Horticulture

Paper sprayed with Tangle Trap sticky coating was placed a) at the base of the plants with a ring of sticky tape around the base of the stem and partially on the stem of the plant to capture any insects crawling down, and b) extending from the base of the plant horizontally outward above the pot surface to ensure complete coverage of the area covered by the plant canopy . This experiment was replicated on a single potted plant over time on 7 dates . Data were analyzed using Fisher’s exact test using SAS 9.2 . At our planned field trial site that would later be used in the B. bassiana trial, pupation emergence cages were used to sample insects moving off foliage towards pupation sites and later emerging out of the soil after pupation. Cages were made from Schedule 40 white PVC pipe with a diameter of 10.2 cm with cages cut to a height of 5.1 cm. The cage was then topped with a double-sided sticky card cut to fit,plastic flower buckets wholesale which was fixed into place with two elastic bands. Four lines of four cages were pushed into the soil to a depth of approximately 1 cm immediately adjacent to each other at the base of a blueberry plant and oriented in a cardinal plane to determine which direction showed the most thrips activity.

The four adjacent cages in a particular plane were used to assess thrips movement in the understory of the blueberry plant in each directional. The study was replicated on 5 plants on a single date and conducted just prior to the commencement of the field trial. Data were analyzed with a nested ANOVA using SAS 9.2. In a greenhouse trial, Mycotrol O ® was applied directly to the soil surface as raw spores and compared to the same product colonized onto millet seed, also using soil application. Millet seed colonization used the Stanghellini and El-Hamalawi method as described below. The colonized millet seed, when allowed to imbibe water and incubate in the laboratory, can support 1.0 x 106 conidia/seed . Based on Stanghellini et al. with modification, we held the GHA colonized millet seed in containers such that the seed mat was at a depth of no greater than 2.54 cm. The seeds were wet with the consistency of very thin slurry and were gently stirred three times per day for four days to ensure they imbibed water properly so that mycelial growth and sporulation would occur. Sporulation was confirmed by slide mounting random sections of mycelia and checking for condia formation under the microscope.

Once spores were initially observed, the seed was held an additional three days so that sporulation could continue before use of the colonized seed in the field study. Mycotrol O® was applied in the maximum recommended field rate for high thrips levels of 2.84 L of material in 378.5 L of water.The colonized millet seed was tested in the greenhouse to determine if late second instar citrus thrips would become infected if they crawled over or through the seed when it was placed at the base of a laurel sumac seedling. A single small laurel sumac seedling, about ~10 cm tall, was placed into each of ten, 9.5 x 9.5 x 18 cm styrene cages with 6 cm diam air holes on all four sides that were covered with ultra fine mesh screening . Small holes were made in the bottom of the container and covered with pebbles to allow for drainage, then soil was added to a depth of 7.62 cm and the top of the container was covered with a removable lid. The base of each plant was completely surrounded by either B. bassiana colonized millet seed or with uncolonized seed . A minimum of 20 late second instar thrips were released onto the leaves of each plant, and were left until enough time had passed for the thrips to molt to the propupal stage.

The seedling was then cut at the soil line and examined for pupating thrips; the removable lid of the cage was sprayed with Tangle Trap sticky coating to collect any emerging adults after 5 days so infection could be measured. The study was replicated on 5 dates . Data were analyzed using 1-way ANOVA with time as a factor and means were separated using Tukey’s Least Significant Difference test using SAS 9.2. To determine the optimum number of colonized millet seeds needed for close to 100% infection when thrips were seeking pupal refuges off the plant, varying amounts of colonized seed were evaluated in a greenhouse trial based on the size of the seed once it had imbibed water and sporulation had occurred. After water inhibition, nine seeds completely filled one square cm of soil surface. There was a 0.5 cm buffer area around all sides of the cage, which was kept clear of seed to provide a 9 x 9 cm grid of seed on the soil surface below the plant. All but two leaves were plucked from the seedling. Small holes weremade in the bottom of the container, which was covered with pebbles to allow for drainage. The 9 x 9 cm2 grid was created from wire screen and differing amounts of sporulating seed or seed alone were placed on the light imprint made from the wire screen on the soil surface. Two replicate seedlings per treatment were set up per date in a complete block design . Plants were watered every third day. A minimum of 20 late second instar thrips were placed onto the leaves of the plant, and were left until enough degree-days had passed for the thrips to molt to the propupal stage, typically about 5 days. The seedling was then cut at the soil line and examined for pupating thrips; the removable lid was sprayed with Tangle Trap sticky coating to collect any emerging adults after another 5 days. Data were analyzed using a 3-way ANOVA with density of seed , application of B. bassiana , and date as factors . Unrecovered insects were counted as missing data and were not included in the analysis. The commercial blueberry test site selected was located north of Bakersfield in Delano, CA. The trial began in August of 2008 and was conducted post blueberry harvest. The V. corymbosum varieties contained within the test area were, ‘Santa Fe’, ‘Jewel’, and ‘Star’. The most susceptible variety of blueberry to citrus thrips damage grown at the test site was the ‘Star’ variety and ‘Star’ was used consistently for evaluation of thrips numbers for all aspects of the trial . Our cooperator was interested in alternatives to traditional pesticides as the farm regularly was dealing with extremely high citrus thrips populations. For example, in 2008 the grower sprayed 5-10 times per field , rotating with traditional chemicals to reduce thrips impact on the subsequent year’s fruit set. Irrigation in all fields took place via drip irrigation with one water delivery emitter per line at each plant base , but additionally, one portion of the blueberry field was equipped with 360° overhead sprinklers. This irrigation setup provided the ideal situation to test B. bassiana under two watering regimes.

The commercially available GHA strain is formulated to be mixed with water and for application via chemigation or as a foliar spray. The label states that no surfactant is needed to keep the spores in suspension. However, agitation alone in the 1,892.7 L holding tank was not sufficient to keep the material from precipitating,black flower buckets therefore 312.3 ml of Silwet L-77 was added to the tank mix. Mycotrol O® was applied directly to the soil surface with a gas-powered sprayer with a hand spray gun equipped with an adjustable flow meter. The dimensions of the plots were used to calculate the amount of material needed for both B. bassiana formulations . Plants in the test field were spaced every 0.92 m down each row, 3.35 m between each row, and each row was about 165 meters in length. Our studies were conducted in an 18-row section of a 4.04 ha field. The overhead sprinklers were spaced every 7 meters in the row and were located every other row for 12 rows. We chose to investigate the effectiveness of the B. bassiana colonized millet seed versus a Mycotrol O® soil application under two watering regimes, drip-line alone versus drip-line with overhead sprinkler, because B. bassiana conidia are highly subject to desiccation. Comparing the soil drench in both irrigation types with the colonized millet elucidated the effectiveness of the treatments when compared to the control. The blocks were laid out in a 3 x 2 factorial design, with each block consisting of most of five rows of blueberries , each being 27.4 m long . The berm used to grow blueberries at the commercial farm was 1.21 meters wide and each plot was 27.4 meters long. The spacing between adjacent rows was 3.35 m, while the spacing between the plants down a row was approximately 0.92 m with 30 plants per treatment plot . These dimensions result in 0.157 ha treated with raw spores but because the top of the berm was where thrips activity was evident and would be sampled, only 36% of the soil surface area was treated. The Mycotrol O® label states that the maximum field rate is 6.9 L/ha mixed in 935.3 L/ha water. We therefore chose to apply the entire 6.9 L of Mycotrol O® in 378.5 L of water per ha directly to the berm with no application between the rows, which resulted in 100% of the per ha rate of product being applied to 36% of the area and allowed the maximum amount of active ingredient to be applied to the area that would have almost all thrips activity . Our field trial was intended to determine the extent to which B. bassiana might fit into a program projected to both control citrus thrips effectively and provide rotation among available chemistries so as to reduce thrips resistance evolution.

Thus, we felt it was important to operate under the best possible conditions for thrips infection by Mycotrol O® , regardless of financial considerations, i.e. application of product at the maximum label rate in the area where thrips were most likely to be active. The amount of millet seed used in the field trail was calculated based on the area of the berm to be treated and likewise with the Mycotrol O® treatment, only 36% of the total field area was treated. The amount of seed used was one colonized seed/ 2 cm2 over an area of 576 m2 ; the fact that 0.45 kg of seed was needed per 840 cm2 resulted in the application of 3.40 kg of colonized millet seed for the 8 treated plots . Every other plant within the middle ten plants of the middle row of each plot were sampled with pupation emergence cages . These cages were placed tight against the base of each set of canes on the east side . With 5 cages per block and 4 replicate blocks per treatment, a total of 20 cages sampled thrips pupation per treatment over two sample periods, i.e. for two consecutive 3-day periods after the Mycotrol O® soil drench. The treatments were: no B. bassiana with and without overhead sprinkler; colonized millet seed with and without overhead sprinkler; and a soil drench of Mycotrol O® with and without overhead sprinkler . In total, data were collected from 240 emergence cages over the duration of the trial . The colonized millet seed was set to imbibe water and allowed to sporulate for three days before application and was applied using a hand fertilizer applicator . Four days post application of the millet seed, the soil drench of Mycotrol O® was applied and pupation emergence cages were placed in the field and left out for 3 days . After three days, the sticky cards from each emergence cage were collected and replaced with new cards and the traps were switched to the next plant on the east side. These traps were left in the field to sample thrips for another 3 days . Because the traps were placed out every other plant, this ensured that all of the middle ten plants were sampled over the two, 3-day sampling periods .

Only 39 cases needed to be top coded to 20 servings. The individual fruit and vegetable items for all 39 cases were examined carefully to make sure that they consisted of believable number of servings, albeit large numbers reported, and all 39 were accepted to remain part of the data file for analysis.The General RDD sample in File-1 was weighted to 1990 Census data for California adults using race, age group, and gender dimensions to emulate the standardized weighting of the CDPS surveys—all of which were weighted to the 1990 Census. Weighting within each of the three race/ethnic groups within each month’s sample, the ANOVA model was used to examine the year-month interaction term and variation among months for White, African American, and Latino groups. This last analysis produced the conclusions for this study with regard to seasonality in fruit and vegetable intake.As part of a nested design, three brief questions were asked to a randomized subset of survey respondents to see how well these might perform compared to the longer, more complex set of CDPS recall questions. This short form of the intake questions are referred to in this study as the “SF3.” For this analysis of the SF3,25 liter pot plastic approximately 57% of the File-1 sample was used due to prior random allocation.

These respondents were administered the SF3 questions ahead of the usual CDPS dietary intake questions. The SF3 captured the following: the number of servings of fruit not including 100% fruit juices ; the number of servings of 100% fruit juice ; the number of servings of vegetables ; and, the total number of servings of fruit and vegetables . Analyses were performed comparing each respondent’s SF3 answers and the respondent’s corresponding number of servings calculated from the CDPS intake responses. The initial analytical step examined Pearson correlations to see if they were positive and relatively high for this type of measurement . If true, results were then examined using a paired t-test to see if there was any consistent bias in the relationship between the SF3 and the CDPS questions. Paired t-tests were performed using a two-tailed significance level of 0.05. Looking at the 6,650 cases in File-1 and the 4,031 low-income cases in File-2 , the year-month interaction is significant for the total servings of fruit and vegetables for File-1 and File-2 . In File-1 this is not the case for servings of fruit . The observed pattern of servings of fruit intake seen in Exhibit 7 shows the month of July with the highest intake at 2.5 servings and November with the lowest intake at 2.0 servings.

Since the year-month interaction is significant for servings of vegetables , a direct interpretation of the monthly variation is not possible. In File-2 there is significant year-month interaction for both servings of fruit and vegetables . These findings indicate that the patterns of intake across the 12 months is different for each of the two years of data collection , and thus it is not feasible to combine the monthly samples from these two years to interpret variation among the months using all the cases in each file. The General RDD component of File-1 , a sample that does not have any race/ethnic over-samples included and thus very much like the CDPS general population sample, has no significant year-month interaction for the total servings of fruit and vegetables. This is also true, as might be expected, for the servings of fruit and the servings of vegetables, separately. Thus, it is the Targeted RDD component of File-1 consisting of the “all-incomes” over-samples of Latinos and African Americans where significant interaction is found for total fruit and vegetables , total fruit , and total vegetables . Given the findings for the General RDD component, the pattern of intake across the 12 months is not significantly different for each of the two years of data collection, and therefore, it is possible to combine the monthly samples from these two years to interpret variation among the months. However, the significant year-month interaction for the Targeted RDD component precludes a direct interpretation for the “all-incomes” oversamples of Latinos and African Americans.

