cultured in synthetic complete media .Preparation of yeast prior to optogenetic experiments was performed, in general, as previously described. Yeast undergoing exponential growth in synthetic media were treated with 31.25 μM phycocyanobilin and incubated in foil-wrapped tubes at 30˚C for a minimum of 2 h. For all microscopy experiments, yeast were spun onto glass-bottom 96-well plates coated with Concanavalin A and washed once with fresh PCB-containing media to remove floating cells. Cells remained approximately spherical following this procedure, as assessed by Concanavalin A staining .Imaging was performed at room temperature. For experiments where isotropic growth was measured , yeast were plated and imaged immediately following PCB treatment. For experiments where growth following Bem1 reactivation was examined , PCB-treated yeast were first placed in clear culture tubes and incubated at room temperature for >6 h while undergoing constant illumination with a red LED panel .

Because of their central positions, the electrodes are closer to the expected sources of current and thus in the region of maximum potential gradient. Hence, this electrode configuration maximizes the changes in both magnitude and sign of the measured ΔV associated with a change in the CSD distribution. The electrode diameter was 1.5 mm. The penetration of the electrodes into the rhizotron was 4 mm ± 1 mm. To evaluate the possible distorting effects of the densely populated electrodes on the potential field distribution, a test was performed with low conductivity water . The test showed no resistivity anomalies, which may be caused by the presence of the electrodes . Therefore, while rhizotron setups with electrodes only on the sides were successfully adopted , we found that the current setup represents a better solution for iCSD experiments . Data were acquired with a MTP DAS-1 resistivity meter with 8 potential channels. For the ERT acquisition over the 2D grid of electrodes, we chose a dipole-dipole skip 2 configuration. For each skip 2-couple of injection electrodes the remaining skip-2 couples of electrodes were used as potential dipoles . The associated complete set of reciprocals was also acquired,vertical grow table the resulting acquisition sequence contained 3904 data points . Following the ERT data acquisition, the MALM data acquisition required little setup adjustments and time.

As the two current electrodes are fixed, the use of a multichannel resistivity meter significantly reduced the acquisition time and, consequently, supported the acquisition of more robust data sets. Electrode 1 was used to inject the current into the plant stem, while electrode 64 was used as a return electrode in the growing medium . The remaining 62 electrodes were used to map the resulting potential field. A sequence with 204 ΔVs was used. Considering the grid in Fig. 2a, the sequence included the vertical, horizontal, and diagonal ΔVs between adjacent electrodes. While 61 ΔVs would provide all the independent differences, the 204 ΔV sequence was preferred because of its redundancy and consequent lower sensitivity to acquisition errors. The acquisition time remained relatively short as the multichannel instrument was optimized with fixed current electrodes that allowed 8 ΔVs to be measured at once.ERT and MALM data were filtered considering: 1) reciprocal error , 2) stacking error , 3) minimum measured ΔV , 4) apparent resistivity , and 5) maximum electrode contact resistance . The filtering was implemented to enhance the control on the ERT inversion and obtain a reliable ρmed for the successive iCSD inversion. After the processing, the data were inverted with the BERT inversion software to obtain ρmed . Data error was set to 5% in line with the stacking and reciprocal thresholds used for the data filtering. The regularization was adjusted using the lambda optimization algorithm provided by the BERT software.

Generally speaking, a rhizotron is treated as a 2D geometry. However, this bounded and thin geometry leads to some complications into the ERT inversion. Specifically, nocurrent-flow boundary conditions were set for all the rhizotron surface and the inversion had to be adapted for the resulting pure Neumann problem . For a higher quality forward calculation, the rhizotron volume was discretized in 3D by extruding a 2D mesh with 5 layers. The discretization allowed the refinement of the mesh near the electrodes while maintaining high mesh quality. At the same time, in order to limit the inversion time and force the inversion to be two-dimensional , the elements in z direction were grouped together and inverted as a unique variable. This way, a 3D forward calculation was implemented within a 2D inversion .The iCSD inversion that we developed was based on the physical principles of a bounded system in which linearity and charge conservation were applied to decompose the investigated CSD distribution into the sum of point current sources. This provided a discrete representation of the root system portions where the current leaks from the roots into the surrounding medium. Because of the linearity of the problem, the collective potential field from multiple current sources is the linear combination of their individual potential fields. As such, the measured ΔV can be viewed as and decomposed into the sum of multiple ΔVs from a set of possible current sources. These possible current sources are namedViRTual electrodes . As purely numerical electrodes, they are simulated by mesh nodes representing possible current sources, but with no direct correlation with the real electrodes used during data acquisition. Basically, the VRTe were distributed to represent a grid over which the true CSD distribution is discretized. In order to account for any possible CSD, a 2D grid of 306 VRTe was arranged to cover the entire rhizotron . The charge conservation law implies that the sum of the current fractions associated with the VRTe has to be equal to the overall injected current, which is provided by the resistivity meter.

If we normalize the injected current to be equal to 1, the sum of the VRTe weights has to be 1 as well. Briefly, for Ohm’s law, normalizing the current to 1 is equivalent to calculating the resistance, R, from ΔV. Then, the use of R simplifies the presentation of the numerical problem. Once the VRTe nodes are added to the ERT-based ρmed structure, the potential field associated with each of the VRTes is simulated with BERT. From these simulated potential fields, the same sequence of 204 R is extracted, each corresponding to a single VRTe. Each extracted sequence contains the resistances that would be measured in the laboratory if all the current sources were concentrated at the VRTe point .Synthetic numerical and laboratory experimental tests were performed in order to evaluate the capabilities of the setup and inversion routine to couple the ERT and MALM approaches for the iCSD. In the numerical tests both the true source response and VRTe responses were calculated with BERT. Figure 3 shows an explanatory numerical test with inversion of a point source, and the associated Pareto front that was used to select the optimum regularization strength. As this first experiment was performed to specifically test the inversion routine, a homogeneous ρmed was used in order to avoid influence from the baseline resistivity distribution complexity. For the second experiment, the laboratory tests were conducted. Because of the ρmed heterogeneity of any experimental system, these laboratory tests need to include the ERT inversion,nft hydroponic and the use of the obtained ρmed as input in the iCSD. The true current sources were obtained using insulated metallic wires inserted into the rhizotron . The insulating plastic cover was removed at the tips of the metallic wires to obtain the desired current sources. Six experimental tests were performed using different numbers and positions of these current sources. The rhizotron was filled with tap water and left to equilibrate to achieve steady state conditions of water temperature and salinity, thus minimizing ρmed heterogeneity and changes during the experiment. Changes in ρmed during the ERT and MALM acquisition periods would make the ERT-based ρmed less accurate and compromise the iCSD. To make sure ρmed was stable, a second ERT was performed after the MALM acquisition and compared with the initial measurement. The conductivity of the solution was also measured in several locations of the rhizotron with a conductivity meter to validate theρmed obtained from the ERT inversion. This setup allowed the acquisition of good quality data sets since less than 5% of the data were discharged during the data processing. Because of the controlled laboratory conditions, the ρmed obtained with the ERT was stable and consistent with the direct conductivity measurements. The quality of the ERT inversion was also confirmed by comparing the model responses with the acquired data . Similarly, the acquired iCSD data were plotted against the resistances calculated with the CSD distribution obtained from the iCSD.

The tests also allowed a more informed definition of the VRTe grid. For our setup, a spacing of 3 cm provided a good compromise between resolution, stability, and duration of the iCSD routine. The 3-cm spacing also agrees with the ERT resolution, which would not support a higher iCSD resolution. Successive numerical tests were based on the 8- source laboratory tests shown in Fig. 4. These tests aimed to 1) link laboratory and numerical tests to evaluate the influence of the numerical iCSD routine and laboratory setup on the overall iCSD stability and resolution; 2) account for a more complex CSD, given by the 8 wire-tip sources that were used to simulate distal current pathways; and 3) account for possible ρmed heterogeneity. To address goals 1 and 2, the position of the 8 sources was replicated in the numerical tests and a test with homogeneous ρmed was included to simulate the water resistivity of the laboratory tests. To address goal 3, heterogeneous ρmed were tested.In order to account for the heterogeneous ρmed the following modeling steps were carried out. First, a true ρmed was assigned to the mesh cells of the rhizotron ERT model. We included homogeneous, linear, and quadratic resistivity profiles in the y direction, see Fig. 5. Second, the ERT acquisition was simulated with the ERT laboratory sequence and 3% of Gaussian error, in line with reciprocal and stacking errors observed in the laboratory data sets. Third, the forwarded ERT data sets were inverted following the exact laboratory procedure. A refined and different mesh was used for forward and inverse problems to, respectively, increase the simulation accuracy and avoid the inverse crime . The ERT forward calculation was then repeated over the inverted ρmed.As for ERT, we compared true and inverted MALM responses. First, the true response was simulated with the 8 current sources overt the true ρmed. Second, a MALM response was calculated over the inverted ρmed and inverted to obtained the inverted CSD. Third, the obtained inverted CSD was used to forward calculate the inverted MALM response over the inverted ρmed. True and inverted MALM responses were then compared.We performed hydroponic and soil experiments using maize and cotton plants. In all the plant experiments, the injection electrode was positioned in the plant stem at a height of 1 cm from the surface of the growth media. For the hydroponic experiments, the plants were first grown in columns with aerated nutrient solution . They were then moved to the rhizotron for the experiments. As in the metallic roots test, the rhizotron was filled 1 day before the experiment to reach stable and homogeneous temperature and salinity conditions. The plant was positioned at the center of the rhizotron with soft rubber supports. The plants were submerged at the same level as in the growing column to avoid discrepancies caused by the plant tissues adaptation to the submerged and aerated conditions, as discussed above with regard to the growing conditions. Consequently, the root crown was approximately 3 cm below the water surface. For the soil experiments, seedlings were grown directly in the rhizotron to avoid damaging the roots and altering the root-soil interface. The soil was prepared by mixing equal volumes of sandy and clay natural soils acquired from an agricultural study site run by U.C. Davis, CA . The plants were irrigated with double strength Hoagland solution . Two soil experiments were performed. In the first experiment, four cotton plants were grown for four months. For these experiments, the plants were positioned with the root crown approximately 8 cm deep . In the second experiment, a pregerminated maize seed was planted 3 cm deep and then grown for four months .Figure 3 shows the result of a synthetic numerical test performed to evaluate the iCSD resolution, inversion stability, and influence of imposed constraints. The obtained CSD matches the true position of the simulated current source. The sum of the current sources equals 1 as expected and required by the continuity constraint. The resolution of the CSD is in line with the electrode interspace . The first-order regularization does not hinder the reconstruction of simulated point source. Figure 4 shows the results of a laboratory experiment where the iCSD method was tested with a known distribution of current sources obtained with metallic wires. The use of metallic wires offered a comprehensive solution to test the overall correct functioning of the laboratory setup and inversion routine. The iCSD correctly characterized both position and intensity of the test sources with no need for prior information to constrain the solution.

There are numerous reports of upland forests and savannas that switched for periods of time to CH4 sources , and wet-land forests that switched to CH4 sinks . In most cases the proximate cause for the shift was a change in soil water content, but the ultimate cause varied from seasonal shifts in precipitation and evapotranspiration , to plant community successional stage , to experimentally imposed warming . Because transpiration helps regulate soil water content, these studies suggest that tree physiology influences CH4 fluxes between upland forests and the atmosphere.Tree physiology influences both the production and oxidation of CH4, and can play an important role in determining whether a particular forest is a net source or sink of CH4. In the near absence of studies on plant regulation of CH4 cycling in upland forests, it is instructive to consider studies in wetland systems. Plants are the ultimate source of organic carbon—in the form of root exudates or detritus—that microorganisms metabolize to CH4, and several isotope tracer studies have demonstrated a tight coupling between plant photosynthesis and methanogenesis . A full cycle of CO2 assimilation by plants, release of photosynthate into soils and emission as CH4 requires as little as 2 hours,hydroponic grow table and up to 6% of the assimilated CO2 is emitted as CH4 in wetland ecosystems.