The results for variation among months in the General RDD sample suggest that there is no significant difference among months for the total servings of fruit and vegetables. However, the p-value is exactly 0.05 and is right on the boarder of being statistically significant. Variation among months for the total servings of fruit and for the total servings of vegetables are each not significant. Exhibit 8 shows the average number of servings per month for each of the twelve months of the year for total fruit and vegetables, for fruit, and for vegetables in the General RDD sample after combining the data for Year-1 and Year-2. These results and monthly patterns in the General RDD sample are virtually unchanged even after controlling for race, ethnicity, and gender . Since the sample is designed to examine fruit and vegetable intake for Whites, African Americans, and Latinos, results are generated for each in both File-1 and File-2 . Exhibit 9 shows the results of the ANOVA Ftests, looking first if any year-month interaction exits, and if none exists, looking for significant variation among months as an indication of seasonal effects. No seasonality is found for Whites when looking at all income levels for total fruit and vegetables, or for fruit and vegetables separately. This is true for low-income Whites for servings of fruit and for servings of vegetables, but significant year-month interaction for the total number of servings of fruit and vegetables precludes any direct interpretation of monthly variation. No seasonality is found for African Americans when looking at all income levels for the total of fruit and vegetables or for fruit and vegetables separately . This finding is also true for low-income African American, with the exception of significant monthly variation for servings of fruit . It is not possible to interpret directly the results either for Latinos of all-incomes or for File-2 low-income Latinos, since there is significant year-month interaction for the total of fruit and vegetables as well as for fruit and vegetables separately.

An examination of the monthly pattern for Years 1 and 2 separately shows each year to be very different; however, the pattern within each year is similar for the Latinos in File-1 and in File-2. The very different patterns for each of the years are the cause for the significant year-month interaction. To demonstrate this, the pattern for the total number of servings of fruit and vegetables for Year 1 and Year 2 and for File-1 and File-2 Latinos is shown in Exhibit 10. Observe that March and April, June and July, and September, October, and November appear different between the two years. There is no explanation for these different patterns. When looking only at the low-income cases found in File-1, the picture changes slightly . For low-income Whites, no year-month interaction is now detected as it was shown when looking at all income Whites. This is also true for servings of fruit for lowincome African Americans. or African Americans , they may be harder to detect given the smaller sample sizes of these low-income groups. A year-month interaction for total fruit and vegetables is also not detected. For both Whites and for African Americans , no variation among months is found for the total servings of fruit and vegetables or for fruit and vegetables separately. For Latinos,25 litre plant pot with a large sample size of 1,040, year-month interaction for total fruit and vegetables is not detected and no significant variation among months is found for the total servings of fruit and vegetables . However, significant variation among months is found for servings of fruit. Exhibit 12 shows the observed highest months of fruit intake to beFebruary and June with the lowest observed months to be March, May, and November. It is not possible to easily determine variation among months for the servings of vegetables due to significant year-month interaction . To gain additional insight into the low-income Latino patterns, the data are examined by the two levels of Latino acculturation: high and low. Exhibit 13 shows that there is no significant variation among months for Latinos with high acculturation whether the data are examined for all incomes , or for those with low-income. Among Latinos with low acculturation, however, it is not possible to easily interpret the data for the all-incomes groups due to significant year-month interaction . For the low-income, low-acculturation Latinos, there is no significant variation among months for total fruit and vegetables . For servings of fruit, both the all-incomes and low-income Latinos show significant variation among months if they are low acculturated.

Exhibit 14 shows the observed average servings of fruit per month for low-acculturation Latinos in the all-incomes group and the low-income group . The months of February and June show the highest averages, while March, May, and November show the lowest averages of fruit intake. These observations for individual months for both lowincome acculturation groups are the same as seen in Exhibit 11 for all low-income Latinos regardless of acculturation level. The CDPS data for the eight bi-annual surveys conducted since 1989 are each weighted to the 1990 Census for California. The cases are weighted for gender, age group, and race dimensions. Since the General RDD sample in this study is similar to the CDPS general population sample, i.e., it includes the entire adult population , this study’s General RDD sample data have been weighted using the identical weighting approach used in the CDPS. In Exhibit 15, using the weighted General RDD sample data , no two groups are statistically different from each other. In an examination of the variation among months, Exhibit 18 shows the results for the overall population of all adults as well as the results for Whites, African Americans, and Latinos. Among all adults, variation among months is found to be significant for the total servings of fruit and vegetables consumed. However, this variation is not significant either for servings of fruit alone or for servings of vegetables alone. Exhibit 19 shows the monthly averages across the year. It is found that the average number of servings for total fruit and vegetables in the month of July is significantly higher than the number of servings in January , a difference detectable due to the relatively large sample size. However, July is found to be not significantly higher than any other month in the year. There is no significant variation among months found either for servings of fruit or for servings of vegetables for the adult population. For Whites, there are no significant differences in the variation of number of servings among months for the total of fruit and vegetables or for either fruit or vegetables alone. The observed monthly patterns for Whites are shown in Exhibit 20. African Americans show significant variation among months for the number of servings of total fruit and vegetables and for servings of vegetables . Despite the pattern for servings of fruit being very close to that of vegetables, no significant difference is detected for servings of fruit . Exhibit 21 shows the wide variation observed among the months of the year. Even with the smaller African American sample, significant differences between individual months for total servings of fruit and vegetables are seen, with the month of December higher than June and January and none of the other months being different from each other. Although the variation among months for servings of vegetables is found to be significant, the follow-up procedure could not detect any significant differences between individual months. The small AfricanAmerican sample, 177 cases distributed over 12 months , needs to be considered when interpreting these findings. Latinos show no significant differences in the variation of number of servings among months for the total of fruit and vegetables or for either fruit or vegetables alone. The observed monthly patterns for Latinos are shown in Exhibit 22. The large sample sizes used in this study reveal that patterns across the months of the year can differ from year to year, as indicated by the significant year-month interactions found for the overall samples of both File-1 and File-2.

Based on the preferred effective Ks, the highest θc deviation between the RZRT model and HYDRUS is one day. While this is a reasonable error for the hard pan characteristics tested here, it is based on one limited example and cannot be regarded as representative. Using effective soil hydraulic parameters to represent highly-contrast layered soil as a uniform soil profile is a complex problem which was beyond the scope of our simplified analysis. Hence, the hard pan analysis implemented in the RZRT learning tool can be used as a first approximation only. Obviously, in fields with a massive hard pan layer, deep percolation is limited, and implementation of Ag-MAR project is not recommended. The drainage curves for all USDA soil texture classes provide an initial estimation of soil suitability for Ag-MAR . The crops almond, walnut, alfalfa, and grape in Fig. 4 with flooding tolerance of 2, 7, 14, and 21 days, respectively, represent the four tolerance classes in Table 3. Since crops have different flooding tolerances, soil drainage largely controls the effective flooding duration. The slow drainage rate combined with the low flooding tolerance that some perennial crops have, make clayey soils, as expected, unsuitable for Ag-MAR. The clay loam soil with shallow-rooted high-tolerance crops, might be suitable for Ag-MAR in terms of drainage duration, however, its ability to transfer large quantities of water is hindered by its relatively low hydraulic conductivity questioning its Ag-MAR suitability. The silty clay loam is an exception of the clayey soils,30 plant pot as it can be used for Ag-MAR with moderate- and high-tolerance crops.

The reason for this exception is the low sand content combined with the silt and clay proportions, which results in a higher critical water content as aggregated soils have higher θccompared to structureless sandy soils . For the same reason, loam soil with lower θc can be used only for Ag-MAR if shallow-rooted moderate- and high-tolerance crops are considered. According to the drainage curves, silt loam and sandy loam soils are suitable for all crops, excluding minimal-tolerance crops, while sand, silt and loamy sand soils are suitable for all crops that have minimal flooding tolerance. For most Ag-MAR sites with contrasting soil layering along the root zone, the model prediction will be less accurate, and a procedure of parameter averaging may be necessary to improve the model performance. Similar model limitations that are related to the homogenous soil profile assumption, are expected at sites with substantial soil heterogeneity, as our results show for the Stoner gravelly sandy loam . A reasonable estimation of the hydraulic parameters is another limitation that should be considered. For example, according to the soils tested in this work, when using fitted and average unfitted hydraulic parameters, twap is overestimated by 0.2 and 1.7 days, on average, respectively . The model assumption of rigid porous media with constant hydraulic properties poses another difficulty, especially under Ag-MAR conditions where the soil can be waterlogged for relatively long periods . Changes in soil structure and hydraulic properties during prolonged flooding were reported in paddy soils due to clay swelling ; however, shrink-swell dynamics are more prominent in clayey soils , which are potentially less suitable for Ag-MAR. The use of hydraulic parameters from a soil database can lead to moderate or poor predictions compared to soil-specific hydraulic parameters.

The shape parameter m and the scale parameters θr, θs and Ks control the drainage curves and therefore are the most important parameters in the RZRT model. For improved accuracy, these parameters should be evaluated insitu at the designated Ag-MAR site. θr and θs can be estimated by the gravimetric method and Ks of the upper soil by various field infiltration tests . Estimating m can be attained by fitting of the SWRC or the particle size distribution ; however, these methods are time-consuming, so it is recommended to obtain m from a soil database, the literature, or to use a pre-defined m based on soil texture. Lastly, and probably most importantly, the parameter estimation of θc can change markedly depending on the method it was first evaluated with . Moreover, the concept of a constant θc is an oversimplification used in the model, because θc is a function of biotic and abiotic parameters, which vary spatially and temporally for a specific soil texture. Indeed, our data indicate that during intervals of AgMAR flooding and drainage, different θc can be obtained even for the same location in the soil . This is probably related to changes in soil respiration after flooding is initiated as well as SWRC hysteresis . Te idea that one should be eating healthy to stay healthy is not a debate. Numerous studies show how particular foods individualistically effect human health, but none thus far, to our knowledge, have investigated about the combined impact of a specific diet on the human body as a whole. It is critical for us to understand which kinds of things we should eat and the ways in which their collective consumption will impact our bodies. According to Dr. Tomas J. Carlson, a distinguished pediatrician and ethnobotany researcher, choosing foods from every color in the rainbow is the key to good health.Each fruit and vegetable gets its natural color from the chemical composition of the exclusive phytonutrient in it.Interestingly, the presence of one molecule in one fruit/ vegetable does not necessarily reflect the same color in another type of fresh produce.

For instance, although the rich red color in most red fruits and vegetables is naturally derived from the phytonutrient lycopene, most berries such as strawberries and raspberries do not contain lycopene. Instead, they contain brightly colored chemicals called anthocyanins, which are made in plants during ripening season through the joining of a molecule of a sugar with a molecule of their colorless “anthocyanidin” precursors.Anthocyanins are also found in raspberries, which are high in dietary fiber and vitamin C and have a low glycemic index because they contain 6% fiber and only 4% sugar per total weight.Higher quantities of fiber in the fruit, when consumed, helps lower the levels of low-density lipoprotein or the ‘unhealthy’ cholesterol to enhance the functionality of our heart and potentially induce weight loss. Te exact pigment that anthocyanins reflect is partly dependent on the variance in acidity or alkalinity in different plants. Because of the relatively high pH of the tissues in blueberry plants,grow raspberries in a pot these chemicals turn blue in color during the ripening process of the fruit.Recent research in the Journal of Nutrition suggests that the abundant antioxidant properties in wild blueberries contributes to the reduction in the development of such disorders as Alzheimer’s Dementia and cognitive loss.A type of antioxidants selectively found in yellow and orange colored foods are called cryptoxanthins. In a study conducted by Bovier et al., it is shown that the combination of the beta form of these carotenoids with other sources of nutrients such as lutein and zeaxanthin in carrots, oranges, and corn leads to improved visual processing speed with regular consumption in young healthy subjects.While green produce mainly derives its pigmentation from chlorophyll, its white counterparts get their natural color from anthoxanthins, favonoid pigments that exhibit antioxidant properties. Among green fruits and vegetables, broccoli stands apart as the most nutritious because of the special combination in which its 3 glucosinolate phytonutrients are found. Tis “dynamic trio” makes what are called Isothiocyanates , the detox-regulating molecules in broccoli that enhance vitamin A in the form of beta-carotene.Many recent studies claim that the antioxidants in ITCs not only regulate metabolism and cholesterol levels when consumed but also act as cancer chemopreventive phytochemicals.Fruits that are on the same level as broccoli with regards to health in the white-produce family are bananas. Japanese Scientists reveal that the high amounts of vitamin B6, manganese, potassium and fiber in the ripened versions of these fruits can help prevent high blood pressure, protect against atherosclerosis, and improve immunity levels in regular eaters.Despite an enormous amount of scientific knowledge and evidence for the overall beneficial effect of a single fruit/vegetable and/or phytonutrient at a time on human health, no study so far, to our knowledge, has been able to conclusively link the validity of these claims to the whole human body. This offers the opportunity for one to test the combined impact of eating a colorful diet on humans through a systematic study. The purpose of our investigation is to apply a more holistic approach to the study of how the human body is effected as a result of a diet that is composed of all the colors of the rainbow. In other words, in addition to exploring the individual food stuf’s role in improving health, we want to analyze the outcome of the regular incorporation of a whole pack of colorful foods into one’s meals. Consequently, this study can serve to reveal the effect, if any, of a continued and rigorous diet consisting of all colors of the rainbow on the physical and mental health of a randomized sample of the adult human population in a given demographically comparable community.