Elevated CO2 concentration stimulates CH4 emissions from wetland soils , an effect that is directly proportional to the stimulation of photosynthesis by elevated [CO2] . Although most studies relating the effects of elevated [CO2] to CH4 emissions from wetland soils have been with herbaceous plants, a single study confirmed a linear relationship between CH4 emissions and photosynthesis in the wetland tree Taxodium distichum Rich.It is reasonable to hypothesize that similar relationships between plant productivity and methane production occur in upland forests. For example, increasing inputs of labile carbon to upland soils may promote CH4 production both by enhancing the electron donor supply to methanogens, and expanding anaerobic microsites via increased microbial O2 demand. Trees exert indirect regulation of CH4 production and oxidation through their influence on soil water content, which determines the proportion of the soil profile that is anaerobic and producing CH4 versus aerobic and oxidizing CH4. An example of tree physiology influencing CH4 cycling in upland forests is provided by the Duke FACE experiment. McLain et al. found that elevated [CO2] increased soil water content, which simultaneously increased CH4 production and decreased CH4 oxidation. The increase in soil water content was caused by reduced transpiration in the elevated [CO2] treatment, and the net effect was a positive feedback on radiative forcing by CH4. A possible mechanism for CH4 emissions from upland vegetation is transport from the saturated zone below the water table through the transpiration stream. In most ecosystems, the deepest 5% of roots occur at depths greater than 1 m and maximum rooting depths can exceed 4 m .

The deepest root systems are found in tropical areas where high concentrations of atmospheric methane have been observed . Specifically, they occur in tropical semiarid to humid savanna, and tropical seasonally dry semideciduous to evergreen forests . Deep roots that access the water table may contribute disproportionately to transpiration fluxes . In such cases, CH4 dissolved in groundwater would presumably be entrained in the transpiration stream in a manner similar to CO2 from root respiration .There are several recent reports suggesting that tropical forests may be larger sources of CH4 than previously believed. The most comprehensive analysis used a satellite-mounted instrument to show that atmospheric CH4 concentrations are far greater than expected from ground-based emissions inventories of tropical rain forests . The deviation between modeled and observed column-averaged atmospheric CH4 concentrations was especially large over the Amazon Basin and was correlated with the distribution of broadleaf evergreen forest. Frankenberg et al. noted that the discrepancies in measured and modeled CH4 concentrations could be explained by underestimates of known emissions sources such as wetlands, biomass burning, termites and cattle. The measurements were taken during the dry season when wetland emissions should be lowest and biomass burning emissions should be highest, suggesting the biomass burning was the more important source. However, localized measurements of atmospheric CH4 concentrations show that there can be significant biogenic CH4 sources in tropical upland forests.

Methane concentration profiles in three upland forests of the Brazilian Amazon showed a CH4 source within the lower 10 m of the forest canopy , and nighttime pooling of CH4 at 2 m above the soil surface was observed in a mixture of forest and savanna in Venezuela . In both cases, when extrapolated to large areas, the estimated CH4 emission rates were potentially significant on a global scale . Scharffe et al. concluded that soil emissions were a relatively small contribution to CH4 sources at the Venezuelan site and suggested that termite mounds and waterlogged pools were unmeasured CH4 emission hotspots. Crutzen et al. reinterpreted these data as evidence of an aerobic plant CH4 source. Regardless of whether the source of the CH4 in these systems was vegetation or a combination of several known sources, none of which can be distinguished by these studies, it is clear that CH4 exchange between tropical upland ecosystems and the atmosphere has not been adequately characterized.Frankenberg et al. recognized that the discrepancies in measured and modeled CH4 concentrations could be explained by a “… hitherto unknown methane source that might be directly related to the broad leaf evergreen forest.” Just 7 months later, Keppler et al. published the first observations supporting one possible unknown CH4 source—direct emissions from aerobic vegetation. They reported that CH4 was emitted from every plant tissues tested, including detached leaves from 30 species, leaf litter and intact plants. The data of Keppler et al. suggested that sunlight, temperature and physiological activity were key variables regulating aerobic CH4 emissions. The sunlit rates for intact plants were significantly higher than those for detached leaves , dark emission rates for intact plants and detached leaves were significantly lower than sunlit leaves ,growing strawberries hydroponically and the temperature coefficient was about 2 over the range 30–70 °C. The process appeared to be non-enzymatic because emissions increased monotonically up to 70 °C and CH4 was emitted from commercially available apple pectin. More recently, Dueck et al. used an isotope-labeling technique in an attempt to verify emissions of CH4 from aerobic plant tissues. This approach indicated rates that were not significantly different from zero, and at best, an order of magnitude lower than those of Keppler et al. . Increasing the amount of plant biomass in the experimental chambers improved the detection limit of their technique and suggested that little or no CH4 is emitted by plant tissues. These data suggest that the fluxes reported by Keppler et al. were an artifact of their methods. The experiments performed by Dueck et al. were more controlled and physiologically relevant than those by Keppler et al. , but it is unclear whether the hydroponic system they used effectively excluded CH4 oxidizing bacteria, which are aerobic and capable of consuming CH4 produced by plant tissues. The negative rates of CH4 production reported by Dueck et al. were reasonably interpreted as experimental error, but they could also be interpreted as net consumption of CH4 and it is unclear whether the leak tests they performed were long enough to allow for this possibility. Given the absence of in situ measurements of aerobic plant CH4 emissions, it is instructive to compare the Keppler et al. rates to other volatile organic carbon compounds such as methanol, which are relatively well understood. There are many different VOCs, but the total flux from foliage is dominated by a few compounds such as isoprene and methanol. The initial studies of methanol emissions from plants reported rates from mature leaves that typically ranged from about 0.8 to 44 µg g–1 h–1 , which is at least an order of magnitude higher than the CH4 emission rates observed by Keppler et al. under similar conditions of light and of temperature. Methanol emission rates from young leaves are even higher than rates observed for mature leaves .

Lower methanol emission rates have since been reported for most plants, but average methanol emission rates for mature sunlit leaves are at least 1.5 µg g–1 h–1, which is four times the CH4 emission rate reported by Keppler et al. . These figures suggest that the global contribution of CH4 from aerobic plant biomass, if it occurs at all, are considerably less than global emissions of methanol, which are estimated to be between 100 and 260 Tg year –1 .Keppler et al. offered a provocative global extrapolation of their intact plant CH4 emission rates that suggested up to 243 Tg year –1 of CH4 was emitted from this new source. This figure was derived by scaling leaf-mass-based emission rates to the globe with day length, growing season length and total net primary productivity as driving variables, all stratified by the major biomes. Alternative extrapolations of the same data were subsequently published that accounted for differences in foliage turnover rates between biomes, significantly lowering the global strength of a putative aerobic plant source . To further constrain the potential magnitude of global CH4 emissions from upland plants, we used a foliar VOC emissions model—MEGAN or Model of Emissions of Gases and Aerosols from Nature—to incorporate certain canopy and physical processes that were not considered by Kirschbaum et al. and Parsons et al. . In particular, we used the temperature responses reported by Keppler et al. and accounted for the effects of self-shading within the plant canopy. We used MEGAN with the assumption that the mechanism of CH4 production, if it exists at all, shares some features of the biochemical pathways that produce other VOCs such as methanol. MEGAN includes a detailed canopy environment model that calculates solar radiation and leaf temperature of sun and shade leaves for each of five canopy depths. Driving variables include wind speed, humidity, soil water content, above-canopy direct and diffuse solar radiation, and ambient temperature. MEGAN includes emission factors for light-dependent and light-independent components of emissions, and irradiances that vary because of self-shading in the plant canopy. Light-dependent and light-independent emissions of CH4 were estimated based on the emission factors recommended by Keppler et al. . Although Keppler et al. did not report light response curves, we assumed that emissions increase nearly linearly with irradiance to a saturation point. This is the behavior we observe for other biogenic VOC and is thus a reasonable starting point for the CH4 extrapolation. The emission algorithm for dark emissions was based on the temperature response shown in Figure 1 of Keppler et al. . A range of global annual CH4 emission estimates was generated using different combinations of the alternative land cover and weather databases described by Guenther et al. . Our parameterization of light and temperature in the MEGAN model is similar to the global model of aerobic CH4 emissions developed by Butenh off and Khalil . The global distribution of CH4 emissions from foliage simulated with MEGAN is shown in Figure 1. Tropical forests are a major source region, which agrees with the predictions of Keppler et al. and the observations of Frankenberg et al. . The annual global CH4 emission from living vegetation estimated with MEGAN ranged from 34–56 Tg year –1, depending on the land cover and weather data used to drive the model. This figure is nearly one order of magnitude lower than the highest estimates provided by Keppler et al. and is consistent with the magnitude of alternative extrapolations provided by Kirschbaum et al. and Parsons et al. , and the global model developed by Butenhoff and Khalil . Our estimates would be about an order of magnitude lower if we had used the mean rate reported by Dueck et al. of 21 ng g–1 h–1.Observations of unexpectedly high atmospheric CH4 concentrations in forested landscapes have revealed a gap in our understanding of trace gas emissions. The wide variety of plausible explanations offered for these observations encompass specialties ranging from soil microbiology to plant physiology to atmospheric chemistry. These disparate research communities should continue to study the problem in order to inform modeling and public policy related to climate change. It is doubtful that these observations can be explained by the aerobic plant CH4 source proposed by Keppler et al. because independent extrapolations and rate measurements suggest emission rates from plant tissues are far lower than initially believed .

These insecticides have outstanding efficacy in crop protection against a number of pest invertebrates , especially piercing–sucking insect herbivores . However, neonicotinoids have limited efficacy against lepidopteran and coleopteran pests . Advantages associated with systemic insecticides over nonsystemic insecticides include: 1) reduced sensitivity to spray coverage and canopy penetration , as the active ingredient translocates within and among plant tissues, 2) high water solubility and xylem mobility of the active ingredients , 3) continuous plant protection for an extended period of time without repeated applications , and 4) protection from direct insect herbivore damage and reduced indirect crop damage by pathogens they transmit . Due to these advantages, systemic insecticides, including neonicotinoids, have been widely adopted across a diverse range of food production systems worldwide since the 1990s . Considering the versatility and widespread adoption, pests evolving physiological and behavioral resistance to systemic insecticides should be a concern to global food security.In this opinion-based article,hydroponic grow kit we hypothesize that drought will increase the likelihood of pests evolving behavioral resistance to systemic insecticides.

Moreover, we predict that climate change will increase the likelihood of severe drought events in many agricultural regions and adversely affect the uptake and vascular flow in crop plants treated with systemic insecticides. If so, this may lead to nonuniform distribution of the active ingredient in plant tissues. Under this scenario, pests that can sense and avoid acquisition of lethal dosages of systemic insecticides within crop plants will have a selective advantage.In addition, we wish to highlight the possible effect of drought on the performance of systemic insecticides as a justification for more research into the many ways environmental factors can affect, directly and indirectly, both the performance of insecticides and the risk of target insect pests developing resistance.In 1936, a study showed that levels of aphid infestation in wheat plants were negatively associated with soil content of selenium . This discovery led to experiments with selenium uptake from soils as a systemic insecticide, giving rise to a new method of insecticide applications . In modern crop protection, systemic insecticides are applied to crops in four ways: 1) coating seeds surface prior to planting , 2) spraying of crop foliage or soil, 3) soil drenching after crop emergence, and 4) the addition of the insecticide to starter solutions used at transplanting . Seed treatment and soil applications are the two preferred methods, representing  60% of neonicotinoid insecticide applications worldwide . Seed coating is the primary method for delivering neonicotinoid insecticides to agricultural crops throughout the world . This method is considered a “safe” alternative to conventionally applied insecticides, because seed coating minimizes drift of pesticides to nontarget surfaces and organisms .

In addition, seed coating significantly decreases the amount of insecticide applied to a crop field area compared with conventional spray methods . Neonicotinoid insecticides and fipronil currently account for approximately one-third of the world insecticide market . Their success is due to high efficacy in arthropod pest management, flexibility of application method, and extended residual effect . The neonicotinoid class of insecticides is applied to a wide range of agricultural and horticultural crops, including cotton, maize, potato, and oil seed rape .Absorption and translocation of systemic insecticides are linked to physical and chemical characteristics of the insecticides’ octanol water partition coefficient and dissociation constant . Once absorbed by crop roots, a high water solubility increases the likelihood of uniform distribution and bio-availability of the active ingredients within plant tissues . Typically, the xylem transport system is responsible for translocation of systemic insecticides , but some systemic insecticides can also move within the phloem, or both . Radiolabeled imidacloprid has been observed moving toward leaf tips and margins after foliar applications . However, predicting the translocation of insecticides in treated plants is difficult due to variable plant morphology, physiology, and chemical properties of the specific compounds. Generally, translocation occurs faster in younger stems and leaf tissues , but abiotic factors, such as weather conditions and soil properties, may affect the uniformity of systemic insecticide distribution among plant tissues . Abiotic factors, including light intensity , temperature , relative humidity, and wind, influence water transpiration from leaves, thus influencing movement of systemic insecticides in the vascular tissues.

Depending on environmental conditions, a plant may direct water to certain parts of the plant, which will influence the uniformity of systemic insecticide distribution . Additionally, the uptake of a systemic insecticide is affected by the rate of transpiration of water leaving the plant . This was demonstrated through drench tests, which determined that systemic insecticides require specific amounts of water to be most efficacious .Insecticide resistance was first reported over 100 yr ago . Since then, there have been 11,254 separate records of 546 pest species evolving resistance to 331 insecticidal compounds . Most of these records refer to “metabolic” or “target-specific” insecticide resistance, which are driven by genetic and physiological selection pressures . In addition to target-specific insecticide resistance, “behavioral insecticide resistance” has been reported in >30 species of insects for >40 yr . Insect pests expressing behavioral insecticide resistance avoid contact with or ingestion of a lethal dose of an insecticide, thereby increasing their survivorship . There are a variety of behavioral resistance strategies of pests, and a few are briefly described below. Reduced leaf tissues penetration by piercing–sucking insects has been shown to function as a resistance mechanism to many different insecticides , because it reduces the insecticide acquisition rate . For example, the adult tea mosquito bug Helopel.This theivora demonstrated avoidance of multiple insecticidal compounds . When exposed to insecticide-treated plants, the tea mosquito bug also shifts its oviposition behavior away from tea shoots, where the insecticide is believed to have the highest concentration . Like the tea mosquito bug, diamondback moth Plutella xylostella L. populations have exhibited behavioral avoidance through oviposition site selection . In a different study, diamondback moths larvae and ovipositing females of two diamondback moths strains expressed different behavioral responses when offered cabbage leaves with and without insecticide treatments . The latter study showed a clear and positive relationship between the level of physiological susceptibility to the insecticides by diamondback moth strains and each strain’s level of avoidance to the insecticide-treated cabbage leaves . In addition, insecticide resistance behavior led to the decline in performance of glucose-based attractants for control of German cockroaches Blatella germanica L. in restaurants and food warehouses in the late 1980s and early 1990s . While high selection pressure favored cockroaches avoiding the attractants,4x8ft rolling benches there was a significant fitness cost to German cockroaches of being glucose averse . When studying behavioral insecticide resistance, it is a fundamental assumption that arthropod pests can somehow sense the presence of pesticides and therefore adjust their feeding and oviposition behavior to avoid contact with the lethal active ingredient. The specific mechanisms responsible for such ability to sense the presence of pesticides are not well described, and that may be considered a weakness of the hypothesis discussed in this article. However, it is well-established that evolution has led to strong selection pressures on arthropod populations regarding both their selection of both host and oviposition plants. And a large body of research has been published on the evolution and nonrandom host selection by arthropods. We are therefore arguing that some of the basic traits used by arthropods to optimize their selection of feeding and oviposition sites may also enable them to avoid plant tissues with high concentrations of pesticides. Even though not directly linked to the discussion of main hypothesis in this article, we wish to highlight the importance of studying the many ways environmental factors can affect, directly and indirectly, both the performance of insecticides and the risk of target insect pests developing resistance.Climate change is already predicted to cause significant challenges to agriculture and pest management strategies. Using current greenhouse gas emission scenarios, increases to global temperatures and changes to regional patterns of precipitation and humidity have been predicted , and a likely scenario is more frequent and also more severe drought conditions .

An important body of research has demonstrated that elevation of CO2 concentration in the atmosphere, as a consequence of climate change, may enhance the effectiveness of Bacillus thuringiensis toxins that are applied as foliar applications . The authors demonstrated that the combination of Bt toxins and elevated atmospheric CO2 concentration led to a reduced nitrogen concentration in leaves, so that herbivorous insects had to consume more leaf material in order to acquire enough nitrogen, and that increased their ingestion of Bt toxins. However, regarding expression of Bt toxins in genetically modified crops, elevated atmospheric CO2 concentration appears to reduce the toxin expression , which supports the argument articulated in this article that climate change may adversely affect the performance of systemic insecticides. We are unaware of similar reports detailing any of the possible effects of climate change on the performance of non-Bt systemic insecticides. However, it seems reasonable to speculate that climate change, through its effect on ambient temperature, humidity, and accessible soil water, will affect the rate of transport in the plant’s vascular system . If so, this may lead to a reduction in both uptake and vascular flow of systemic insecticide. This phenomenon represents a serious threat to global food security, as most insect pest management is still based on insecticide applications. Several agricultural systems already demonstrate evolved behavioral resistance, which could be exacerbated by drought. Significant differences in Colorado potato beetle Leptinotarsa decemlineata larval mortality and development among vertical leaf positions provide evidence that the concentration of imidacloprid and its metabolites were unevenly distributed in the potato foliage 8–14 wk post planting . Olson et al. indicated that the concentration of imidacloprid was lowest in the younger tissues of the upper leaves and highest in the older, lower leaves. While these leaves act as toxic barriers to susceptible Colorado potato beetles, beetles could easily develop behavioral resistance that would allow the insects to preferentially feed on the lower insecticide concentrations in the upper canopy. Therefore, the risk of behavioral resistance increases in this system, if the younger upper leaves receive a lower concentration of systemic insecticide . Similarly in sugar beet, the concentration of imidacloprid was six times higher in lower leaves compared with the upper leaves 49 d after application . A similarly nonuniform distribution pattern was noticed with the carbofuran in Douglas firs , which documented decreasing concentrations of the chemical from the roots to the upper part of the tree. These examples highlight nonuniform systemic insecticide distribution within treated plants, and such within-plant gradients may be exacerbated under the effects of climate change. Another significant factor which may lead to an increase in behavioral resistance within a pest population is the unequal amount of insecticide between neighbor plants receiving the same treatments. This can be caused by variable amounts of water available in the soil, a situation likely to occur under drought. Higher quantities of soil moisture favor water uptake, and consequently insecticide uptake . Castle et al. observed little difference in imidacloprid concentration between lower and upper sections of citrus trees, but found significant variation among the trees. Variability in the uptake of insecticide for these trees could be explained through different soil moisture contests, with optimal irrigated plants in the field able to incorporate more product than suboptimally irrigated plants. This situation is exacerbated during a drought, creating an opportune situation for populations of pest insects to develop behavioral resistance . In conclusion, as we prepare for the effects of climate change and predicted increases in frequency and severity of droughts, food production systems face a wide range of direct and indirect challenges. Climate change will, both directly and indirectly, affect crop maintenance, occurrence of invasive species, and existing pest management practices. Compared to the different types of physiological resistance, behavioral insecticide resistance mechanisms have received considerably less research attention . In this article, we discussed potential effects of climate change on the performance of systemic insecticides, and we argue that more research is needed to thoroughly study the likelihood and potential impact of the following scenarios: 1) drought suppression of systemic insecticide uptake and vascular flow rates, 2) the distribution and concentration of systemic insecticide within plant organs , 3) target insect pests developing the ability to sense and avoid leaf tissues with high concentrations of systemic insecticides , and 4) behavioral resistance becoming more widespread as consequence of climate change.

The 75th percentile varied widely by commodity: $6,172 for those primarily employed by FLCs, $10,572 for those in grapes and $29,465 for those in mushrooms.The number of individuals and jobs reported by agricultural employers increased in the 1990s, reflecting increased production of labor-intensive fruit and vegetable crops and, the data suggests, more farm workers each worked a fewer number of hours. With the state’s minimum wage at $6.25 per hour after Jan. 1, 2001 , the earnings reported by employers suggest that most farm workers are employed fewer than 1,000 hours per year . FLCs increased their market share in the 1990s, but dependence on them varied by commodity. For example, FLCs rather than citrus growers reported many citrus workers, while dairy employers reported most dairy workers. FLCs are associated with low earnings, which suggests few hours of work — the median earnings reported by FLCs for their employees in 2001 were $2,650, or 400 hours if workers earned the state’s $6.25 minimum wage. California’s farm labor market has large numbers of workers searching for seasonal jobs; FLCs are matching an increasing share of these workers with jobs, resulting in lower earnings for FLC employees.If FLCs are most likely to hire recently arrived and unauthorized workers,black plastic plant pots bulk as the National Agricultural Worker Survey suggests, FLCs serve as a port of entry for immigrant farm workers.

The impact of guest workers, legalization and earned legalization will depend on the details of any new program. If the status quo continues, the percentage of unauthorized workers is likely to rise. Alternatively, if there were a legalization program, farm workers might more quickly exit the farm workforce. However, an earned legalization program could slow this exit if workers were required to continue working in agriculture to earn full legal status. The next step in this analysis is to examine the mobility of individual farm workers over time and geography, examining where workers migrate during 1 year and patterns of entrance to and exit from the farm workforce . Do farm workers who increase their earnings by moving to non-farm jobs stay in non-farm jobs, or do they sometimes return to agriculture? Are geographic and economic mobility linked for workers who get non-farm jobs? Answers to these questions will help to determine the trajectory of the farm labor market.In addition to its historical roles in paper production and as ornamentals, varieties of the wild grass Miscanthus can produce high yields of harvestable vegetative biomass while maintaining and potentially increasing soil carbon. These features, enabled by C4 photosynthesis, perenniality, and related high efficiencies of light, nutrient, and water use, make Miscanthus and its close relatives promising candidates for economically feasible and sustainable bio-energy crops. Continued genetic improvement of bio-energy feed stocks is needed to enhance productivity and ensure that these crops remain robust in the face of ongoing biotic and abiotic stresses.

This is particularly true for perennial grasses, where the advantages in economic and environmental sustainability relative to annuals depend on the longevity of the crop once established. Although perennial crops have tremendous potential for maximizing agricultural yields and minimizing environmental impacts, our knowledge of their biology and ability to manipulate their genetics lags well behind that in annual crops. Polyploidy is also common within the Saccharum complex, a group of closely related and highly productive perennial C4 grass species in the subtribe Saccharinae that includes sugarcanes and miscanthus. Intergeneric hybrid “miscanes” have been made by crossing miscanthus with hybrid sugarcanes, suggesting that natural genetic variation in these two genera could be combined in order to blend desirable traits . Here we establish miscanthus as a genomic model for perenniality and polyploidy, and develop a foundation for genomic variation that will enable the future improvement of perennial biomass crops. We describe a draft chromosome-scale genome sequence for M. sinensis, prove that miscanthus is a paleoallotetraploid by analyzing the distribution of transposable elements across its genome, and establish the timing of key evolutionary events. By mRNA sequencing, we identify genes preferentially expressed in rhizomes, stems, and leaves, and explore the unique transcriptional dynamics of nutrient mobilization in this rhizomatous perennial grass. Unlike most perennial Andropogoneae, which are restricted to tropical or subtropical regions, the Miscanthus genus comprises species that naturally range from tropical to subarctic regions. Genomic analysis of 18 miscanthus accessions sequenced for this study, in addition to reduced representation genotyping of over 2000 accessions collected in the wild from east Asia, reveals extensive population structure and interspecific introgression, which further contributes to the genomic diversity of the genus Miscanthus.