The current study is a small-scale secondary application of some of the methods used in a previously conducted study that has been reported elsewhere.The primary study used a randomized controlled trial to compare the effect of daily consumption of probiotic versus low-fat conventional yogurt on weight loss in healthy obese women; the outcomes tested were changes in anthropometric measurements . In our study, we measured hand grip strength and stress levels in addition to some of the parameters mentioned that were tested in the primary study. We created a Rainbow Diet Pack that consisted of the following fruits and/or vegetables in the respective quantities: raspberry , orange , baby carrots , corn broccoli foret , blueberry , and banana . The choice of each kind of fresh produce was based on the specifc nutritional facts and molecular composition of the phytonutrients in each . As per the personal choice of its members, the intervention group received daily administration of RDP during a 10-wk intervention period. Measurements were taken of both the study and the control groups twice: at baseline and at the end of the intervention period. Our study design was in accordance with the Declaration of Helsinki.Twenty-four normally healthy human adult volunteers who belonged to the same demographic identity and had similar dietary backgrounds were recruited by word-of-mouth from the local community of the student investigators and screened for health. A total of eight were chosen to participate. Individuals were eligible for the study if they were nonsmokers, free of known disease, not allergic to items in RDP, not taking medications and were identifed as being healthy according to the following criteria: body mass index between 18.5 to 24.9 kg/m2 and a self-report of no diseases/illnesses in the previous 6 months. Randomization A computerized random number generator was used to assign individuals chosen to participate to either the control or the intervention group. At the end of the baseline screening, a message containing the participant’s number assignments was sent via email to the participants. Participants and the student investigator were aware of group assignment during the intervention phase. Participants were not aware of other participants who have agreed to be in the study. Before analysis, the primary investigator received an anonymized data set and was no longer aware of group assignment post data collection; no data can be traced back to the individual participant.The aim of this study was to assess the effects of eating a diet consisting of all the colors of the rainbow in the form of an RDP once a day on weight loss, stress levels, and other indexes of health in normally healthy volunteers during a 10 wk intervention program. We found that consumption of RDP as lunch may result in positive changes in waist circumference, weight loss and stress levels as measured during the program. This was despite fnding no signifcant diferences in observed hand grip strength between the study and control groups. In spite of evidence for the beneficial effects of eating various naturally colorful produce on obesity and health, to our knowledge, this was the frst randomized controlled trial that investigated the effect of consuming the RDP as a whole on weight loss and stress levels in healthy human subjects.

Water samples were analyzed for their stable isotopic compositions using Los Gatos DLT- 100 laser isotope analysers for Dorset and Wolf Creek, a Los Gatos Liquid Water Isotope Analyzer for Bruntland Burn and Dry Creek, and a Picarro L2130-I for Krycklan. The precision of the liquid water stable isotope analysis is reported to be better than ±0.1 ‰ for δ18O and ±0.4 ‰ for δ2 H. All isotope data are given in delta-notation in reference to the VSMOW. At all sites – apart from Dry Creek – direct water-vapor equilibration analysis was used to sample the bulk soil water isotopic composition from the soil . The accuracy of the direct water-vapor equilibration method was ±0.3 ‰ for δ18O and ±1.1 ‰ for δ2 H. For a detailed description of the procedure, we refer to Sprenger et al. . Bulk soil water isotopic compositions at DC were sampled using cryogenic extraction at 100°C under vacuum of < 30 millitorr over 40 minutes, as described by McCutcheon et al. . We are aware that different methods of soil water extraction have been a major focus of research in the past few years, with no definitive agreement on a standard method . While differences between cryogenic extraction and the direct water-vapor method have been reported in laboratory experiments ,container raspberries previous work by the authors has found the direct equilibrium method to be a reliable method for extracting bulk soil water from sandy soils giving similar results to cryogenic extraction .

Source water apportionment of plant xylem: To quantify the potential source of vegetation water from different soil depths and over a range of time periods, a modification of the ellipsoid method was utilized for the gymnosperms and angiosperms at soil depths in 10 cm increments up to 40 cm. All soil samples deeper than 40 cm were lumped together. The 40 cm cut off was chosen due to fewer sites sampling below 40 cm and a large decrease in the temporal resolution of sampling which could otherwise skew results. Due to soil water fractionation resulting in deviation from the local meteoric water line, the data are not well represented in an ellipsoid shape such as that employed in Amin et al. . Therefore a minimum polygon area was used to encompass the data points. Based on Equation 5, we derived the sw-excess of xylem isotope data. For sw-excess less than 0 ‰, the xylem data plot below the soil water line of the corresponding soil water isotopes sampled on the same day. Thus, the sw-excess can serve as an indicator for deuterium fractionation between the uptake time at the root-soil interface and the measured xylem water. We acknowledge that the soil water line is not necessarily solely a product of evaporative enrichment and that seasonal variability of the stable isotope compositions of the precipitation can affect how much soil waters deviate from the LMWL . However, the process of how the “soil water line” developed is not important here, since we used the regression to describe the isotopic compositions of potential water sources for vegetation at the time of sampling.

The influence of site characteristics on soil and xylem isotopic samples was evaluated using Spearman rank correlation. Site characteristics, mean annual temperature , elevation , aridity index , annual precipitation , and latitude , were correlated to xylem and soil water δ2 H , δ18O , and the corresponding sw-excess , and lc-excess to a significance level of 0.001. Isotopic compositions of all soil depths, vegetation species and sampling times were bulked for each site to assess an overall trend of soils and vegetation in relation to climate indices. Statistical analysis of isotopes in precipitation, bulk soil water, angiosperms, and gymnosperms was conducted at each site using the Wilcoxon signed-rank test to test the statistical similarities of median values of the datasets. This allowed for a two-sided probability test without the assumption of normality. The datasets were tested to the 95% confidence limit using all available data .Plant water and soil water data from the five sites are plotted in Figure 2. For both soils and xylem, the sites occupied partially overlapping regions showing a general gradient from highly isotopically depleted at Wolf Creek, the coldest of our sites in Canada, to the more isotopically enriched waters at Bruntland Burn at the temperate/boreal transition in Scotland. For each site there was a substantial range of variability in soil and xylem water isotope composition over the course of the sampling year. Most soil and xylem samples plotted below the GMWL, although xylem waters were generally more 2 H-depleted at each site, which was also evident from the lc-excess data . Samples from Dry Creek and, in particular, Wolf Creek showed the greatest divergence from the GMWL.

These two sites slightly obscured an otherwise clear relationship between plotting position along the GMWL and the mean annual temperature gradient through Krycklan, Dorset and Bruntland Burn. Despite this, the isotopic ratios of δ2 H and δ18O in soils and xylem water correlate positively with air temperature, annual precipitation and aridity index, and negatively with elevation and to a lesser extent latitude . At all sites, substantial isotopic differences were apparent between xylem and soil water isotopes, and between angiosperms and gymnosperms . Gymnosperms generally plotted further from the GMWL . Soil waters at each site generally tracked precipitation and snowmelt inputs being more 2 H- and 18O-depleted in winter/spring and more enriched in summer; evidence of evaporative fractionation was also most evident in the more 2 H- and 18O-enriched summer soil water samples. The soil water data are shown relative to the sampling dates for each site in Figures S2 to S6 in the Supplementary material; also see Sprenger et al. for more detail. Soil water δ2 H data were significantly different from precipitation at Dry Creek, Dorset and Wolf Creek, while soil water δ18O differed from precipitation at Bruntland Burn and Dorset . Bruntland Burn, Krycklan and Dorset showed the greatest visual deviation of xylem δ2 H samples from soil water, while the most southern site, Dry Creek, and the most northern site, Wolf Creek, showed smaller differences between the xylem and soil water isotopes for δ2 H . However, at all sites the δ2 H characteristics of both angiosperms and gymnosperms were significantly different from soil water . Angiosperm xylem water δ18O at all sites, apart from Krycklan, was significantly different from soil water δ18O; whereas significant differences for gymnosperms were apparent only for Dorset and Bruntland Burn. Xylem water isotopic characteristics differed between angiosperms and gymnosperms at some sites. For δ2 H, they were significantly different for Krycklan, Bruntland Burn and Dry Creek, while for δ18O they were different for Dorset and Dry Creek . Snowmelt plotted on the LMWL and was more depleted for 18O than almost all measured soil and xylem waters,draining pots although a substantial number of xylem samples at Dry Creek, Krycklan and Wolf Creek were more depleted in 2 H but plotted off the LMWL . Similarly, at the four sites where groundwater samples were collected, the mean isotopic composition of groundwater fell on the LMWL but plotted towards the more depleted end of the range of soil water samples. This reflects the generally higher recharge of groundwater by depleted water following the spring melt at Dry Creek, Krycklan, and Wolf Creek ; and during winter rainfall at Bruntland Burn . Isotopic composition of groundwater at all sites showed limited temporal variation, indicating the volume of annual recharge is small relative to groundwater storage. Groundwater was generally more strongly depleted in 18O than xylem waters for both angiosperms and gymnosperms, although at each site a substantial proportion of xylem samples were more depleted in 2 H.The minimum boundary polygon analysis quantifies the degree to which xylem water for both angiosperms and gymnosperms overlaps bulk soil water sources at different depths. The use of the spatially bulked data for soils and vegetation at each site was necessary to provide a sufficient number of samples for the development of encompassing polygons.