We assembled the M. sinensis genome into n = 19 chromosomes by combining short read whole-genome shotgun and fosmid-end data with in vitro and in vivo chromatin proximity libraries . The reference accession is the previously characterized doubled haploid DH1, which as expected is homozygous throughout. The genome assembly anchors 1.68 Gb of contigs to chromosomes, with a contig N50 length of 33.1 kb and pre-HiC scaffolding N50 length of 190 kb . An additional 0.20 Gb of contig sequence in scaffolds is not yet placed on linkage groups; highly repetitive sequences are problematic and missing from the assembly . We validated the assembly at chromosome scale by comparison with an integrated genetic map with 4298 assignable markers . We predicted the structure of 67,967 protein-coding genes based on several lines of evidence, including homology with other grasses and deep transcriptome data for miscanthus and sugarcane. These predicted genes account for an estimated 98% of protein-coding genes, with 94% assigned to a chromosomal position . These genes are embedded within a sea of transposable element relicts and other repetitive sequences, which account for 72.4% of the M. sinensis genome assembly. The most common class of assembled transposons are gypsy long terminal-repeat retrotransposons . The paleotetraploidy of miscanthus is evident at the sequence level, since each sorghum chromosome aligns to a pair of M. sinensis chromosomes, after accounting for the chromosome fusion of ancestral sorghum 4- and 7-like chromosomes that reduces the karyotype from n = 20 to n = 19 . As expected from earlier genetic maps, the miscanthus and sorghum genomes show extensive 2:1 conserved collinear synteny , consistent with a whole-genome duplication in the Miscanthus lineage. While it has been suggested that this duplication could be shared with sugarcane, comparison of M. sinensis and S. spontaneum genomes shows that the duplications in the two lineages are distinct . Although the doubled genome and disomic genetics of miscanthus is suggestive of an allotetraploid history,flower pot wholesale neither a mechanism nor timing for paleotetraploidy has been described, in part due to the absence of known diploid progenitor lineages. We address this further below. Regarding the more than twofold difference in bulk genome size between sorghum and miscanthus, we find that lengths of coding sequence and introns are generally similar , with overall differences arising from increased intergenic spacing in miscanthus due to transposon insertion, as well as by the expansion of repetitive pericentromeric regions, which are only partially captured in the assembly . The chromatin conformation contact map exhibits an enrichment of centromeric and telomeric contacts, respectively, consistent with the interphase nuclear “Rabl” conformation as seen in the barley genome. We identified locally interacting chromosomal compartments for which A compartments have a higher gene density and B compartments have lower gene density and tend to occur predominantly in the pericentromeric region, as observed in other plants.An allotetraploid origin for a paleotetraploid species is commonly demonstrated by showing that one set of its chromosomes is more closely related to some diploid lineages to the exclusion of others. Because there are no known candidates for the diploid progenitors of tetraploid miscanthus, this approach cannot be used here. Instead, we used a new method that relies on the chromosomal distribution of repetitive elements, which can provide robust markers for sub-genome ancestry.

We sought repetitive sequences whose presence is enriched on one member of each homeologous chromosome pair . Such sequences are definitive markers of allotetraploidy, and occur as relicts of repetitive elements that were active in only one of the two diploid progenitors prior to hybridization and genome doubling. Importantly, the method does not require access to or even knowledge of living representatives of the progenitor lineages. We found 1187 13-bp sequences whose pairwise enrichment pattern consistently partitions homeologous chromosome pairs between distinct A and B sub-genomes . This observation establishes the past existence of distinct A and B progenitor lineages , and the allotetraploid origin of miscanthus. Although we can use these markers to assign each miscanthus chromosome in bulk to the A or B sub-genome, we find evidence for the balanced reciprocal exchange of distal segments between homeologous chromosomes such that dosage remains intact . Based on consistency with our dense genetic map, these are clearly bona fide homeologous exchanges rather than misassemblies. The observed distal reciprocal exchanges likely occurred either by mitotic recombination in the vegetative tissue of an AB F1 hybrid founder prior to genome doubling, or by aberrant homeologous recombination after allotetraploidy. The concentration of these exchanges toward the ends of chromosomes is consistent with the proximity of these regions in a telomeric bouquet conformation. The maintenance of discrete A/B patterns of diagnostic 13-mers in these distal segments implies that these exchanges occurred by single crossover events rather than recurring recombination throughout the distal regions of the chromosomes, which would blur the distinctive A/B 13-mer signature. Discrete homeologous exchanges are often observed in newly formed allotetraploids and are thought to occur in response to a new meiotic environment. In studies of other polyploids, homeologous replacements that alter the balance between A and B alleles are common; when such variants are segregating in apopulation, the resulting genetic variation can underlie quantitative trait loci. In contrast to these studies, however, in Miscanthus, we find predominantly balanced reciprocal exchanges that alter chromosomal linkage, but do not change A/B dosage, and no evidence that these segmental exchanges are segregating in our sequenced samples, suggesting that the reciprocal homeologous exchanges are the result of ancient events that have become fixed in Miscanthus. In addition to these long fixed reciprocal exchanges, there are several shorter internal homeologous segments that could correspond to nonreciprocal or recurrent exchange. These segments will be interesting to study further. From the identification of distinct A and B sub-genomes, we see that the sorghum-7 and -4-like chromosomes that fused to form miscanthus chromosome 7 were both derived from the B progenitor. While it is possible that the fusion occurred in the B progenitor itself prior to hybridization, the absence of other Saccharinae with n = 9 chromosomes, and the likelihood of chromosome instability in the aftermath of allotetraploidization, suggests that the fusion occurred after allohybridization. The timeline of paleotetraploidy in miscanthus can be established through inter- and intra-subgenome comparisons . We estimate that the A and B progenitors diverged from their common ancestor ~7.2 Mya , based on the synonymous differences between homeologous protein-coding genes . After this divergence but before hybridization, the two progenitors evolved independently; evidence of their species-specific transposable element activity appears in the contemporary Miscanthus genome as subgenome-specific repeats. Consistent with this hypothesis, we find several LTRretrotransposon families within only one of the two subgenomes, and estimate that they were actively inserting during the period ~2.5–6 Mya . In contrast, transposon activity after the allotetraploidy event should be distributed across the entire Miscanthus genome without regard to subgenomes. Also, consistent with this picture, we find a burst of transposon activity that is not subgenome-specific starting ~2.5 Mya, which serves as our best estimate for the allotetraploid origin of Miscanthus . Finally, the interfertile sister species M. sinensis and M. sacchariflorus diverged ~1.65 Mya , consistent with speciation occurring after allotetraploidy. Chromosome-level comparisons of repetitive elements and protein sequences confirm that the polyploidies of Miscanthus and sugarcane occurred independently . Common hallmarks of allopolyploidy are asymmetric gene loss and biased gene expression between subgenomes, which are both thought to arise from epigenetic asymmetries in the aftermath of allohybridization. Comparing miscanthus and sorghum genes, we find that ~29% of sorghum genes have been lost on one of two subgenomes; conversely, ~71% have co-orthologs on both subgenomes .

The cumulative crop evapotranspiration during the 29 day experimental period was equal to 65.3 mm, and daily ETC varied from 1.68 to 3.39 mm. Irrigation was initiated on 16 August 2010 and terminated on 13 September, 2010. Irrigation and rainfall were recorded daily and drainage volume was measured 3 times per week throughout the trial period. Daily irrigation was applied in 5 short pulses using an automated irrigation controller, with 2 h breaks between irrigation pulses. The amount of irrigation water applied was slightly higher than ETC for the period. A total of 70 mm of rainfall fell during the experimental period, including a single event of 52 mm on 3 September 2010.The Kcb values for different months were taken from Allen et al. , assuming 70% canopy cover and no ground cover, since the lysimeter was placed in a well-grown citrus orchard, and the lysimeter soil surface was kept free of weeds during the experimental period. Estimated Tp and Ep values during the experimental period varied from 1.5 to 3.2 mm day−1 and from 0.5 to 1.1 mm day−1, respectively. The total Tp and Ep during the experimental period were 59.3 and 21.1 mm, respectively. Note that the potential ETC was larger than the 10-year average,plastic growers pots which was used for irrigation . However, since additional rainfall occurred during the experiment, no shortage of water was expected.

HYDRUS reduces the potential transpiration to the actual transpiration by integrating actual water uptake over the entire root zone, while considering water and salinity stresses. HYDRUS implements a scheme whereby the actual evaporation remains equal to the potential evaporation as long as the pressure head at the boundary is higher than a critical pressure head hCritA, considered to be −10,000 cm in our study. When the pressure head on the soil surface boundary falls below hCritA, the potential evaporation is reduced. The total rainfall was considered to be equal to the effective rainfall for the purpose of modelling, and canopy interception was not considered because through fall and stem flow account for about 90–95% of precipitation in citrus . Runoff was also not considered as the lysimeter was a closed system, which does not allow for surface runoff.The simulation domain was represented by a 110-cm deep and 100-cm wide cylindrical cross section. Drip irrigation was modelled as a circular line source 25 cm from the centre of the lysimeter with a uniform water flux along the drip line. This simplification was made to enable HYDRUS to model this problem in a 2D axi-symmetrical mode , rather than in a full 3D mode, which would be computationally much more demanding. Additionally, since the surface wetted area and input flux densities under drippers were dynamic, an option that we would not be able to model with HYDRUS in a 3D mode, we assumed that the simplification of the problem to axi-symmetrical 2D was adequate. Moreover, the drainage system laid out in the lysimeter also supported the use of an axi-symmetrical domain as the drainage pipes run in a circular fashion to collect and flushdrainage water out of the lysimeter.

The transport domain was discretized into 3294 finite elements, with a very fine grid around the dripper and near the outflow , with gradually increasing element spacing farther from these two locations . Simulations were carried out over a period of 29 days.Since most soils on which citrus is grown in South Australia are coarse textured soils with good drainage, high oxygen levels, low organic matter, and low microbial populations, denitrification and mineralisation was assumed to be negligible in this study. Similarly, the soil adsorption of nitrate was also considered to be negligible since both nitrate and solid surfaces are negatively charged. Plant uptake of non-adsorbing nutrients like nitrate is controlled mainly by mass flow of water uptake . Therefore, it was assumed that nitrate was either passively taken up by the tree with root water uptake or moved downward with soil water. Spatial distribution of nitrate in the transport domain was thus simulated using the convection–dispersion equation for a nonreactive tracer. Molecular diffusion was neglected as it was considered negligible relative to dispersion. The longitudinal dispersivity was considered to be 5 cm, with the transverse dispersivity being one-tenth of this . Similar values of these parameters have been used in other studies .Citrus trees in this region are fertilised from early September till March, and in drip systems fertilizers are mostly applied with the second irrigation pulse for the day. All fertigation scenarios reported here are hypothetical. Fertigation was assumed to be supplied with the same quantity of water as in irrigations without fertigation and to conform to the 2D axi-symmetrical domain. For the initial scenario, 5 fertigation pulses were applied from 30 August 2010 at the rate of one fertigation pulse each day. These were followed by 2 days without fertigation and then another 5 daily fertigation pulses.