This may lead to larger estimated polygon areas and a greater estimated overlap of soil and xylem water, although the effect is much less marked than for the ellipse method of Amin et al. . This may provide insight into the sources of xylem water, although the proportion that cannot be ascribed to soil water sources is equally informative regarding the need to hypothesise and identify other causal reasons. Distinct inter-site differences emerged in terms of the overall overlap of xylem and soil water isotopic composition . For Bruntland Burn, soil water had a 77% overlap for angiosperms, but only 6% for Gymnosperms. At Dorset, like Bruntland Burn, angiosperms showed a much higher degree of overlap than gymnosperms . At Dry Creek, almost all xylem water in both angiosperms and gymnosperms overlapped soil water at almost all profile depths. Of all sites, Krycklan had the lowest degree of overlap with only 27% for angiosperms and 0% of gymnosperms . Finally, while Wolf Creek had only angiosperms present as willow and birch shrubs, a 99% overlap between xylem water and soil water was evident. The depth dependent overlap of xylem and soil water isotopic composition showed differences between depths, with higher overlap tending to be in shallow soil depths for most sites. For Bruntland Burn, there was 72% and 55% overlap between angiosperms and soil water at 0-10 cm and 10-20 cm depths, respectively, but only 9% and 3% for gymnosperms. Dorset was the only site with the greatest overlap occurring in deeper soil, with overlaps of 34%, 28%, 24%, 59% and 31% for 0-10, 10-20, 20-30, 30-40, and >40cm, respectively. The gymnosperms at Dorset had a similar deviation to that of angiosperms, with much smaller overlaps of 4%, 7%, 8%, 18%, and 7%, for 0-10, 10-20, 20-30, 30-40, and >40cm, respectively. Depth-dependent overlap of soil and angiosperms at Dry Creek was high through all soil layers with the greatest overlap in the near-surface soils . Gymnosperms at Dry Creek had a similarly high overlap of 78%, 55%, 86%, 72% and 86 % for 0-10, 10-20, 20-30, 30-40, and >40cm, respectively. At Krycklan, the upper two soil depths had approximately the same overlap for angiosperms , with a moderate decrease to 12% in the 20-30 cm soils. None of the soil water at any depth overlapped the gymnosperm samples. Wolf Creek angiosperms showed a high overlap in the upper two soil depths with a more substantial decrease in deeper soils .The general patterns of the pooled data sets for the entire study year mask differences in the degree to which seasonal variations in the isotopic composition of xylem water can be ascribed to soil water data collected on the same day or integrated over increasing monthly time windows to capture antecedent conditions. However, as described in section 2.2, soil water boundary polygons for increased averaging periods can also be calculated to estimate the overlap relative to xylem. Depth dependent overlaps are shown in Figure S7 and Figure S8, respectively. At Bruntland Burn, a longer time window of soil water isotopes explained a greater degree of variation in xylem water isotopic composition for angiosperms . Bulked soil water samples collected on the same day provided 80% and 87% of overlap in spring and autumn, respectively, but only 4% in summer. Increasing this window to 3 months increased overlap to 90%, 38% and 87% in spring, summer, and autumn, respectively. The spring and summer bulked soil and xylem water overlap increased to 100% and 58%, respectively, with a 6 month window. For gymnosperms, same day sampling provided no overlap in spring and summer, and only 7% in autumn . For a 3 month window, overlap increased to 20% in spring, but only 3% in summer and 7% in autumn. For a 6 month window, the autumn overlap increased to 13%. There were marked seasonal differences between angiosperms and gymnosperms at Dorset. For angiosperms, bulked soil and xylem water overlapped for same day sampling 100% in spring, 0% in summer and 20% in autumn . This increased to 20% in summer for a 3 month averaging window and 47% in summer for a 6 month average. The overlaps were much lower for gymnosperms; same day sampling showed bulked soil and xylem water overlaps of only 13% in spring, 2% in summer and 7% in autumn .

Data were summarized separately for each of the two years. For each year, a Chi square goodness of fit test was used to examine whether or not there were equal levels of a damage type among three treatment categories within a variety. If there was a significant difference in damage among the three treatments in a variety, then Fisher’s Exact tests were used to compare each pair of treatments. Tests were considered significant at the p < 0.05 level. This study examined the impact from feeding by two Leptoglossus species, L. clypealis and L. zonatus, on developing almonds in four varieties during the growing season. Almonds of each variety were caged with equal numbers of adults of each species to determine the potential impact. Early in the growing season, leaf footed bugs fed by puncturing their stylets into the developing almond accessing the jelly-like immature kernel. In both years, almond drop in the controls was low,blueberry pot size while almond drop in cages with Leptoglossus adults was twice as high. The first month of the study in April had higher levels of almond drop than in the later weeks of the study in May. The time in April corresponded to weeks when the almond shell could be punctured mechanically and indicated that the developing almonds were more vulnerable than in May, when the shell had hardened.

Overall, almond drop during the season was lower from L. clypealis than from L. zonatus. This may be due to the smaller size of L. clypealis compared to L. zonatus adults. Monterey had higher levels of almond drop from L. zonatus in both years than the other three varieties. Feeding by leaffooted bugs also caused significant damage to almonds in the form of nut strikes, kernel necrosis and shriveled kernels. The final damage observed at almond harvest was higher overall from feeding associated with L. zonatus than L. clypealis. Other studies have found significant crop damage from the presence of Leptoglossus clypealis and Leptoglossus zonatus. For example, feeding by L. zonatus in physic nut increased fruit abortion. A study of L. clypealis on pistachio found that when one adult L. clypealis fed for 48 h, the number of fruits dropped was higher on average than in controls. L. zonatus feeding in citrus resulted in spots on the outer citrus rind and feeding on satsuma mandarin by 1–3 adults for 14 days resulted in 37.5–100 percent of premature fruit abortion. Studies such as these demonstrate the need for controls, to determine the natural level of fruit abscission, and which damage symptoms can be attributed to insect feeding.Developing almonds may be more susceptible than mature almonds to feeding damage from Hemiptera, as has been observed in pistachios. In the present study, the almond shell could be punctured by an insect pin until the end of April but by May, the external almond shell became too firm to puncture and almonds were presumed no longer susceptible to bug feeding. The majority of almond drop in the four varieties occurred in the first few weeks of observations.

After the fifth observation week of caging Leptoglossus on branches, the percent almond drop decreased relative to the early weeks of observations and remained minimal. This agrees with an early study by Haviland, where almonds were artificially damaged by puncturing, and more almond drop occurred in April than in May. Our study was a no-choice test, where bugs were caged with only one almond variety; when offered one variety and no choice, the levels of almond drop were similar among the four varieties. However, in a natural field-study where almond drop was assessed after a Leptoglossus infestation, higher levels of almond drop were observed in Fritz . When provided with a choice of varieties, L. clypealis appeared to prefer to feed on Fritz. Almonds on the trees that were fed on by bugs later in their development may not drop but can suffer downgrades or rejects at harvest as observed for other crops. In pistachios, Leptoglossus sp. was capable of causing feeding damage to the pistachio kernel even after the hardening of the shell. Michalides et al. found that the large bugs including Leptoglossus clypealis were able to cause pistachio kernel damage until late June, when nut development was at the final stage. A late season feeding study of large bugs in pistachios found that kernel necrosis could range up to 20%. The vulnerability of almonds later in the growing season has not been fully investigated. Leptoglossus may cause feeding injury to almonds which are well developed, and thus might be monitored and controlled throughout the growing season. In other systems, fruit size and shell hardness has been found to influence the level of insect feeding damage.

Feeding on physic nut by Leptoglossus zonatus resulted in larger fruits having more seed abortion and feeding resulted in more shriveled or damaged nuts; similarly, some varieties of olives with larger fruits had a higher infestation rate by the olive fruit fly, Bactrocera oleae. In hazelnut, shell thickness was not correlated with damage by brown marmorated stink bugs, Halyomorpha halys, and the authors suggested that shell thickness should not be a criterion to select cultivars resistant to H. halys. Follett et al. reported that husk and shell thickness in macadamia nut do not primarily determine susceptibility of fruits to Nezara viridula. Hull width could relate to the susceptibility of the almond to feeding damage by the two leaf footed bug species. Although there was a significant difference in hull widths between Nonpareil and Fritz, there was no relationship between hull width and almond drop. In addition, the hull width of Nonpareil was significantly thicker than Fritz, but hull strikes on Nonpareil and Fritz from L. clypealis and L. zonatus did not vary significantly, and nut strikes were also not higher on Fritz. This suggests that damage from Leptoglossus feeding on these two varieties was not influenced by hull width . In 2015, higher levels of damage were observed in all four varieties compared to 2014, but again did not relate to the hull width differences . The final assessment of damage from L. zonatus and L. clypealis included hull strikes, nut strikes, kernel necrosis and shriveled kernels. Insects probing the hull results in hull strikes and suggest that the internal almond kernel may be damaged. Nut strikes, almond kernel necrosis and shriveled kernels can lead to downgrades or unsellable product. In both years of this study, the cages with both Leptoglossus species typically had higher levels of hull strikes and nut strikes than in the control cages. In 2014, L. clypealis feeding did not result in significant kernel necrosis compared to controls in any variety,plant raspberry in container but L. zonatus had higher levels of kernel necrosis than controls in Monterey and Carmel; in 2015, kernel necrosis was consistently higher in L. zonatus cages than in controls. In 2014, the percent of shriveled kernels at harvest did not vary between the controls and the L. clypealis cages in any variety. However, the percent of shriveled kernels was higher in L. zonatus cages than controls in two varieties, Monterey and Carmel, while in 2015, the cages with L. zonatus resulted in higher levels of shriveled kernels in Nonpareil and Monterey. Research has similarly found that insect feeding damage varies among almond varieties as well as in varieties of other crops such as in apple, blueberry and olives. Hull strikes that are characterized by a spot on the external portion of the almond could correspond directly to internal damage such as nut strikes or almond damage. The number of external hull strikes was similar to the number of internal nut strikes and damaged nuts for L clypealis. However, for L. zonatus in both years, the number of hull strikes recorded was often lower than the number of nut strikes or damaged nuts. Hull strikes could be used as a proxy to estimate the number of almonds with internal damage such as nut strikes or kernel necrosis which might later be unsellable . Evidence of hemipteran probing and feeding has been used as a proxy for feeding damage in other systems. Nut strikes are expected to occur due to feeding injury from sucking insects where insects probe their mouth parts into fruits during feeding.

In 2014, nut strikes on the four varieties due to L. clypealis was an average of 15%, while nut strikes from L. zonatus averaged 24.75%; in 2015, L. zonatus similarly had higher numbers of nut strikes than in controls. In contrast to the relationship found between hull strikes and other kernel damage from Leptoglossus feeding, in other crops, the presence of holes, spots, or mouth part stylet sheaths on a fruit has not always been found to translate directly into fruit damage. For example, Wiman et al. reported that in blueberry, external fruit probing by Halyomorpha halys indicated by a high numbers of stylet sheaths had very little internal damage as measured necrosis and discoloration. However, in apples, the punctures by the mullein bug were related to internal damage, which is more similar to what was observed in this study. Interestingly, some kernel necrosis was observed in control cages of all the varieties in both years. In 2014, the controls in each variety had few or no almonds with hull strikes yet had some level of kernel necrosis. A similar pattern was observed in 2015 as well. In cages with feeding by Leptoglossus there was a higher level of kernel necrosis than in controls. It should be noted that Leptoglossus feeding does not account for the kernel necrosis observed in the controls, but perhaps another agent such as a pathogen could be responsible. Studies such as the one herein with caged insects help to determine the damage symptoms which can be attributed to insect feeding. Similarly, a study of pistachios used caged bugs to determine which damage symptoms could be attributed to feeding. Pathogens may be responsible for a percentage of kernel necrosis observed in controls in this study, but this would need to be investigated. The final damage parameter, shriveled kernels, was also observed in all the controls, similar to the pattern observed for kernel necrosis. It should again be noted that this is a natural type of damage which occurs in the crop, and it is not only induced by feeding of L. clypealis and L. zonatus. However, in L. zonatus cages, two varieties had levels of shriveled kernels which exceeded the controls. Drosophila suzukii, also known as the spotted wing drosophila , is a vinegar fly originating from Southeast Asia. SWD was first detected in North America in August 2008 in Santa Cruz County, California, where it was observed infesting strawberries and caneberries.1,2 In 2009, SWD was detected in Washington, Oregon, and Florida. By 2010, SWD was detected in Utah, Mississippi, North Carolina, South Carolina, Wisconsin, and Michigan in the United States, and Alberta, Manitoba, Ontario, and Quebec in Canada.Recent trapping indicates that SWD can be found in virtually any region of North America where host fruit are available. A coincidental invasion of SWD with a genetically distinct population has also been observed in Europe, with initial detections in both Spain and Italy in 2008, followed by its spread throughout the continent.In North America, SWD is primarily a pest of berries and cherries. In Europe, it is reported to also damage a number of stone fruits and grapes. Unlike native vinegar flies in North America and Europe, female SWD possess a serrated ovipositor that can pierce the skin of healthy, soft-skinned fruits to lay eggs. These eggs quickly develop into larvae, which consume the fruit and render it unmarketable. The only other Drosophila species known to oviposit in sound, marketable fruit is Drosophila pulchrella Tan. This species is native to Japan.1 Growers have attempted to mitigate crop damage risk by applying additional insecticide, harvesting more frequently, performing field sanitation, and implementing trapping programs to detect SWD populations. These management practices are costly and many growers still face significant yield losses from SWD infestations.Raspberry producers are perhaps the most affected by SWD’s invasion among California commodities, although producers of blueberries and cherries have experienced substantial losses too. Strawberry producers have experienced lower damage rates and primarily on the lower-value fruit produced for processing.

We developed a Bayesian framework that permitted quantitative integration of borehole flow meter data and cross hole geophysical information for estimating the hydraulic conductivity distribution at each pixel along the tomographic cross sections. Figure 2 illustrates the estimates of hydraulic conductivity along two vertical cross sections at the Oyster site, obtained using the Bayesian estimation framework and radar velocity tomograms. Hydraulic conductivity data from an electromagnetic borehole flow meter log are superimposed on top of the estimates obtained using radar tomographic data within the Bayesian framework. Comparison of the estimated hydraulic conductivity field and tracer breakthrough data suggested that the tomographic estimates were extremely useful for helping to reduce the ambiguity associated with interpreting bacterial and chemical transport data collected during tracer tests. Even though this site was fairly homogeneous and it had extensive borehole control ,planting blueberries in a pot it was difficult to capture the variability of hydraulic conductivity using borehole data alone sufficiently to ensure reliable transport predictions.