The resultant dose of N for the period from 16 August till 13 September was calculated based on recommended fertilizer application practices for 5–6 year old orange tree. The seasonal recommended dose of nitrogen for an orange tree ofthis age is 139 g N applied from September to March . Hence for the seasonal simulation, nitrogen was assumed to be applied in equal monthly doses , in similar pulses as described for the experimental period. The simulation was run for 300 days in order to evaluate the fate of seasonally applied nitrogen fertilizer in citrus. Further scenarios examining the impact of timing of nitrogen application on the efficiency of nitrogen uptake simulated a fertilizer application either at the beginning , middle , or end of the daily irrigation scheme. Since the daily irrigation consisted of 5 pulses, fertigation was applied during the 2, 3 and 4 irrigation pulse in the PF1, PF2 and PF3 scenarios, respectively. It is a common practice that the initial and final irrigation pulses are fertilizer free to ensure a uniform fertilizer application and flushing of the drip lines. In addition to these simulations,blueberry in pot two continuous fertigation scenarios were also performed to compare pulsed and continuous fertigation. The first scenario consisted of applying the same amount of fertilizer spread across all irrigation pulses , except for the last irrigation pulse to enable flushing. The second scenario consisted of continuous irrigation of the same duration and irrigation amount as under pulsed treatments, with fertigation at all times , except for the same period of flushing at the end of irrigation. The fertigation scheme in PF1, PF2, PF3 and continuous scenarios was assumed to start from 17 August 2010. All fertigation simulations were run as for the irrigation experiment, that is for 29 days .To evaluate the impact of the quantity of irrigation water on nitrate leaching, additional simulations were run for all scenarios with 50% , 75% , and 125% of irrigation water applied in the field experiment .The water content distribution in the soil reflects water availability to plants, and plays a crucial role in water movement through and out of the root zone. Volumetric water contents simulated by HYDRUS 2D/3D are compared in Fig. 5 with the measured values obtained using EnviroSCAN probes 15 cm away from the dripper. Simulated values matched measured values well, both spatially and temporally. However, deviations between simulated and measured values were observed at day 19 of simulation, particularly in the upper 50 cm of the soil profifile; at later times this difference was not observed. Simulated and observed daily and cumulative drainage are compared in Figs. 6 and 7, respectively. Both variables showed a close match between simulated and measured values. It can be seen that simulated daily drainage remained slightly below observed values , except for the initial higher leaching on day 1. However,the total drainage observed in the lysimeter was matched closely by the model. The high peak on day 21 represents the effect of high rainfall on that day, which also was very well predicted by the model. However, the cumulative drainage remained slightly over predicted during the initial 15 days, after which the simulated and observed values matched well. Model evaluation was performed using a number of model performance parameters calculated using measured and model generated soil water contents . The mean absolute error varied from 0.006 to 0.22 cm3 cm−3 and the root mean square error ranged between 0.007 and 0.028 cm3 cm−3, which indicated small deviations between measured and simulated values. However,the maximum values of MAE and RMSE were observed at day 19, confirming the deviations shown in Fig. 5 at this time. However, the values of paired t-test between measured and simulated water contents showed insignificant differences at 5%level of significance at all times.Values of the coefficient of determination varied between 0.68 and 0.96, indicating a reliable generation of water contents by the model at all days of simulations.

Similarly, the Nash and Sutcliffe efficiency coefficient values ranged from 0.17 to 0.96, indicating a good performance of the model for the prediction of water contents in this study.However,the relative efficiency value at day 19 reveals unsatisfactory performance of the model at that point according to the criteria suggested by Moriasi et al. . The values of MAE, RMSE, r2, E, and RE for the drainage flux were 2.87, 4.14, 0.97, 0.94, and 0.78 , respectively, which also showed a robust performance of the model for drainage fluxes from the lysimeter. The close match of both water contents and drainage fluxes indicates that the HYDRUS 2D/3D software can be successfully used to predict water movement and drainage fluxes in a lysimeter planted with a citrus tree. Other studies have also reported good performance of this software for various soil, water, and crop conditions under pressurised irrigation systems . Simulated water balance components over the 29 day experimental period are shown in Table 3. It can be seen that simulated drainage, which is similar to the amount measured in the lysimeter, represents 48.9% of the total water balance. A much higher seasonal drainage has been reported for a lysimeter planted with an orange tree in a fine sandy soil . High drainage is bound to occur in highly permeable, coarse textured soils, such as the sand/loamy soil used in this study, where water drains easily and quickly from the root zone because gravity dominates over capillarity . However, Sluggett estimated deep drainage in the range of 6.1–37.2% under citrus trees growing in light textured soils in the Sunraysia region of Australia. A major contributor to the high drainage measured in this experiment was the high amount of water applied, mostly as a result of large rainfall events. Simulated plant water uptake was estimated to be 40% of the water application, indicating low irrigation efficiency of the drip system. The daily plant uptake varied from 1.2 to 3.14 mm . However, plant uptake is a very complex process, and depends on a number of parameters describing the root and canopy development. Since the HYDRUS model does not support a dynamic behaviour of the root system and considers only the static root parameters, root uptake was optimised on the basis of a changing transpiration rate over time. Additionally, since in the present study we dealt with a tree, for which the root distribution development over time is not as fast as observed for seasonal crops like cereals, the root development was considered relatively constant for the modelling purpose. Hence, a static root distribution and variable atmospheric conditions produced a good approximation of plant uptake, as has been revealed in a number of earlier studies that used HYDRUS for modelling purposes .Simulated distribution of nitrate at selected times after commencement of fertigation is shown in Fig. 8. Concentration of NO3-N was maximum at the centre of the plume below the dripper, with a gradual decrease in N concentration towards the outer boundaries of the plume. Subsequent irrigation and fertigation pulses resulted in enlargement of the plume, with a rapid lateral and vertical movement of NO3-N. It is worth noticing that after 15 days of fertigation all nitrate still remained in the lysimeter, reaching a depth of 70 cm. The maximum nitrate concentration at this time was at 20 cm.

Our age adjustment delivers a measure that could be called ‘completed polygyny’ by analogy to ‘completed fertility’. The populations exhibiting surprisingly high levels of polygyny by our definition—e.g. the Ache´, Hadza, Maya, English and Krummho¨rn populations—reflect the prevalence of serial monogamy, not polygyny in the usual sense of multiple concurrent wives. Although most anthropological analyses of polygyny limit the definition of the term to two or more co-occuring wives of one man, we forego the sequential/concurrent distinction because a male’s wealth is generally shared to some degree across all wives and the children of each over the male’s lifetime and as we show later, the elasticities2 of fitness with respect to times married are reliably positive for almost all populations sampled here, even those in which serial monogamy is practised. This suggests that males do indeed increase fitness through marriage to multiple women, even in cases in which these marriages are sequential. Sequential marriage can be considered a form of polygyny insofar as men typically replace divorced wives with younger women, allowing a subset of males in the population to increase their lifetime reproductive success relative to less wealthy males in the population, as has been shown in many of the populations sampled here and elsewhere, both directly and indirectly. The essential puzzle to be explained with our model, however, is not the extent to which effective polygyny is driven by concurrent marriage versus sequential remarriage,container raspberries but rather how effective polygyny can be attenuated by changes in the structuring of wealth inequality.

As in the Standard Cross-Cultural Sample, there is no overall relationship between wealth inequality as measured by the Gini coefficient and per cent age-adjusted female polygyny in our sample . However, analysed by subsistence category, this relationship varies. Foragers show little variation in wealth inequality, but high variation in polygyny. A possible concern related to the cross-cultural compatibility of our estimates is that our rival wealth proxies vary between populations and productions systems; in cross-cultural projects as wide-ranging as this one, however, there is rarely a single variable that can be compared directly across populations—instead, we have relied on ethnographic accounts to identify which sources of wealth are most relevant to production and reproduction in each society, and attempted to build a cross culturally comparable dataset by using the most locally relevant measures of wealth in each population .Following Oh et al., we consider a population of men with two types of fitness-relevant resources:non-rival wealth, denoted as g, and rival wealth, denoted as m. As a useful mnemonic, we can think of g as the value of a male’s genetic contribution to offspring production and survival, and m as the value of his material contributions, but the general definitions are considerably broader. Although we treat g and m as completely distinct stores of wealth in this mathematical model, we recognize that most empirical wealth variables will lie somewhere on a continuum of rivalness between non-rival resources, like genes, that can be provided to all offspring in equal measure, and rival resources, like land, which must be divided among offspring. For example, local ecological knowledge can be passed in equal measure to all offspring, but the time allocated to personal instruction may be rival.

We represent the total mating investment devoted to acquiring a wife by a cost equal to c units of the rival resource per wife; this term includes classic costs, such as bride price, in addition to all other costs associated with courtship and marriage. For an explanation of these and all other variables and functions used in this paper, see table 2.The parameters g and m are constrained to the unit interval reflecting the assumption—strongly confirmed in our empirical estimates—that the marginal fitness effect of additional wealth of either type, while positive, is either constant or diminishing as wealth increases. Note that rival and nonrival wealth are modelled as complementary inputs using a fitness function analogous to the Cobb–Douglas function widely used in economics. This assumption formalizes the idea that having high non-rival wealth with limited material wealth will not contribute as much to fitness as having farming skill in the presence of substantial amounts of such material resources. In other words, the multiplicative nature of the fitness function means that the marginal fitness effect of each kind of wealth is greater as the amount of the other kind of wealth increases. The parameter d is key to our proposed resolution of the polygyny paradox. It controls the extent of diminishing returns to increasing number of wives for reasons unrelated to the need to share a male’s rival wealth among wives; a value of one indicates no such sources of diminishing returns and an increasing extent of such diminishing returns is indicated by values of d falling farther below one. In the model, as d decreases the effective number of wives falls further below the empirically observed number n, indicating that female reproduction is constrained in some way by a male’s additional marriages for reasons other than rival wealth sharing.

In order to produce analytically tractable results, we simplify by assuming throughout that there are only two types of males, rich and poor, with rich males being a fraction u of the population. All rich are identical, as are all poor. The rich males are indexed by r and the poor by p.We now demonstrate two theoretical results with the potential to resolve the polygyny paradox. First, diminishing returns to additional wives arising from causes other than necessity to share a husband’s rival material wealth will reduce the number of wives acquired by each rich male. Second, because of this fact, a highly unequal wealth distribution with few extraordinarily rich men may produce little polygyny, while a less unequal wealth distribution with a larger fraction of rich men may produce a greater extent of polygyny. Two rich men, for example,draining pots can be expected to have more wives in total than one very rich man whose wealth equals their combined wealth. For this same reason, the Gini coefficient—see table 2 for a definition—is not a sufficient statistic for the analysis of the relationship between polygyny and wealth inequality. We take up each of these results, in turn, before assessing if our empirical estimates are consistent with this explanation.To address prediction P1, we present empirical estimates of m and d. These values are estimated using a multi-level regression model fit to our individual level data; methodological details are provided in the electronic supplementary material. In all but four of the populations in our sample, the estimated d coefficient is reliably less than 1. This result provides cross-cultural empirical support for the first of the two conditions needed to generate a transition to a greater degree of monogamy with increasing wealth inequality. Note two further results also shown in figure 5. First, our estimates for m are quite low, particularly across the agricultural economies. Second, our estimates of d 2 m are positive in almost all populations, including those that are concurrently polygynous and those that are serially monogamous. The consistently small values of m across all of our samples, even the monogamous ones, was unexpected. However, these low values reflect changes in male fitness per wife. Because of biological limits to the rate of reproduction in human females, significant increases to wealth are constrained to have less than proportional effects on fitness per wife. The effects observed here are more likely to reflect the ability of males with more than a threshold level of resources per wife to minimize offspring mortality, rather than to significantly enhance their own fertility. Though not discussed in detail here, our data suggest that male wealth impacts male fitness primarily by increasing the rate of wife acquisition rather than by increasing reproductive success per wife . Our second point addresses the possible concern that our estimates of d may be low, in part, because we use times married as our measure of polygyny. While it is true that men can accumulate a greater maximal number of marriage years through concurrent polygyny than serial monogamy, figure 5a demonstrates that the use of times married is an appropriate measure of polygyny for our purposes.