By comparing numerical model predictions with tracer test measurements at the Oyster Site, Scheibe and Chien found that conditioning the models to the geophysical estimates of hydraulic conductivity significantly improved the accuracy and precision of the model predictions relative to those obtained using borehole data alone. This study suggested that the geophysical based methods provided information at a reasonable scale and resolution for understanding field-scale processes. This is an important point, as it is often difficult to scale the information gained at the laboratory scale or even from discrete well bore samples for use at the remediation field scale.In addition to the importance of hydrogeological heterogeneity in controlling contaminant and bacterial transport, geochemical heterogeneity plays a large role in reactive flow and transport. In the same general area as the study discussed above, we used crosshole ground penetrating radar amplitude data to estimate lithology and sediment Fe and Fe. In this study, we developed a sampling-based Bayesian approach to fuse the diverse geochemical, lithological, and geophysical datasets into an integrated interpretation. The geophysical data do not sense the geochemical parameters directly, but the geophysical attribute is sensitive to lithology, which is in turn sensitive to sediment geochemistry.

Our developed estimation approach exploited this mutual dependence to estimate lithology and sediment geochemical parameters using geophysical data. Figure 3a illustrates the 2-D geophysical attribute field obtained from inversion of GPR amplitude data. Figures 3b-3d illustrate the mean values of the estimated Fe and Fe distributions; variances associated with these estimates are available but are not shown in the figure. Cross-validation exercises revealed that the estimates obtained using the geophysical data were accurate and greatly improved the 2-D identification of the geological and geochemical properties. This study represents perhaps the highest resolution field-scale characterization of geochemical properties performed todate. Although geophysical methods have been used to estimate hydrological parameter probability density functions with very high resolution , this level of detail may not always be necessary to adequately describe the controls on transport. Many studies suggest that spatial variations of lithological changes tend to be closely correlated with hydrological parameters and with geochemical parameters. As such, if an understanding of the relationships between lithofacies, hydrological and geochemical parameters is available, field-scale mapping of lithofacies may provide sufficient information about the controls on transport over large spatial scales. Figure 4 illustrates how geophysical methods have been used with sparse hydrological data and with stochastic estimation techniques to estimate the probability of being within hydraulically important units.

The top image illustrates the probability of being within a transmissive fracture zone at the NABIR Field Research Center at the Oak Ridge National Laboratory in Tennessee obtained using seismic velocity tomographic and flow meter data within a Monte Carlo markov Chain approach. This fracture zone is the ongoing focus of a Uranium bio-stimulation experiment at this site . The middle image shows the probably of being within a sandy lense at the Hanford 100H site in WA, and was obtained using seismic and radar tomographic data and a discriminant analysis technique. Finally, the lower figure illustrates the probability of being within a sandy lithofacies at the DOE Bacterial Transport Site in Oyster, VA , which was estimated using radar velocity data within a Bayesian estimation approach.Remediation approaches, such as in situ chemical manipulation and bio-stimulation, often induce dynamic spatiotemporal transformations in subsurface systems, such as the dissolution and precipitation of minerals, gas evolution, redox variations, biofilm generation, and changes in permeability and porosity. The limited understanding of bio-geochemical-hydrological processes and the inadequacy of conventional approaches for characterizing or monitoring these processes hinders our ability to guide contamination remediation. We have investigated the capability of time-lapse geophysical datasets for remotely detecting changes in hydrological-biogeochemical properties during bio-stimulation at both the laboratory and the field scale. Using column-scale experiments, we have tested the sensitivity of different geophysical methods to reaction products that occur during bio-stimulation, such as gasses, precipitates and biofilms during nitrate and sulfate reduction. As a consequence of the greater energy available from nitrate reduction, a majority of nitrate in a groundwater system is reduced prior to reduction of the less energetic manganese, iron, and sulfate. Thus, the onset of denitrification is an important indicator for determining the redox state of the aquifer that is being perturbed, and advanced techniques to detect this onset and monitor associated processes in a remote and accurate manner are needed. We conducted laboratory based experiments to investigate the sensitivity of radar attributes for detecting N2 gas generated during denitrification as the gas replaces the original pore water. The key steps in the experimental design included packing and inoculating sand columns with Acidovorax sp. , providing nutrients to the microbes to stimulate denitrification, and measuring the hydraulic and geophysical responses during the bio-stimulation experiment.

TDR measurements were made along the length of the column and over time to estimate the spatiotemporal variations in dielectric constant during the stimulation experiment. We used a volumetric averaging/mixing model to represent the effective dielectric measurement as a function the individual components that contribute to the measurement,raspberries in pots including the dielectric constants of N2 , of water, and of the sand grains. Figure 5 illustrates the estimated percent of the pore space that was filled by N2 gas as a function of time after the bio-stimulation experiment began for three different TDR measurement locations. This figure illustrates how the pore water started to be significantly replaced by gas after about thirteen days. Gas was first detected by probe #1, or the top probe in the column. The apparent ‘jumps’ in the estimated evolved N2 gas are associated with the pressure release procedure. With time, all of the probes sensed the presence of a significant volume of gas. At the end of the experiment, we estimated that approximately 22% of the pore spaces were filled with N2 gas for the bottom third of the column, about 21% of the pore spaces were filled with gas for the middle third of the column, and that 31% of the pore spaces were filled with N2 gas at the top third of the column, yielding an average estimated gas saturation over the entire column of 24.6%. The experiment suggested that the radar velocity may be a good indicator of the onset and extent of denitrification that occurs during bio-stimulation. Our laboratory and field-scale experiments have also indicated that the geophysical methods hold good potential for detecting some amendments as they are introduced into an aquifer and as they distribute over time. We have conducted geophysical imaging in support of a Cr bio-remediation effort that is being performed at the 100H Site at the Hanford Reservation in Hanford. Here, HRC, which is a slow-release polylactate was injected into a sandy portion of a saturated aquifer to reduce and immobilize Cr. Field tomographic data were collected before and after HRC injection. Figure 6 illustrates some of the field-estimates obtained using radar and seismictomographic data at the site. The top image in Figure 6 illustrates the hydraulic conductivity zonation in the stimulation zone, obtained using a statistical approach with radar and seismic tomographic data together with borehole flow meter data. Although the entire section is characterized as being ‘sandy’ using conventional data, there are areas within the section that are more permeable . The subsequent images in Figure 6 show the changes in electrical conductivity as a function of time after HRC was injected into the aquifer, obtained using radar amplitude and velocity information following Peterson.

We find that the HRC, which is electrically conductivity upon injection due to the release of lactic acid when mixed with the groundwater, originally distributes near the injection area. However, very soon after injection , the lactic acid redistributes itself into the higher hydraulic conductivity section, and migrates down gradient. After 9 days, the change in the electrical response due to the lactate injection is minimal compared to the change in the conductivity associated with the metals precipitation around the HRC reaction front . The bottom image in Figure 6 shows that the seismic energy is completely attenuated in the vicinity of the HRC. These images illustrate the utility of high-resolution geophysical methods for imaging the amendment location and redistribution as a function of heterogeneity. The geophysical responses to HRC that we observed at the field scale were similar to the responses observed in the laboratory.In 2007, 311 million kg of pesticide active ingredients were used in agriculture in the United States . California, the state with the largest agricultural output, uses 25% of all U.S. agricultural pesticides, or 84.5 million kg annually. Although recent studies have demonstrated widespread organophosphate pesticide exposures in the general U.S. population, including pregnant women and children, exposures are often higher in agricultural populations . Among pregnant women in the Center for the Health Assessment of Mothers and Children of Salinas study, all of whom lived in an agricultural region, and many of whom either worked in agriculture or lived with people who did, OP urinary metabolites or dialkylphosphate levels were ∼40% higher than those in a representative sample of U.S. women of childbearing age . We observed adverse associations in the CHAMACOS study between prenatal maternal DAP concentrations and children’s performance on the Bayley Scales of Infant Development at 2 y , measures of attention at 5 y , and on the Wechsler Intelligence Scale for Children at 7 y . Several studies in other populations have similarly reported adverse associations of prenatal exposure to OP pesticides and child neurodevelopment , but few studies have examined the effects of other potentially neurotoxic pesticides on child cognitive development. Populations residing in agricultural areas may be exposed to a complex mixture of neurotoxic pesticides through pesticide drift and para-occupational exposures . Some of these pesticide classes—including OPs as well as carbamates— share atleast one mode of action, depression of acetylcholinesterase , and there isin vitro evidence that there may be additive inhibitory effects from exposure to certain pesticide mixtures . Furthermore, although biomarkers such as DAP metabolites are an important tool for assessing exposures to pesticides, several challenges limit the utility of pesticide biomarkers in epidemiologic analyses. For example, many pesticides have a short halflife in the body, and biomarkers reflect only very recent exposures . In addition, no biomarkers are available for some pesticides, leaving only environmental concentrations or modeling to characterize exposure. Since 1990, all agricultural pesticide applications in California have been compiled in the uniquely comprehensive Pesticide Use Reporting database. In several studies, PUR data have been shown to correlate with pesticide levels in various media. For example, we have shown significant associations between nearby use of specific pesticides based on the PUR data and levels in house dust , and moderate to strong associations between agricultural use of malathion, chlorpyrifos, and diazinon with community air samples . In addition, several epidemiologic studies conducted in California have shown that higher nearby agricultural pesticide use is associated with various adverse health outcomes, including OP and fungicide use with Parkinson disease , OP and pyrethroid use with autism and birthdeffects , organochlorine pesticide use with autism , and the use of carbamates and the neonicotinoid imidacloprid with neural tube deffects in children .

Recently, however, reports regarding the financial difficulties experienced by U.S. agricultural cooperatives have been much more common than news of their successes. In particular, the 2002 bankruptcy of Farmland Industries — a federation of 1,700 independent Midwestern cooperatives and the nation’s largest agricultural cooperative — received considerable media attention. In California, news about cooperatives has centered on the bankruptcy of Tri Valley Growers in 2000; the dissolutions of Blue Anchor and the Rice Growers Association of California in 2000; and the conversions of Calavo in 2001 and Diamond Walnut Growers in 2005, to publicly traded, investor-owned corporations. Such news has raised concerns among producers and lenders regarding the viability of the cooperative form of agricultural business. In the agricultural sector, producers use cooperatives to market and process their crops and livestock, purchase supplies and services, negotiate terms of trade with processors of their raw product, and provide credit for their operations. An international management consulting firm, McKinsey & Company,plastic gutter issued a report in 2002 alleging that agricultural cooperatives “destroy value” because few cooperatives “have changed the way they operate” .

This report received considerable attention from the management and boards of numerous large cooperatives, despite the fact that its analysis was based on only 2 years of data. Some cooperative researchers also noted other technical limitations. Was McKinsey & Company’s claim that agricultural cooperatives destroy value justified? Or do cooperatives benefit California’s agricultural producers? What is the future for agricultural cooperatives in California? Cooperatives have been part of the agricultural sector in the United States for approximately 200 years. They can benefit their members in several different ways. In the Midwest, cooperatives were formed primarily to maximize the welfare of their individual members. These cooperatives handle the entire output of their members regardless of market needs, and are clearly extensions of their members’ farming businesses. Conversely, many of the marketing cooperatives formed in California during the first quarter of the 20th century were designed to create market power by improving product quality and restricting raw product flows. Such market power–oriented cooperatives seek to maximize the profitability of the firm, rather than the welfare of individual members. These different objectives can have vastly different impacts on the operations of cooperatives. A cooperative with a market-power structure could operate in niche markets with a strong brand identity and handle limited volumes of member product to maximize its profitability as a firm. This type of cooperative would then distribute some or all of its earnings to its members. Some of these cooperatives, such as Mountain States Lamb, require members to buy enough delivery rights to match their delivery volumes.