Across almost all populations, the elasticity of fitness with respect to times married, d 2 m, is positive and reliably non-zero. Because these estimates measure the population-specific effects of cumulative number of wives on reproductive success, they demonstrate that an increased number of marriages leads to increased reproductive success in both types of marriage systems—concurrently polygynous and serially monogamous.We have established that there exists a strong cross-cultural pattern of decreasing—but reliably non-zero—fitness returns to increasing number of wives for reasons beyond rival wealth sharing. We now turn our attention to testing if the transition to agriculture is associated with a decreasing fraction of wealthy males. In our theoretical model, we assume a discrete two-class wealth distribution, but empirical wealth data typically have continuous distributions. To deal with this issue, we consider two proxy measures for per cent rich in our empirical data: the minimum percentage of men that account for a fraction f of the total wealth and the frequency of men with more than c wealth, where c is the empirical midpoint in each population between the average wealth of males with one wife and the average wealth of males with two wives. More details about these metrics are included in the electronic supplementary material. Table 3 provides population-level posterior estimates of the completed wealth and completed polygyny measures, with the mean estimates by subsistence type shown in the bottom panel. To address prediction P2, we calculate empirical estimates of the fraction of rich men by production system . We find that agricultural populations have a significantly reduced frequency of wealthy individuals relative to horticultural populations. All four panels show reliable differences in mean per cent rich between the horticultural and agricultural subsistence modes. This lesser fraction of wealthy individuals suggests a decreased number of men both able and willing to take second wives. This in turn leads to reduced levels of per cent female polygyny in contexts where large wealth differentials are not able to underwrite large differentials in wives due to the existence of diminishing fitness returns to such additional wives. A limitation of this last result is that it is based on data from only four agricultural populations, three of them concentrated in a restricted region and time period . Moreover, a more informative dataset would come not from agricultural populations in the time period between the 1700s and 2000s, but rather from the agricultural populations in which monogamy actually began to emerge denovo. In our main analysis, we use estimates derived from the individual-level records available in the populations shown in table 1; in the electronic supplementary material, we present comparable analyses that include 14 additional wealth distributions from historical agricultural populations. The results of this supplementary analysis are consistent with our arguments here—and in fact show stronger and more reliable effects in the direction predicted by P2. These supplementary data, however, are based on sometimes contested reconstructions of the historical wealth distributions pieced together by archaeologists and economic historians;they must be appreciated within the constraints associated with such forms of data.Using individual-level data from 29 populations, we show evidence of a general cross-cultural pattern of decreasing marginal fitness returns to increasing number of marriages. Further, using these same 29 datasets , we demonstrate the existence of an increasingly skewed distribution of material wealth in class-based agricultural societies . Both of these empirical findings are consistent with our model-based explanation for the decline of polygyny in societies engaged in agricultural production.We use cross-cultural data and a new mutual mate choice model to propose a resolution to the polygyny paradox. Following Oh et al., we extend the standard polygyny threshold model to a mutual mate choice model that accounts for both female supply to, and male demand for, polygynous matchings, in the light of the importance of, and inequality in, rival and non-rival forms of wealth.

Dynamic, on-line route planning has recently received attention in the agricultural robotics literature for large-scale harvesting operations because of its economic importance and the availability of auto-guided harvesters and unloading trucks. Reported approaches compute a nominal routing plan for the harvesters assuming some initial yield map, and then they route the support units based on the computed points where harvesters fill up their tanks . The plan is adjusted during operations based on updated predictions of when and where harvester tanks will be full. A recent application that falls in this category is robot-aided harvesting of manually harvested fruits , where a team of robotic carts transports the harvested crops from pickers to unloading stations, so that pickers spend less time walking. Overall, the increasing deployment of commercially available auto-guided harvesters and unloading trucks, and the emerging paradigm of replacing large, heavy machines with teams of smaller agricultural autonomous vehicles drive the need for practical on-line route planning software.Primary units and support autonomous vehicles form a ‘closed-loop’ system: the delays introduced by the support vehicles affect the primary units’ temporal and spatial distributions of future service requests. Reactive policies are not efficient enough,growing blueberries in a pot because support trucks/robots must traverse large distances to reach the primary units in the field, thus introducing large waiting times.

The agricultural vehicle routing problem lies under the broad category of Stochastic Dynamic VRP. The incorporation of predictions about future service requests has been shown to improve scheduling for SDVRP. However, most SDVRP applications are characterized by requests that are stochastic and dynamic in time, but fixed and known in terms of location . In contrast, service requests from primary units in agriculture are stochastic and dynamic, both temporally and spatially . Also, the real-time and dynamic nature of agricultural operations means that very few established requests are available to the planner/scheduler, which has to rely much more on predicted requests. In addition, the optimization objective also varies depending on the situation. For example, it can be minimizing waiting time, maximizing served requests and so on, while VRP mainly focuses on minimizing travel distance. Therefore, existing SDVRP predictive scheduling approaches are not well suited for agriculture and more research is needed to incorporate uncertainty in on-line route planning for teams of cooperating autonomous agricultural machines.Therefore particular focus has been on computing paths and trajectories that are optimal in some economic or agronomic sense. Also, in most cases vehicles are non-holonomic. The general problem of moving a vehicle from one point/pose to another lies in the area of general motion planning and is covered adequately in the robotics literature . The focus of this section is on motion planning inside field or orchard blocks. When several machines operate independently of each other in the field they do not share resources, other than the physical area they work in. Furthermore, independent robots will typically operate in different field or orchard rows and their paths may only intersect in headland areas, which are used for maneuvering from one row to the next.

Therefore, motion planning is restricted to headland turning and involves: a) planning of independent geometrical paths for turning, and b) computing appropriate velocity profiles for these paths so that collision avoidance is achieved, when two or more robot paths intersect. Problem is a coordinated trajectory planning problem and has been addressed in the robotics literature . In headlands, optimal motion planning is of particular interest, as turning maneuvers are non-productive and require time and fuel. Auto-guided agricultural vehicles must be able to perform two basic navigation tasks: follow a row, and maneuver to enter another row. The latter requires detection of the end of the current row and the beginning of the next row. The route planning layer specifies the sequence of row traversal and the motion planning layer computes the nominal paths. During row following, precision crop cultivation requires precise and repeatable control of the vehicle’s pose with respect to the crop. Inside rows, agricultural vehicles travel at various ground speeds, depending on the task. For example, self-propelled orchard harvesting platforms move as slow as 1-2 cm/s; tractors performing tillage operations with their implement attached and their power take off engaged may travel at 1 Km/h up to 5 Km/h. Sprayers may travel at speeds ranging from 8 Km/h up to 25 Km/h. Vehicle working speeds in orchards are typically less than 10 Km/h. The above speeds are for straight or slightly curved paths; during turning maneuvers much slower ground speeds are used. Wheel slippage is common during travel, especially in uneven or muddy terrain. Also, agricultural vehicles will often carry a trailer or pull an implement, which can introduce significant disturbance forces. There are two basic auto-guidance modes: absolute and crop-relative. Absolute auto-guidance relies exclusively on absolute robot localization, i.e., real-time access to the geographical coordinates of the vehicle’s location, its absolute roll, pitch and yaw/heading, and time derivatives of them.

These components of the vehicle’s state are estimated based on GNSS and Inertial Navigation System . Tractor GPS based absolute auto-guidance was first reported in 1996 , after Carrier Phase Differential GPS technology became available. Since then, auto-guidance for farming using Global Navigation Satellite Systems has matured into commercial technology that can guide tractors – and their large drawn implements – with centimeter-level accuracy, on 3D terrain, when Real Time Kinematic corrections are used. Absolute guidance can be used for precision operations when there is an accurate georeferenced map of the field and crop rows that is valid during operations, and the vehicle knows its exact position and heading in this map, in real-time. Essentially, establishing accurate vehicle positioning with respect to the crop is achieved by achieving absolute machine positioning on the map. The first step towards this approach is to use RTK GPS guided machines to establish the crop rows – and their map , transplanting . After crop establishment, as long as crop growth does not interfere with driving, vehicles can use the established map to repeatedly drive on the furrows between rows using RTK GPS . Accurate, robust and repeatable path tracking control is needed for precision guidance. The topic has received significant attention in the literature with emphasis given on slip compensation and control of tractor-trailer systems. Approaches reported in the literature include pure-pursuit , side-slip estimation and compensation with model based Liapunov control , back stepping predictive control , fuzzy neural control , sliding mode control , and others. Model-based approaches have also been proposed, such as nonlinear model predictive control , and robust nonlinear model predictive control . Absolute auto-guidance is an established commercially available technology that has acted as enabler for many precision agriculture technologies for row crops, such as variable rate application of seeds and chemicals. It has also led to recent advances in field automation,blueberry sunlight requirement including the development of remotely supervised autonomous tractors without cabin and master-slave operation of grain carts with combines for autonomous harvesting systems . Absolute auto-guidance is not practical in row crops or orchards where one or more of the following are true: a) no accurate crop rows map is available to be used for guidance because crop establishment was performed with machines without RTK GPS; b) such a map exists but changes in the environment or crop geometries may render pre-planned paths non collision-free ; c) GNSS is inaccurate, unreliable or unavailable . In these operations plants grow in distinct rows and the wheels of the autonomous vehicles must drive only inside the space between rows. Examples include open field row crops ; orchards with trees/vines/shrubs and their support structures; greenhouses and indoor farms. Crop-relative auto-guidance is necessary in the situations described above. Researchers have used various sensors, such as onboard cameras and laser scanners to extract features from the crops themselves, and use them to localize the robot relative to the crop lines or trees rows in order to auto-steer. Crop-relative guidance in open fields and orchards is still more of a research endeavor rather than mature, commercial technology. Most of the work so far has focused on row detection and following, and in particular on the estimation of the robot’s offset and heading relative to middle line of the row between the crop lines. All approaches exploit the fact that multiple parallel crop lines are spaced at known and relatively fixed distances from each other. Although the problem of finding such crop rows in images may seem straightforward, real-world conditions introduce complications and challenges that will be discussed next.

When the crop is visually or spectrally different from the material inside furrows , discrimination between soil and crop is easy . However, it can be very challenging in the presence of intra-row weeds or when there are cover crops or intercropping in the furrows , as the visual appearance of the intra-row plants can have similar visual and spectral characteristics to the crops in the rows that need to be detected. Other challenges include row detection of different plant types at various crop growth stages, variability in illumination conditions during daytime or nighttime operation, and environmental conditions that affect sensing. Robustness and accuracy are very important features for such algorithms, as erroneous line calculations can cause the robot to drive over crops and cause economic damage.Researchers have used monocular cameras in the visible  or near infrared spectrum , or multiple spectra to segment crop rows from soil based on various color transformations and greenness indices that aimed at increasing segmentation robustness against variations in luminance due to lighting conditions. Recently, U-Nets , a version of Fully Convolutional Networks were used to segment straw rows in images in real-time . Other approaches do not rely on segmentation but rather exploit the a priori knowledge of the row spacing, either in the spatial frequency domain – using band pass filters to extract all rows at once – or in the image domain . An extension of this approach models the crop as a planar parallel texture. It does not identify crop rows per se, but computes the offset and heading of the robot with respect to the crop lines . Once candidate crop row pixels have been identified various methods have been used to fit lines through them. Linear regression has been used, where the pixels participating are restricted to a window around the crop rows . Single line Hough transform has also been used per independent frame , or in combination with recursive filtering of successive frames . In an effort to increase robustness, a pattern Hough transform was introduced that utilizes data from the entire image and computes all lines at once. Researchers have also used stereo vision for navigation. In an elevation map was generated and the maximum value of the cross-correlation of its profile with a cosine function was used to identify the target navigation point for the vehicle.In depth from stereo was used to project image optical flow to vehicle motion in ground coordinates and calculate offset and heading using visual optical flow.Most reported work was based on monocular cameras, with limited use of stereo vision and 2D/3D lidars. One reason is that in early growth stages the crops can be small in surface and short in height; hence, height information is not always reliable. Given the increasing availability of real-time, low-cost 3D cameras, extensions of some of the above methods to combine visual and range data are conceivable and could improve robustness and performance in some situations. Also, given the diversity of crops, cropping systems and environments, it is possible that crop or application targeted algorithms can be tuned to perform better than ‘generic’ ones and selection of appropriate algorithm is done based on user input about the current operation. The generation of publicly available datasets with accompanying ground truth for crop lines would also help evaluate and compare approaches.Orchards rows are made of trees, vines or shrubs. If these plants are short and the auto-guided robot is tall enough to straddle them, the view of the sensing system will include several rows and the guidance problem will be very similar to crop-row relative guidance. When the plants are tall or the robot is small and cannot straddle the row, the view of the sensing system is limited to two tree rows when the robot travels inside an alley, or one row if it is traveling along an edge of the orchard.