Members must invest in a delivery right for each lamb they deliver annually to Mountain States Lamb for processing and marketing. The delivery rights control the amount of raw product delivered by members; they depend on the processing capacity of the cooperative’s plant. Investment in delivery rights is part of a producer marketing agreement. If a producer is unable to deliver the agreed amount of raw product, purchase of commodities is authorized by the cooperative for undelivered obligations. Such delivery rights are marketable and can appreciate in value if the cooperative is successful. For example, the founding members of Dakota Growers Pasta paid $3.85 in 1991 for a right to deliver a bushel of durum wheat annually to the cooperative. By 1998, the cooperative’s strong earnings enabled retiring members to sell a delivery right for $7.50. In contrast, a Midwestern-style marketing cooperative could maximize benefits to its members by accepting their deliveries up to its break-even point, which would provide as much of a home for their product as possible without incurring losses. While this decreases the members’ potential earnings from the cooperative, it also reduces the risk they face. It is inappropriate to assume that all cooperatives are seeking to maximize their profitability as firms. Nonetheless, various national studies were conducted during the late 1980s that compared the financial performance of agricultural cooperatives and investor-owned firms . The findings from these studies varied widely . These financial performance studies used ratio analysis, including profitability measures. Ratio analysis is a tool used to evaluate a firm’s financial performance by taking data from its financial statements and comparing the ratios over time, and/or with those for other firms or the industry. However, Sexton and Iskow pointed out how analyses of cooperatives based upon financial ratios, although popular, were not based on economic theory. Specifically, they noted that since cooperatives are extensions of their members’ businesses, a cooperative could be less profitable than an investor-owned firm and still be beneficial to a member — as long as the member’s discounted stream of returns from the cooperative was greater than those from marketing the commodity directly or through an investor-owned firm.

For example, membership in an almond marketing cooperative that is averaging a 6% operating margin while one of its investor-owned competitors is averaging a 10% operating margin could still be beneficial to the cooperative’s members. Members could receive a higher price for their almonds from the cooperative than if they sold their crop to the investor-owned firm; the investor-owned firm strives to minimize its costs, including the price it pays for its almonds. John Hicks is credited with advancing the conjecture that changes in relative prices induce technical progress . This conjecture implies that relative factor prices serve a dual function, as signals of resource scarcity and as determinants of the firm’s technology choice. Hayami and Ruttan revitalized Hicks’ conjecture and made important contributions to the explanation of the magnitude and direction of TP in the American and Japanese agricultural sectors using the relative price hypothesis. Over the past thirty years, many authors have attempted to test this hypothesis using aggregate data and obtaining mixed results. In these studies, the consensus approach to the econometric estimation and testing of the hypothesis that technical progress is induced by relative prices has been to regress the ratio of some factors of production over a distributed lag series of their price ratios and other similar series of extension,blueberry container public and private R&D expenditures. Thirtle, Schimmelpfennig and Townsend summarized several significant studies of this kind and produced one of their own. The sample information about output quantity and output price is remarkably absent in many of these studies. This omission seems in contrast to the conjecture advanced by several economists according to whom the choice of techniques is determined, to a large extent, by profitability considerations. In this paper, therefore, we attempt to recast the price-induced technical progress hypothesis into a framework that utilizes all the available theoretical and sample information, including output price and quantity. This approach leads to a novel set of comparative statics conditions of the economic theory of the firm undergoing technical progress that provides an exhaustive scaffolding for testing the PITP conjecture.When dealing with technical progress, it is convenient to distinguish the innovation phase from the adoption phase. The majority of price-taker firms self select into the adoption phase. In general, the choice of available techniques made by those firms is guided mainly by expected profitability considerations. When price-taker firms are aggregated into an industry, such as the US agricultural sector, the R&D and extension expenditures may become determinants of the industry technical progress. Griliches , Arrow , Hirsch and other economists have suggested that expected profitability objectives may be a determinant of adoption rates. The expected profitability conjecture relating expected profits to TP leads to a model where expected output and input prices enter the production function as shifters of the technology frontier. As originally suggested by Paris and re-elaborated more recently by Paris and Caputo and by Caputo and Paris , we incorporate expected relative factor prices explicitly into the production function and assume a cost-minimizing behavior of the individual entrepreneur.

The introduction of expected relative prices into the production function invalidates the traditional comparative statics relations of the competitive firms but leads—by necessity—to a more general model of the cost-minimizing/profit-maximizing entrepreneur. The novel set of comparative statics conditions depends on both primal and dual relations and is expressed in the form of a symmetric and negative semidefinite matrix of estimable terms. It follows that the empirical implementation of the PITP conjecture developed in this paper requires the joint estimation of the derivatives of the cost function with respect to relative input prices, the production function and the first order necessary conditions.Traditionally, aggregate models of TP based upon time series data have been specified using a distributed lag representation of either quantities or prices, or both. This approach seems to have been taken for two main reasons: to capture, somehow, a dynamic aspect that is assumed to be inherent in a process of technical progress, and to represent some process of expectation formation of the entrepreneur about quantities and prices. Often, the two aspects are confounded. With respect to the PITP model presented above, we would like to point out that the expectation process is taken into consideration explicitly and there is no need to formulate a distributed lag representation of expected quantities and prices. We acknowledge that the dynamic aspect of TP requires an explicit theory, akin to the static theory formulated above: a distributed lag specification without theory is only an ad-hockery. In general, it will be wise to postulate that the theoretical relations expressed in equations – are represented by flexible functional forms. Such forms are not self-dual in the way that the Cobb-Douglas and the CES functions are. Hence, the implementation of the above model requires the statement of a cost function that has entirely different parameters from those of the production function. The coherent link between the primal and the dual frameworks is represented by the unknown expected quantities and prices that must be estimated along with the parameters. The discussion of how to estimate the model given by equations – will be the subject of the following sections. We would like to advance here that, in principle, a Bayesian approach along the lines presented by Zellner would produce consistent estimates. But, as we are not comfortable with elaborate and multi-dimensional integration techniques, we will propose a two-phase approach based upon a nonlinear least-squares estimator.The sample input data for the present analysis were made available by Thirtle, Schimmelpfennig and Townsend and are described in their paper. The time series consist of four input quantity and price indices relating to machinery, labor, fertilizer and land, from 1880 to 1990; public and private R&D and extension expenditures are also from 1880 to 1990. Additionally, aggregate output quantity and price indices from 1910 to 1990 were derived from the US Historical Statistics and USDA databases and provided by Spiro Stefanou. All the index series are defined with base 1967 = 100. Because the primal-dual model of PITP developed in this paper uses also the output quantity and price series, the usable sample data range from 1910 to 1990 with 81 observations. In this paper we chose to deal with the single aggregate of output for the US agriculture. All the data were scaled by a factor of 100 so that the average of most series is close to 1.Phase I of the PITP model was estimated using the GAMS programming package and unitary € λ weights for the objective function . This choice was dictated by a lack of knowledge of the true weights. The selection of these weights transforms the given problem into a nonlinear Total Least Squares model, originally described by Gulob and Van Loan , and by a vast literature since then. The model constraints, represented by equations , and , are highly nonlinear and non-convex. Hence, the solution achieved is only locally optimal. The problem was solved several times with different initial values. A serial correlation of order 1 was implemented during the estimation procedure. The use of the GAMS 21.6 programming package requires a careful choice of upper and lower bounds for all parameters. Still, the solution of the problem is a non-trivial enterprise. The phase I PITP model has 1495 constraints and 1721 unknown parameters. In a typical run, the CPU time to achieve a locally optimal solution was about 20-30 minutes on a Supermicro machine .

Similar regressions have been reported by Belongia and by Grennes and Lapp, and each study supported neutrality of money growth after intervals of one year or less. Using annual data, Grennes and Lapp found that, once real demand and supply forces were accounted for, there appeared to be no effect of inflation on real agricultural prices. Quarterly data were used by Belongia to test the money neutrality hypothesis. He found that the difference in growth rates between the GNP deflator for farm products and that for industrial commodities was not affected by unanticipated money growth after two quarters.The agricultural sector is specified as a series of supply and demand equalions with market prices playing the key equilibrating role. The agricultural sector is composed of two blocks of crop equations and three blocks of livestock equations. As shown in Figure 1, these blocks are related to the international and macroeconomy sectors-through a number of linkages. These consist of variables from the non-agricultural components of the model, such as interest and exchange rates,greenhouse snap clamps that affect the agricultural sector. A more general treatment of the linkages between the sectors incorporates feedback effects as well.

These were not included in the simulation results reported in this paper, so the agricultural sector can be thought of as a satellite model. Each grain block includes behavioral equations for acreage planted, yield per planted acre, domestic utilization, and inventories. Production is computed as the product of acreage and yield. Domestic utilization is divided into two components: livestock and residual demand and industry or food demand. Inventories are either publicly controlled loans, and stocks in the farmer-owned reserve or, privately owned. The privately held stocks and inventories under CCC loans are aggregated into a single inventory position. This specification allows different rules governing the movement of the various types of stocks to be incorporated in policy experiments. Since the planting decision is tied to the discrete choice of participation in farm programs, an appropriate specification must incorporate the trade-oft between expected returns of all potential crop choices. Traditional acreage response equations included in past models do not fully incorporate these trade-offs. Acreage planted of each crop is presumed to depend on expected returns from noncompliance and compliance with acreage programs for the crop under consideration, the expected profitabilities form competing crops, and last years’ acreage planted. The final variable is included since acreage planted is modeled as a partial adjustment process. Crop production costs depend on inputs purchased from the non-farm sector.

Costs are a function of the wage rate paid for hired labor; the market interest rate paid for financing working _capital, machinery, and buildings; prices paid for energy and fertilizer; and an index of nonfood prices. This cost measure enters the expected profit calculations for wheat and feed grains and provides a direct link with conditions in the general economy. When farmers do not participate in government programs, profitability depends, among other variables. on anticipated output price. For estimation purposes, the expected output price was taken to be the iarch price for a September futures contract. For simulation purposes, these price expectations .I were assumed to be rational, and the March futures price used in the acreage and yield equations was set equal to the cash price observed in the third quarter of the simulation. Thus, the price “expectations” used in the simulations are those which bring forth a level of production just sufficient to create market conditions consistent with that price, and the need to simulate the relationship between cash and futures prices is avoided. Domestic consumption is divided into food consumption and feed and other uses with separate demand equations for each component. Since most wheat , that is fed goes to broilers, the feed demand for wheat is specified to be a function of own price and corn price, each relative to the price of broilers, and the number of broilers on feed. Domestic feed demand for feed grains is specified to be a function of the inventories of cattle on feed, pigs on feed, broilers on feed and the price of grains relative to the price of meat. As suggested by the theory of consumption, domestic per capita food demand for wheat is a function of the real price of wheat, an index of real food prices, and real per capita income.

Food and industrial use of feed grains is modeled as a function of real feed grain prices, ” trend variable representing technology and real income. Inventory equations are used to·complete the grains blocks and determine the price of each crop. As noted above, inventories are separated into three components. In general a measure of the expected profitability of holding stocks is the main determinant of private stock holding. The different specifications for the various public inventory positions reflect constraints imposed on relase and entry in the publicly controlled stocks and by other causal influences. Quantity demanded by the private sector for stocks by both producers and users is motivated by transactions and precautionary motives. A large part is also due to the seasonality of production and to speculative motives. Specula active demand is influenced by the farm price relative to expected farm price. It is also presumed that the difference between the farm price and the loan rate, and public stocks have an influence. The market stock equation was modeled in price-dependent form. Interest rates enter the stock holding equations in two ways– the real interest rate and the government interest rate subsidy are both included as explanatory variables. In the private stock equations, it is expected that increased interest rates should have a negative effect due to the increased opportunity cost of holding idle inventories. As real interest rates rise, prices of wheat and feed grains fall since the opportunity costs of holding grain inventories has increased. Demand for stocks from the private sector is modeled in price dependent form. Stocks demanded by the government sector include government-owned stocks and the farmer-owned reserve. To a large extent, government stocks are a residual with the government playing a passive role. Farmers place stocks with the government when the farm price is close to or below the loan price by defaulting on non-recourse loans. They redeem loans only as the farm price moves above the loan price. A:5 required by law, the government can only release its own stocks when prices are sut efficiently above the loan price. In the case of the farmer-owned reserve, stocks flow out whenever market price approaches or exceeds the release price. The livestock sector includes blocks of equations for beef, pork and broilers. The structure of each block in the meat sector is similar. The meats are disaggregated to reflect different consumption patterns over time,snap clamps for greenhouse different income elasticities, and different production processes . Per capita meat demand is modeled in price-dependent form as a function of own quantity, the price of substitute meats, income, and the price of 1 nonfood items. Prices and income are measured in constant dollars, and income is in per capita terms. Supply behavior in the cattle sector is disaggregated into equations explaining the closing inventory of cows, placements of cattle on feed, and production of beef. The cattle sector is disaggregated and the dynamics associated with biological production lags and interactions between beef, feed prices and interest costs are incorporated. Our model follows that described by Jarvis; Freebairn and Rausser; and by Arzac a.nd Wilkinson except that, for simplicity, we have only one beef price. The cattle breeder and fed cattle activities are treated as distinct operations with different decision makers. Because of the biological lags involved, a change in the current cow inventory reflects a history of decisions to retain or slaughter cows and sell heifers to feeder operators or retain them for breeding over a period of three years. These decisions are related to current and past beef prices relative to feed costs and current and past real interest rates .Placement of cattle on feed is expressed as a function of lagged cow inventories to reflect the availability of feeder calves and the expected profitability of cattle feeding. Profitability is influenced by the price of beef relative to feed costs.