In addition, hazelnut trees on C. colurna root stocks are frequently more variable in size and yield than self-rooted trees of C. avellana. In a trial using ‘Barcelona’ as a scion cultivar, the graft unions were overgrown and nut yields declined with age, at ~20–25 years. Due to these disadvantages, the Faculty of Agriculture, at Novi Sad in Serbia, has focused on identifying non-suckering selections of C. avellana. Currently, seeds of selected C. colurna are used as hazelnut root stock as it has been demonstrated to be long-living, resistant to frost and drought, has wide adaptability to soil conditions, and the trees are more vigorous and productive than self-rooted trees. Hazelnut root stock breeding started in Oregon in 1968. In nursery rows, open pollinated seedlings of C. colurna seedlings whose traits were intermediate between C. colurna and C. avellana were selected and propagated. During twenty years, approximately 150 potential root stocks were selected from 20,000 seedlings investigated.Both root stocks are thought to be interspecific hybrids because their nut and husk characteristics differ from those of the maternal parent. In 2000, a root stock trial was established at the IRTA-Mas Bové Research Center ,blueberries in pots with Spanish cultivar ‘Negret’ grafted onto four different root stocks, ‘Dundee’, ‘Newberg’, and two open pollinated C. colurna seedlings, compared to own-rooted ‘Negret’ as the control.

The results showed that ‘Dundee’ and ‘Newberg’ root stocks improved agronomic performance, solving the problem of suckering, increasing productivity and vigor, and producing increased yield at lower cost. However, the search for additional non-suckering root stocks necessary for commercial hazelnut orchards remains topical and is continuing. Root stocks can be vegetatively propagated by micropropagation, layering, or cuttings. The rooting ability of root stocks and the most effective propagation methods vary by species and genotype. Among walnut root stocks, Persian walnut is more difficult to root than black walnut × Persian hybrids. Japanese × European chestnut hybrids are more easily propagated by cuttings or layering than European chestnuts. Many efforts have been made to propagate walnuts by layering, cuttings, and micropropagation. In vitro propagation of walnuts obtained seems quite difficult. Generally, the effects of genotypes, but also the culture medium in vitro on proliferation, rooting, and survival rates are significant. Along with genotypes, nutritive support in vitro has an important influence on all stages of micropropagation. In addition to the well-known Murashige and Skoog culture medium, the Driver and Kuniyuki medium is also widely used for tissue culture of walnuts. However, depending on nutritive improvements of the medium, large variations of the results can be obtained regarding the success of in vitro culture . Vahdati et al. reported in-vitro rooting of Persian walnut cultivars ‘Sunland’ , ‘Chandler’ , and ‘Vina’ . Vahdati and Khalighi and Vahdati et al. evaluated stool layering of Persian walnut and found the greatest root number and root length was obtained using 5000 and 10,000 ppm IBA + IAA + NAA, respectively. Vahdati et al. obtained up to 81% and 82% rooting of Paradox walnut semi-hardwood and hardwood cuttings respectively, using 8000 ppm of IBA. Dong et al. reported a range of 60.5 to 87.5% rooting in a study of six cultivars.

Currently, the nursery pathogen problems have demonstrated it is better to produce plants in inert medium, and micropropagate the root stocks and graft the material in the nursery. Vahdati et al.found rooting success of low-vigor walnuts was better than more vigorous ones in response to stool layering. Peixe et al. achieved ex-vitro rooting rates exceeding 80% for microcuttings of ‘Vlach’ hybrid walnut. RolABC genes , derived from the bacterium A. rhizogenes, were inserted into somatic embryos of Px1 to increase the rooting potential. In a field trial, the rolABC genes produced shorter internodes and a more fibrous root system. Water and nutrient uptake are one direct effect of root stock on nut tree yield. These are regulated by complex interactions between the scion and root stock. Hormones, macromolecules, and miRNAs act as long-distance signaling molecules that regulate nutrient uptake. Water and nutrient uptake are enhanced by root stock vigor. In addition, the rate of vascular bundle development in a graft union determines the transfer potential of water and nutrient to the scion. Insufficient vascular bundle connection in a graft union leads to decreased water flow and subsequently altered nutrient translocation and hormonal signaling. Vertical and lateral root development plays an important role in water and nutrient uptake. Root stocks with a vigorous root system, i.e., long roots with many lateral branches and root hairs, are able to exploit water and nutrients from different soil depths and textures . Water uptake by roots is both parallel symplastic and apoplastic pathways. Root system hydraulic conductivity defines the root’s ability to conduct water across a water-potential gradient between the root surface and the stem xylem. Root stock effects on the canopy nutrient content are influenced not only by the roots physical characteristics but also depending on the chemical composition of the soil and environmental conditions. Pistachio root stocks differ in efficiency of macro- and micronutrient uptake.

The P. integerrima root stock is less efficient in zinc and copper uptake than P. terebinthus or P. atlantica. Trees on P. integerrima root stocks have much higher sodium , chloride and boron uptake than the reciprocal hybrids of the latter root stock species. This tendency to absorb and translocate Na and Cl ions to the leaves can be harmful to scions on P. integerrima in saline environments. The PGII root stock is more efficient in Zn and Cu uptake than P. terebinthus; P. atlantica is intermediate; UCB1 and P. integerrima are the least efficient. Boron uptake by PGII is somewhat less efficient than P. integerrima root stocks and slightly more efficient than UCB1. Boron uptake by UCB1 is similar to P. atlantica and P. terebinthus. PGII is less efficient than P. integerrima root stocks and a bit more efficient than UCB1. The ‘Kerman’ scion onto different pistachio root stocks demonstrated that leaves of trees on P. terebinthus often have the highest nutrient levels. P. terebinthus was more efficient than other root stocks in absorbing Cu, Zn, and other micronutrients that are often deficient in pistachio orchards. PGII and P. atlantica root stocks were superior to UCB1 and P. integerrima in absorbing Cu. A study of ‘Bianca’ scion budded onto various in vitro propagated clonal root stocks,square plant pot revealed that P. terebinthus was the most efficient at K uptake, but less efficient in uptake of Mg. The P. atlantica and P. integerrima clones seemed to be deficient in K uptake and the most efficient in Mg uptake. A four-year study of two pistachio cultivars budded on six P. vera seedling root stocks demonstrated that, K, P, and Fe absorption differed significantly among these root stocks. Scions on ‘Badami’ and ‘Daneshmandi’ seedlings had the maximum and minimum K absorption, respectively. ‘Akbari’ budded on ‘Badami’ was the most efficient in uptake of K and Zn. ‘Kalle-Ghouchi’ and ‘Daneshmandi’ had the maximum and minimum Fe content, respectively. The minimum K and Zn uptake occurred in ‘Akbari’ budded on ‘Daneshmandi’. ‘Barg-Seyah’ budded onto ‘Kalle-Ghouchi’ gave the maximum Fe and Cu uptake. These results indicate that selecting the appropriate root stock and scion for a particular environment is an important decision that can affect orchard growth and yield. Tavallali and Rahemi reported that leaves of pistachio cultivars grafted on ‘Beneh’ root stock had higher K, P, and Zn uptake than trees on ‘Badami’ and ‘Sarakhs’ root stocks. Leaves of pistachios on ‘Badami’ and ‘Sarakhs’ had the highest Ca and Cu content, respectively. Kernels of cultivars grafted on ‘Sarakhs’ root stock had greater K, P, Mg, Cu, Fe, and Zn content than cultivars on other root stocks. Trees grafted on P. atlantica seedling root stocks were less likely to show B, Ca, or Zn defificiency. These studies identified the effect of pistachio root stocks on nutrient uptake and yield but our knowledge on the effect on nutrient uptake of different cultivars grafted on the same root stock is limited. Surucu et al.grafted 14 pistachio cultivars of different origins on a single source of P. khinjuk seedling root stocks and evaluated nutrient uptake and yield. Scion cultivar ‘Haciserifi’ had the greatest N, P, and K accumulation, while ‘Mumtaz’ had the greatest uptake of Ca, Mg, and Cu. ‘Vahidi’ accumulated the most Fe and Zn, and ‘Sel-150 accumulated the most Mn. ‘Sel-20 , ‘Sel-50 , and ‘Siirt’ scions had the highest percentage nut split and ‘Mumtaz’ had the highest yield.

Knipfer et al. reported that the root hydraulic conductance of ‘RX10 and ‘Vlach’ walnut root stocks was more than 50% greater than ‘VX2110 and possibly, one reason for the tolerance of these two root stocks to drought stress. Under drought stress, ‘Vlach’ and ‘RX10 decreased root hydraulic conductivity to maintain root biomass. Walnut roots selectively absorb ions when they are under stress. A study of the response of own-rooted walnut varieties to salt stress showed that the tolerant varieties accumulate and translocate more K and Ca in shoots than the less tolerant varieties. In other words, the roots of salt-tolerant walnuts not only absorb more K and Ca, but also translocate more to the leaves. A comparison of nutrient uptake between two walnut root stocks, J. hindsii and Paradox, showed that N, P, Ca, Mg, and Mn uptake were significantly higher with Paradox root stock. In almonds, the impact of root stock choice on concentrations of lime, alkali, B, Zn, and K has been well studied. Jiménez et al. reported that high levels of sucrose, organic acids, amino acids, and PEP carboxylase activity in the roots of Prunus root stocks lead to root growth and iron uptake under iron deficient conditions. Trees on almond or almond × peach hybrids show reduced levels of chlorosis from iron deficiency in high-lime soils. Somewhat less tolerant are the Myrobalan root stocks, which will often develop some chlorotic leaves at the shoot tips by late summer. The three-way, and similarly complex, hybrids tend to show more intermediate tolerance to calcareous soils. In general, almond trees on peach perform poorly on calcareous soils, whereas trees on almond root stocks typically perform better. All Prunus root stocks are generally sensitive to alkaline soils or water containing an excess of alkali salt. Trees on almond root stocks appear to be the most tolerant, followed by Myrobalan plum, and peach, with little difference among the latter two. Some peach × almond hybrids have also demonstrated greater tolerance to alkali than peach or Myrobalan. The Prunus scion also appears to have considerable influence on sensitivity to alkaline soils, but the extent of this influence has not been well characterized. Marianna plum and peach show greater tolerance to excess boron than almond, which, in turn, is more tolerant than Myrobalan root stocks. For this reason, almond root stocks are recommended for locations where excess B is a problem. If boron is low, more vigorous root stocks and Marianna plum are generally preferred. Almond and peach root stocks are more likely to experience Zn deficiency than trees on Marianna. Almond trees on almond or Myrobalan root stocks are more susceptible to K deficiency than peach, with tree death possible if not treated. Reid performed a leaf analysis of two pecan scions, ‘Posey’ and ‘Pawnee’, grown on 10 root stocks: ‘Chickasaw’, ‘Colby’, ‘Dooley’, ‘Giles’, ‘Greenriver’, ‘Major’, ‘Mohawk’, ‘Peruque’, ‘Posey’, and ‘Shoshoni’. He concluded that root stock influenced K and Zn concentration. The greatest K accumulation was seen in trees on ‘Posey’ seedlings while scions on ‘Greenriver’ seedlings showed the least. Trees on ‘Chickasaw’ seedling root stocks contained the highest amount of Zn while those on ‘Major’ seedlings had the least. A study of hazelnut root stocks showed that ‘Dundee’ and ‘Newberg’ are more resistant to iron chlorosis and maintain leaves on the tree for a longer period during the season, an important aspect to be considered, as these trees can then absorb soil nutrients up for a longer period. In fruit trees, there is a lag between planting and fruiting, leading to a delay in the profitability of commercial orchards. Root stocks are not only able to induce precocity, but also increase the quality of flowers and ability to set fruits. Previous results on pistachio showed that flowering time of pistachio can be delayed when ‘Badami-e-Zarand’ is used as root stock and ‘Akbari’ as interstock. In contrast, ‘Badami-e-Zarand’ and ‘Fandoghi’ as root stock without interstock had no significant effect on flowering time.