Feed costs for beef cows depend on the cost of feed grains, measured by the farm price of corn. Production of beef comes from gross number of placements of cattle on feed in previous periods, cull cows, and other nonfed cattle slaughter. Cull cows and other nonfed slaughter are modeled as the change in lagged cow inventories. The price of beef and the feed cost for beef may have two effects. In the short term, they encourage feeding of animals to heavier weights and withholding of heifers to increase the breeding stock. This gives rise to a negatively sloped short-run supply curve. In the longer term, the supply curve will be upward sloping as placements on feed,from the higher breding inventories increase. As with the cattle sector, the representation of the hog sector is highly aggregated. It allows for cyclical responses of pork production to changes in the final product price and costs. On the supply side. equations are given for the closing inventory of breeding sows, pig crop and production of pork. As with beef, the decision to retain breeding sows or send them for slaughter represents a series of decisions to retain or slaughter breeding sows and to feed pigs for slaughter or retain them to add to’ the breeding stock. At each period, these decisions are based on a comparison of the current value of pork to the expected returns from the sale of hogs in the future. The closing inventory of breeding sows is positively related to the price of hogs. negatively related to feed costs, and negatively related to the interest cost of holding inventories. The pig crop is a function of lagged breeding hog inventory and anticipated profitability from producing pork. Production of pork depends on previous pig crops and on liquidation of breeding inventories, which is measured by the previous period’s change in the breeding inventory of hogs.Production of broilers is modeled similarly to the beef and pork sub-components. Equations with the same type of causal influences are specified for poultry production, broiler chicks hatched, and broiler hatchery supply flocks. Real interest rates enter the livestock equations as a measure of the opportunity cost of holding livestock inventories. An increase in real interest rates tends to decrease current breeding inventories. increase current slaughter and production of meat, and push prices down. The longer run effects of an increase in the real interest rate will be an increase in meat prices due to smaller herds. As is apparent from the discussion above, macroeconomic variables are incorporated into the agricultural sector in a number of places. Income and prices of nonfood items affect food demand. interest rates affect the willingness to hold stocks of either crops or livestock. and the exchange rate and rest-of world prices and income affect the exports of feed grains and wheat from the U.S. We turn now to the simulation results to examine the extent to which variations in these macroeconomic variables induced by monetary policy affects variables in the agricultural sector.The ad hoc regressions reported earlier provided some evidence concerning the effect of money growth on the rate of change of food and nonfood prices. However. this approach reveals nothing about the effects on real incomes m the agricultural sector, since agricultural output was not included and there is no evidence concerning consumption, inventory behavior, and exports. Enders and Falk and Huffman and Langley have estimated similar regressions with growth in output as dependent variables, focusing on whether unanticipated money growth has output effects. While this method does add some information to the price change regressions, it is still not amenable to policy analysis. To investigate the effect of monetary policy on agricultural sector prices. quantities. and incomes, as well as to indicate its effects on government outlays for the feed grains and wheat programs. w~ used estimated equations for the above model using data through 1983. The starting point of the sample used for estimation varied with the stability of the equation over time and also depended on whether the dependent variable was quarterly or annual. but no sample data from before the 1960s were used.

Similarly, SO2 or H2S gas modified agricultural wastes bio-chars produced -C=S and -S-S groups, which formed strong complexes with Cd2+ and Hg2+ . Depending on experimental conditions, methods to introduce S-containing functional groups can either increase or decrease specific surface area and pore volume of carbonaceous adsorbents ; however, any reduction in sorption capacity associated with the loss of surface area and porosity is generally ofset by the increased S-containing functional groups. Sulfur-functional groups also interact with other functional group types in synergist adsorption mechanisms. When -COO-, −NH and -C-S were co-introduced to the surface of sugarcane bagasse during modification procedures, these groups interacted to retain metals through ion exchange and complexation reactions . The interactions among these functional groups greatly improved the overall sorption capacity for many environmental pollutants.While O-, N- and S-containing functional groups are the predominant reactive groups controlling adsorption performance, other functional groups may also enhance the adsorption performance of agricultural waste products . Most of the -C=C groups exist in benzene rings and react with pollutants through π-π interactions. Aniline addition modification enhanced the -C=C content of corn stalk and strengthened π-π interactions betweenadsorbent and adsorbates,plant pot with drainage thereby increasing the adsorption capacity for acid red and acid orange dyes .

Fe-containing functional groups are typically introduced onto agricultural waste materials to prepare magnetic adsorbents, especially in the preparation of bio-char. Doping with magnetic materials creates an adsorbent that can be easily separated from solution to remove bio-char-bound pollutants. These Fe oxides were highly efficient for the removal of As3+ and As5+ through specific sorption reactions . Additionally, Fe3O4 reacts with H2O creating a polar structure that can retain pollutants by hydrogen bonding. P-containing functional groups are generated on adsorbents by H3PO4 modification and are capable of retaining pollutants primarily by ion exchange mechanisms. Tang et al. demonstrated the presence of a large number of -P-O functional groups on corn stalks after H3PO4 treatment. The -P-O group was effective in retention of methylene blue through ion exchange. Additionally, the -P-O group efficiently retained U6+ from solution via ion exchange . Adsorption of uranium changed the morphology and the structural characteristics by decreasing the distributed interstices, voids and crystal structure in the surface of the modified rice stem through interaction with -P-O.Adsorption mechanisms are primarily afected by specific surface area, pore volume/connectivity and the amount/type of surface functional groups. Physical adsorption takes place by weak Van der Waals’ attraction forces and H-bonding, whereas chemisorption occurs through stronger chemical bonding between adsorbates and adsorbents. Chemisorption generally plays a more prominent role in pollutant removal from aqueous solution than physisorption for modified agricultural adsorbents . Notably, although no functional groups or chemical bonds take part in the fixation of pollutants during the precipitation process, chemical reaction occurs during the formation of the solid products casused by the adsorbents.

The retention of pollutants through precipitation is still a chemisorption process. Many O-, N- and S-containing functional groups are suitable for the removal of cationic pollutants, whereas O- and N-containing groups are more suitable for adsorption of anionic pollutants. Fe- and S-containing functional groups often coexist with modified adsorbents surface and were used to binding divalent cationic heavy metals via complexation . Moreover, chemical precipitation usually occurred as well for the pollutants retention due to the formation of stable crystal structures. Complexation and ion exchange are the main adsorption mechanisms for O-containing groups , whereas N- and S-containing functional groups interact with pollutants primarily through complexation . Studies involving modifications to increase O- and N-functionality of agricultural wastes are much more common than those addressing enhancement of S-functionality, due to the prominence of O- and N-functional groups and their higher adsorption affinity compared to S-functional groups, especially for anionic pollutants. The main mechanisms for pollutant interactions with modified agricultural wastes are portrayed in Fig. 3. Complexation and ion exchange are often the most important adsorption mechanisms for interactions between functional groups and various pollutants. These chelate-forming or electron-donating functional groups readily react with pollutants to form complexes. Electrostatic attraction is a prominent adsorption process, especially under acidic or alkaline conditions where dissociation/ionization of functional groups initiates interaction with oppositely charged pollutant compounds. For carbonization-treated agricultural wastes, π-π interactions with organic pollutants and alkaline precipitation mechanisms are improved due to the increased C=C content and high alkalinity after modification . Moreover, carbonization generally increases the specific surface area of the modified materials, which favors physical adsorption , H-bonding and van der Waals’ attraction.

Given the multi-functionality of most modified adsorbents, the overall adsorption process will involve a combination of several mechanisms.Cost is an important consideration when selecting an agricultural waste and modification treatment. Currently, few studies have assessed cost estimates of modified adsorbent, thereby limiting an evaluation of material and processing costs. A few studies demonstrated that modified agricultural wastes showed a good price advantage compared with commercial adsorbents. For example, the cost of citric acid modified sugarcane bagasse was 4.76 $ kg−1 , much lower than commercial activated carbon . Further, Kannan and Sundaram determined that the price of carbonised adsorbents prepared from rice husk or straw was ~5 times cheaper than commercial activated carbon. In addition, some modified adsorbent materials exhibited excellent pollutant removal efficiency over at least three reaction/ recovery cycles , allowing for reuse potential that further reduces their lifetime costs. Moreover, many feedstocks for bio-adsorbents originate from agricultural wastes that would otherwise be discarded. Hence, the reuse of these solid waste materials is beneficial for utilization of waste materials as well as reducing waste disposal costs, which is often a more substantial cost than the modification costs. Other studies demonstrated that bio-char preparation could generate energy , thereby of setting production costs partly . Based on the available studies, almost all cost-benefit analyses indicated that agricultural waste modification provides a low-cost option for preparation of bio-adsorbents for environmental remediation. Most studies of bio-adsorbent preparation were limited to laboratory evaluations of synthesis costs, which do not account for several associated costs. Te costs of raw materials, transportation, modification chemicals and energy are the main factors determining the final preparation cost. Many of these costs are site and time specific making it difficult to produce a universal cost estimate . For example, Salam et al. calculated that the total cost of HCl-modified peanut husk was L.E. 5000 t −1 , a factor of two lower than commercial activated carbon at that time. Additionally, bioadsorbents will have variable efficiencies for retention of a given pollutant, wherein a higher cost,pot with drainage holes but higher efficiency product will actually have a lower application cost per unit of pollutant removal. More research is required to assess the costs of modified agricultural waste materials, not only for their production costs, but also for the cost per unit of pollutant removal and including a complete life-cycle analysis that accounts for externalities, such as greenhouse gas impacts.The main purpose of current modification procedures is to alter the physical and chemical characteristics on the surface of agricultural wastes to enhance pollutant adsorption. Future studies will undoubtedly devise new techniques to improve the efficiency and selectivity of the modified adsorbents for targeted applications. In addition, some adsorbent modification processes generate a series of potentially toxic by-products that must be addressed to minimize negative environmental impacts. Thus, optimization studies are required to generate low-cost adsorbents that are tunable for efficient and selective retention of targeted pollutants using green-chemistry principals. This will require systematic studies followed by physicochemical characterization of the modified materials and finally testing of their efficacy for retention of various pollutants under a wide range of environmental water conditions.

Rigorous physicochemical characterization is a critical intermediate step in this overall process. First, characterization provides the details for how various modification steps affect the physicochemical properties of the modified products. Second, understanding the physicochemical properties of the modified products is critical for mechanistically understanding the materials ability to retain various pollutants. Once sufficient characterization data has been systematically compiled, it will serve as a toolbox for fine tuning modification techniques to optimize materials for efficient and selective retention of specific pollutants. Although the modification methods discussed above are effective to improve the adsorption performance of agricultural wastes, there are some drawbacks that need attention. High alkali concentration may cause an excess elimination of covering materials from the cellulose surface and delignify the fibre extremely due to the hydrolysis, which can negatively afect the strength of the fibre. Concentrated acid oxidation has strong corrosiveness and was shown to decrease the surface area of oxidized adsorbent, which may reduce the porosity and efficacy of the adsorbent material for retention of some pollutants. Esterification and etherification creat high cost of the organic solvents used, the catalyst would also need to be recovered after modification. Carbonization not only consumes a lot of electricity, but also reduces the content functional groups of adsorbent at a high temperature. Magnetization can reduce surface area due to the block of magnetive particles in the pore of adsorbent. Surfactant and grafting have strict requirements for preparing environment and are prone to produce formation of undesirable block co-polymers. In all, the effectiveness of the treatment depends not only on the adsorption environment, but also on various preparation conditions. The conditions for the production of low-cost adsorbents after surface modification for higher uptake of pollutants need to be optimized further. Therefore, we still need to refine these modification methods to reduce their shortcomings and make them exhibit greater potential in preparing agricultural waste based adsorbents. Although modified agricultural wastes have been proven effective in retention of various pollutants in water, remediation actions that leave the pollutant-adsorbent compounds in the water environment have not been fully investigated. Over time, pollutants retained by bioadsorbents and accumulated in aquatic sediments may be released back to the water column upon changes in pH, temperature, ionic strength, redox conditions and bio-adsorbent degradation. Thus, bio-adsorbents that can be effectively extracted from the water environment, such as magnetic compounds, will provide a more permanent solution for pollutant retention and extraction from environmental waters. While modified agricultural wastes show great potential for the removal of various pollutants under laboratory conditions, far fewer studies have demonstrated their efficacy in real-world environmental waters, such as industrial/municipal waste waters. The composition of waste waters is much more complicated than that of synthetic waste waters used in many laboratory studies, which undoubtedly will affect the adsorption performance of the bio-adsorbents. Testing common bio-adsorbents across a wide range of environmental waters will provide fundamental knowledge to optimize applications for real-world use. Finally, most previous studies focused on the single adsorbent-adsorbate system, while there is a paucity of studies evaluating simultaneous use of multiple bio-adsorbents for retention/extraction of multiple pollution types. The coexistence of different pollutants is a common scenario in environmental waters and interactions among pollutants often affect the adsorption performance of various adsorbents. Moreover, there is a distinct paucity of research on the removal of rare and emerging pollutants , which are of considerable concern for human and aquatic ecosystem health. Finally, greater effort is required to rigorously investigate adsorption/ retention mechanisms. In addition to traditional sorption isotherm and kinetic studies, the emergence of advanced analytical methods, such as spectroscopic, microscopic, isotopic and molecular techniques, offer great potential for advancing our understanding of adsorption mechanisms. We are currently at the cross-roads of advancing from a more trial-and-error approach to developing a cook-book approach for designing modification techniques to achieve targeted materials for selective removal of pollutants.Children and other community members living within agricultural communities have an elevated risk of exposure to pesticides during pesticide spray seasons . This has been shown even among people who do not work in agriculture but reside near crops . These studies have described greater urinary metabolites of pesticides and lower acetylcholinesterase activity during the spray season compared to pre-season levels. Organophosphates and carbamates are commonly used insecticides in agriculture which are designed to inhibit the activity of AChE, leading to cholinergic overstimulation of the nervous system . Alterations of the cholinergic system can induce physiological alterations in the cardiovascular system . The relationship between pesticides and blood pressure is unclear, with a limited number of studies reporting positive associations between blood pressure and pesticide exposure constructs based either on selfreports or biomarkers , while some evidence of negative associations has also been described .

A natural experiment from a migration lottery in New Zealand finds evidence that migrant earnings stimulate remittance flows and generate better mental health outcomes . If out migration causes the local labor supply to decrease, this can put upward pressure on wages, which can be beneficial to local workers but potentially harmful to farmers who rely on hired labor. Filipski et al. find econometric evidence that migration from Mon state in Myanmar to Thailand caused Mon state wages to rise. However, migrant remittances offset the negative effects of higher wages on Mon production, as the infusion of remittances into the local economy stimulated productive investments and created spillovers by raising the demand for local goods and services. The role of agriculture as a driver of remittances becomes more marginal as migrant networks develop and information about non-farm employment opportunities spreads. In the U.S., for example, immigrants have become increasingly prevalent in all of the other low-skilled sectors of the economy , revealing agriculture’s diminishing role over time. The World Bank predicts a significant reduction in remittances due to lockdown measures from the COVID-19 crisis that prevent migration .

The decrease in remittances poses a huge threat to development,drainage collection pot which could potentially push a significant number of people back into poverty. Restrictions on mobility and work have particularly affected workers who are ineligible to receive benefits from social safety nets due to their informal working arrangements or legal status. In Southeast Asia, aggregate agricultural production is predicted to decline by three percent as a result of reduced labor mobility and access to input and output markets, which could increase the number of people in poverty by as much as three percent . Ultimately the revival of remittances will depend on the mobility of labor after the crisis calms down. Migration by men can affect the empowerment of women and the types of work in which they engage. Kar et al. find that, in Nepal, male out migration induces women to become the primary decision makers on the farm rather than simply providing labor to agricultural production. The receipt of remittances facilitates group membership and financial integration, as evidenced by the possession of bank accounts. However, in the absence of remittances, spouses of international migrants tend to be worse off with regard to several domains of empowerment, including decision making about certain productive activities, agricultural income, and access to information.

In Senegal, when household members migrate but do not send remittances home, households become more food insecure. These findings underscore the importance of programs to reduce remittance costs and improve extension services that enable women to become more productive farmers and entrepreneurs in migrant-source economies. To reduce reliance on immigrant farm labor, farmers and countries could switch out of labor-intensive crops and import them from lower wage countries. Some U.S. farm operations already expanded into Mexico in order to meet the year-round demand of their customers. In fact, about half of the fresh fruit consumed in the United States and a third of fresh vegetables are imported. There is some evidence that farmers are planting more land in less labor-intensive crops like tree nuts, most of which are harvested by machines that shake the nuts off the tree and sweep them off the ground . However, consumer demand for fresh fruits and vegetables, both in the United States and abroad, continues to rise, and food imports are expanding. Consumers’ demand and willingness to pay for locally-grown produce increases as incomes rise, creating limits to countries’ reliance on food imports as a solution to the farm labor problem. At the other end of this trade often are countries with much lower land per laborer, such as China. Since the turn of the century, China has dramatically raised its exports of labor-intensive fruits and vegetables, while increasing its imports of less strategic, and more land intensive ones such as soybeans and corn for animal feed, much of it from the United States and Brazil .

The structural transformation is a quintessential part of economic development everywhere; people move off the farm and pressure on agriculture grows to feed a growing population. What policies are required to address these issues logically depends on what stage of the development process a country is in and what institutions and social norms are in place. But at the core must lie a policy package that raises labor productivity in agriculture while leveraging the poverty-reducing powers of the AFS, mitigating the social-adjustment costs inherent to this transition, and avoiding the introduction of inefficient policies, such as the closure of borders for agricultural goods and labor. Accomplishing these tasks has been challenging in the past and will continue to be a challenge moving forward, with technological shifts, altering attitudes towards globalization, and climatic change further setting the boundaries of what’s possible and desirable. We conclude by pointing out a trio of policy entry points for developing countries, at the early to middle stages of the agricultural transformation, and for high-income countries at the late stages. The starting point for thinking about policy responses in developing countries is to recognize that agricultural labor productivity in many African countries continues to be dismally low, that current and future generations of young people are less willing than their parents to perform low-paying and onerous farm work, and that agricultural exports and emigration may offer fewer employment opportunities than in the past. However, domestic food demands continue to increase and diversify, creating important employment opportunities in the off-farm AFS.

These changes mean that both traditional and new digital technologies can be leveraged to induce a productive exit out of agriculture in Sub-Saharan Africa while maintaining a competitive agricultural workforce on and off the farm in the chains elsewhere. Three key policy implications emerge. First, productivity-enhancing investment in agriculture must accelerate in the lower-income countries and proceed at least in tandem with the movement of workers off the farm elsewhere. Populations will continue to grow despite slowing birthrates, and food production will have to expand to keep pace. The movement of workers off the farm to meet the demand for other goods requires producing more food with fewer workers, once underemployed labor has been activated. Historically in today’s high-income countries, agricultural extension and public investments in infrastructure, from irrigation to information, marketing institutions, and roads, played a critical supporting role in facilitating the labor exit out of agriculture. They enabled the remaining farmers to earn a living commensurate with non-farm sectors,round plastic pot as competition for workers with the non-farm sectors and downstream food processors intensified. This agenda holds as much today as then. In Sub-Saharan Africa, the agricultural share of public spending continues to be well below that in East Asia . Myriad input, factor, and output market constraints hold agricultural labor productivity back, and integrated solutions that simultaneously overcome a number of these constraints are needed. Inclusive value chain development , which links farmers with buyers in contracting arrangements, offering knowledge, access to credit and inputs , and higher prices in exchange for a consistent volume of high-quality products , provides a market-based solution to do so, though smallholders’ lack of legal protections can be an obstacle . Given the challenge to develop self-enforcing incentive compliant contracts, iVCD typically does not work well for raising staple crop productivity. Yet, in low income countries, this is where the need and scope for raising labor productivity and poverty reduction is highest. For raising labor productivity in staple crops, more and better public investment in public goods is needed . Second, the scope for iVCD to raise smallholder incomes and benefit the poor and women is greater for non-staples. iVCD also creates jobs off the farm, in the chains and beyond . Success factors of iVCD include careful diagnosis of the competitiveness and sustainability of the product value chain chosen, starting small, involving financial institutions, monitoring producer-buyer relationships, and sustaining capacity building. This is in addition to creating an economic environment that is conducive to investment generally. Developing systems to monitor and enforce food quality standards in the AFS is equally critical. There is clearly a role for agricultural ministries, as well as for the private sector, to ensure that the development and use of labor-saving technologies keeps pace with the movement of workers off-farm. Many questions remain, however, especially on the best entry points for support: through farmer organizations/cooperatives, large anchor firms and/or SMEs, or externally initiated stakeholder platforms. More experiments are needed. In the meantime, appropriate measures will be needed to help SMEs in the transformative food chains see through the decline in liquidity caused by COVID-19 and avoid undue concentration of activity in the long run.

Labor-market regulations and other social protections can also be useful in protecting vulnerable populations from exploitation as they transition into non-farm work . Third, investment in people is critical to raise agricultural labor productivity and to make sure that those leaving can access the new jobs in the AFS, as well as other non-farm sectors, and meet the rising economic aspirations of rural youth. Continued investment in quality rural education, which continues to largely underperform in developing countries, is needed . Increasing educational attainment in rural areas facilitates technology adoption, as well as occupational mobility, and reduces income inequality. This is also important for young women facing social norms that make it difficult to escape from traditional gender roles. Nontraditional skill-building programs and effective agricultural extension systems will be equally needed to build up human capital in regions where traditional education has proven ineffective. The extension system is particularly weak in Sub-Saharan Africa and has been largely neglected for the past couple of decades by governments and donors alike. The 2010s have witnessed a surge in studies on social network or farmer-to-farmer technology extension, which proves more promising especially in combination with public extension than traditional public-sector extension approaches. But several issues remain such as the choice and compensation of appropriate lead farmers . Policy implications are different, but just as immediate, in high income countries. Rich-country farmers will be required to produce more and higher-quality fresh and processed foods for a growing, and increasingly affluent, domestic and global population, and they will be required to do so under increasingly stringent environmental and animal welfare standards. However, they will have to do this with fewer workers. The transition of domestic workers out of farm work largely has run its course in rich countries. The option of importing foreign workers is gradually closing, due to a declining farm labor supply in farm labor exporting countries and a less supportive political environment for immigration, particularly of low-skilled workers, in high-income countries. Three key policy implications emerge for high-income countries in this era of growing farm labor scarcity: First, farmers in high income countries will increasingly need to look beyond immigration policy as an answer to farm labor scarcity —especially in the medium and long run. Guest worker programs can expand as a short-run response to farm labor scarcity. However, as the structural transformation progresses in farm labor-exporting countries and political resistance to importing low-skilled farm workers intensifies, the immigration solution to the farm labor problem becomes less of an option. This does not mean that immigration will not continue to play a central role in farm labor markets throughout the developed world for some time. But farmers will need to take steps to retain an aging, mostly immigrant, workforce while pursuing available options to contract new workers from abroad. International farm labor migration could continue to be a much-needed channel for sharing prosperity across nations and reducing poverty in the world’s poorest countries. For this, however, a counter narrative needs to take hold rapidly. If not, its days may be numbered prematurely, especially now that the COVID-19 pandemic so clearly exposed the agri-food sector’s dependence on immigrant labor and the logistical challenges this may entail, eroding support for reliance on immigrant agricultural labor even further. Second, increasingly sophisticated technological change is going to be a fundamental feature of the food supply chain, from farming to food processing. Productivity-enhancing investments likely will include the use of highly-advanced robotic systems that will dramatically reduce the need for workers .