Temperature, humidity, ethylene levels, and the storage oxygen-to-carbon dioxide ratio must be controlled to slow down maturation and senescence in order to maintain produce shelf-life and quality. Low temperatures are used to reduce respiration, thereby extending shelf-life, but also have the added benefit of suppressing water loss, shrinkage, and fungal growth, which can occur due to physical injury and physiological disorders. Modifying the atmosphere to change the carbon dioxide-to-oxygen ratio and relative humidity using modified atmosphere packaging or large-scale storage of produce in controlled atmosphere rooms can extend the post harvest life of commodities . Ethylene biosynthesis and emission underpin post harvest quality and shelf-life in climacteric fruit and vegetables. Ethylene accelerates ripening, but also senescence; therefore, ethylene must be managed to optimize shelf-life. This is underscored by the number of ethylene inhibitors, absorbers, and blockers on the market .The goal of post harvest management is therefore to control this progression to senescence, i.e., to pause the ripening process for shipping and storage, and then to restart it with a minimal loss of quality. However, the processes that control the ripening-to-senescence transition dictate quality, creating a dilemma, whereby altering ripening biology via refrigeration, chemicals, or other means to lengthen shelf-life,blueberries in containers often unavoidably disrupts ripening outcomes and reduces quality.

This leads to consumer rejection and post harvest waste. The alternative—to maximize consumer preference by harvesting produce close to peak maturity stage, and with no chemical or physical treatment, will invariably increase post harvest losses due to the shortened shelf-life, and increased susceptibility to bruising and pathogenic infection .There is great excitement at the innovation gene editing and the associated technologies potentially bring for improving crop quality, especially for species and traits that have been relatively understudied, such as post harvest traits of horticultural crops. Manipulation of plant genomes in a precise manner has been achieved at a spellbinding pace since the era of genome editing. The current gene-editing tool of choice is CRISPR–Cas9. The researcher is able to generate mutations in narrowly defined regions of the genome, and it has been successfully applied to induce valuable traits in many crop species. Further, CRISPR can bypass other burdens like sterility, self-incompatibility, high heterozygosity, low frequency of recovering desired alleles and traits and long life cycles, which extend or halt entirely conventional breeding efforts. CRISPR is a prokaryotic system that protects organisms from viral infection. This naturally occurring mechanism in bacteria has been co-opted by scientists to remove unwanted nucleotides or to insert new or altered ones to promote traits seen as desirable in an organism of interest. For CRISPR editing, a synthetic guide RNA is designed to an identified protospacer adjacent motif in the sequence of interest, and this, along with the Cas protein sequence, is inserted into a cell where they are processed using the cell’s gene expression apparatus.

The Cas protein synthesized in the plant produces a double stranded break at the bases identified by the gRNA. Repair of the DSB in DNA is usually not faithful to the original sequence, and thus, non-synonymous mutations may be introduced into the genome. The precise changes in nucleotide sequences are difficult to predict, but indels of varying sizes and single nucleotide polymorphisms are most common, providing diverse genetic variants. DSB repairs occur naturally in almost all plant tissues, so this is not an inherently foreign process. Although genomic mutations generated by CRISPR mediated random repair mechanisms are easily achieved, the ability to specifically express the Cas protein in a controlled spatial-temporal manner, and in conjunction with other enzymes, is often desirable for basic and applied plant research. Precise site-directed editing can be used for single-base substitution of a gene of interest, which has been achieved in cereals, as well as horticultural crops such as tomato and potato. In addition, tissue-specific knockouts using a CRISPR technique, called CRISPRTSKO, can generate somatic mutations in cells, tissues, and organs by using specific promoters. Similarly, another gene-editing system uses an inducible chimeric transcription factor , to control the expression of Cas protein in planta. Apart from knock-out/in of gene coding regions, transcriptional modulation of gene expression can be achieved by CRISPR targeting of gene regulatory elements. New alleles generated by CRISPR/Cas in promoters and enhancers where transcription factors bind to direct gene expression, can lead to fine-tuned expression. Similarly, variants in upstream open reading frame sequences could enhance post-transcriptional modulation of gene expression, influencing phenotype. The expression of a gene may also be varied by changing its DNA methylation status. In tomato, orange, and bell pepper, DNA methylation regulates ripening by controlling ripening-related TFs or genes.

Binding a methylation modifying protein to a CRISPR complex with a deactivated Cas9 may be a feasible approach to edit regions targeted for de/methylation in ripening-related genes, thus controlling shelf-life. CRISPR-Cas also enables modulation of traits in species that are difficult to obtain through traditional breeding. Approximately 70% of angiosperms are polyploid, which increases the effort needed for introducing new alleles by crossing and selection. Transmission of Cas activity in the progeny of CRISPR-expressing lines holds promise for transgenerational gene-editing in polyploid plants. This method was shown to introduce newly mutated alleles, not only in F1 but also in F2 and F3 plants. De novo domestication, a new idea in crop improvement, has been demonstrated in multiple species of the wild Solanum genus by CRISPR targeting. Novel alleles of selected “domestication genes” are generated in wild species, land races, or non-commercial genotypes to speed-up their transformation to elite varieties suitable for cultivation and post harvest practices of modern agriculture. In conclusion, various CRISPR techniques and approaches can be used to introduce nuanced changes in the expression of single or multiple genes, however, it also has real value as a tool to dissect the network of biological pathways responsible for ripening, senescence, and quality. It is expected to help identify hitherto unknown genes, that when altered, can promote favorable post harvest phenotypes. These desirable phenotypes are discussed in “Produce post harvest attributes that would minimize PLW” section.Consumers have shown that fruit and vegetables with desirable appearance, texture, taste, and flavors will have higher salability. The criteria for a favorable appearance include produce of the right color and color uniformity, correct shape and dimensions,planting blueberries in pots and often a glossy surface area free from defects. Identifying and manipulating the genes determining these pathways could improve quality. Consumers also have specific notions of what “unacceptable” produce is, and this has consequences for the generation of post harvest waste. This may vary culturally and according to socio-economic status, but general trends are identifiable. Produce with characteristics reminiscent of rotten, infested, or unripe material will be rejected. This is widely accepted as an evolutionary strategy to avoid poisoning or illness from contaminated food, as well as a learned response based on a previous negative experience. Therefore, lesions or aromas due to age or bruising are associated with “bad” fruit and vegetables and will be rejected not only as “low quality” but as potentially dangerous, despite the produce being largelyintact and actually safe. While quality of flavor is widely believed to be a strong predictor of repeat purchase, visible appearance has a strong role in initial selection or rejection at the point of purchase, and later discarding in the home. These negative traits all interact with the consumer priorities mentioned above and contribute to post harvest waste.Although our knowledge of basic fruit and produce biology is incomplete, there has been extensive work that points to the action of individual genes which, when altered in expression, may deliver useful phenotypes. Manipulating these biological processes by gene editing is a promising new avenue for reducing PLW. Many traits, however, are determined by networks of genes, and although distinct, some networks overlap so that changes in one may have unintended consequences in another. A major challenge is to understand the complicated regulation of these pathways in order to fine-tune them in a beneficial way. Gene editing has the potential to clarify the role of individual constituents in conjunction with the production of novel varieties.As mentioned in “The challenge of the post harvest supply web” section, ethylene is a master regulator of ripening; in climacteric fruit, ethylene production must be managed to optimize shelf-life , but genetic solutions may be more effective.

In climacteric fruit, ethylene synthesis, regulation, and perception lead to the transcription of ripening-regulated genes that determine quality attributes desired by consumers. When ACO and ACS expression is genetically suppressed or silenced in a range of species, e.g., petunia, tomato, melon, papaya, and kiwifruit, ethylene production is decreased and shelf-life is extended due to slowed ripening processes. In tomato, the regulation of ethylene biosynthesis is mediated by a complex network centered around the master regulatory proteins: CNR, RIN, and NOR, which are required for normal ripening. The recent use of CRISPR to induce targeted deletions or substitutions in CNR and NOR, and in other transcription factors , AP2a, FUL1, and FUL2 revealed multiple and redundant levels of regulation in the ripening pathway. Using CRISPR to create fruit varying sequentially in one or more of these transcription factors may improve our understanding of the molecular regulation of ethylene response in horticultural crops. This knowledge would allow us to control ethylene production so that ripening proceeds at the rate and with the timing that is optimal for supply chain dynamics while maintaining quality. This would directly mitigate PLW.Global demand for fresh-cut ornamentals has increased in the past years, with an estimated value of $16B in 2015. The top producers, the Netherlands, Ecuador, Columbia, and Kenya, export floral products long distances, primarily to Europe, North America, and East Asia. However, ornamental crops are highly perishable and up to 50% of the farm value may be lost along the cold-chain, and each extra day in transit leads to a 15% loss of value. Further, after consumer purchase, ornamental shelf-life, i.e., vaselife, is typically only 10–12 days, so rapid transport along a cold-chain is essential. Ethylene has a critical role in accelerating flower senescence in some species, and targeting components of the ethylene signal transduction pathway has been successful in extending vase-life in carnation and petunia. Gene editing was also used to mutate ACO1 in petunia thereby increasing flower longevity. In species that are not ethylene-responsive, vaselife could also be extended by inhibiting general senescence proteins.The triterpenoids and waxes coating the harvested parts of horticultural crops may have a bigger influence on quality and shelf-life than previously recognized. The plant cuticle is the first layer of defense against water loss and pathogen infestation. The cuticle is also responsible for multiple traits involved in fruit quality and shelf-life, such as surface brightness, the characteristic “bloom” of grapes, blueberries and plums, and potentially modulating texture changes. Fruit cuticle composition actively changes depending on the environment and organ developmental stage, which affects its protective function during fleshy fruit ripening. The interaction between the bio-mechanical properties of the fruit cuticle and cell wall polysaccharides affects the development of surface cracks in cherries, apples, and tomato. These aesthetically undesirable traits for consumers can also reduce produce shelf-life. Identifying genes key to cuticle compound biosynthesis could improve fruit response to environmental stresses during post harvest storage and reduce pathogen susceptibility.The breakdown of the cell wall during fruit ripening is a crucial process in the development of fruit sensorial quality. Softening the fruit is essential for increasing its appeal to animals and humans for consumption, and thus seed dispersal. Ripening and senescence, together with fungal attack, accelerate the rate of CW degradation, leading to rotting. Rotting and ripening are discussed separately, even though they overlap biologically in relation to CW softening and fruit shelf-life. The modern, worldwide food supply chain often necessitates that the breakdown of the cell walls, either by ripening, senescent processes or by fungal rot, be halted or slowed. CW softening processes are catalyzed by multiple enzymes that respond to developmental and environmental cues and occur over a variety of timelines, depending on the organism and tissue in question. CW degradation is orchestrated by polygalacturonase , pectin methylesterase , pectate lyase , and β-galactosidase. PG, PME, PL, and β-Gal vary in their biotechnological potential to control firmness/fruit softening .