USDA Agricultural Research Service Research Articles

Effects of combined conservation practices on soil and water quality in the Central Mississippi River Basin

Conventional cultivation of claypan soils leads to soil and water quality degradation because of high runoff and associated soil erosion. The Goodwater Creek Experimental Watershed, which is part of the USDA Agricultural Research Service Benchmark Conservation Effects Assessment Project, Watershed Assessment Studies, was established to address these issues. Plot studies have highlighted trade-offs between erosion control and herbicide or nutrient runoff. There is a need for long-term field-scale evaluation of combined practices that reduce sediment, nutrient, and herbicide losses by runoff. A 36 ha field located in Missouri was under a conventional corn (<i>Zea mays</i> L.)–soybean (<i>Glycine max</i> L.) system from 1993 to 2003 with fertilizer application and tillage prior to planting in the spring. A precision agriculture system defined by two main management zones was implemented from 2004 to 2014: wheat (<i>Triticum aestivum</i> L.) and soybean in 60% of the field, and corn and soybean in the remaining 40%. The system included no-till, cover crops, atrazine split-applications based on weed pressure, variable rates of nitrogen (N), and variable rates of fall-applied phosphorus (P). The objective of this study was to compare runoff water quality from the two management systems, based on flow and load duration curves, cumulative distribution functions, and conclusions from replicated plot studies. The precision agriculture system did not affect annual runoff, but it did increase the frequency of low flows. Sediment losses were reduced by 87% as a result of no-till and cover crops. Atrazine and P losses were lower than expected, despite the lack of incorporation into the soil. Atrazine losses were possibly lower because of the wheat area acting as a buffer, greater atrazine adsorption and retention in the field, and faster decay. Dissolved P losses as a fraction of applied remained the same, likely because of greater adsorption and lower runoff risk when applying P. Finally, nitrate-N (NO₃-N) losses decreased and resulted in an overall decrease of N losses despite a slight increase of ammonium-N (NH₄-N) losses. Explanations included a greater soil water content, a different timing of N applications, and N uptake by cover crops. Building on these successes, an aspirational management system is proposed to further improve on the performance and practicality of the precision agriculture system.

A strategic plan for future USDA Agricultural Research Service erosion research and model development

Soil erosion is a natural process, and the erosion potential of a site is the result of complex interactions among soil, vegetation, topographic position, land use and management, and climate. Soil erosion occurs when aeolian and hydrologic processes exceed a soil’s inherent resistance to these forces (figures 1 and 2). Soil erosion was recognized as a significant problem at both local and national scales in the United States in the 1920s; by 1935 soil erosion was considered a national disaster, covering over one-half of the country (Sampson and Weyl 1918; Weaver 1935), and is still a concern with 21% of the western United States degraded and vulnerable to accelerated soil erosion (Herrick et al. 2010; Weltz et al. 2014a; Duniway et al. 2019). In 1995, it was estimated that 4 × 109 t (4.4 × 109 tn) of soil was lost from US cropland (Pimentel et al. 1995). The most vulnerable areas for soil movement and thus erosion occur where annual precipitation is 100 to 400 mm y–1 (4 to 16 in yr–1), which limits soil moisture available to sustain plant growth. Anthropogenic-driven dust emissions have dramatically increased across …

Influence of Model Grid Size on the Estimation of Surface Fluxes Using the Two Source Energy Balance Model and sUAS Imagery in Vineyards.

Evapotranspiration (ET) is a key variable for hydrology and irrigation water management, with significant importance in drought-stricken regions of the western US. This is particularly true for California, which grows much of the high-value perennial crops in the US. The advent of small Unmanned Aerial System (sUAS) with sensor technology similar to satellite platforms allows for the estimation of high-resolution ET at plant spacing scale for individual fields. However, while multiple efforts have been made to estimate ET from sUAS products, the sensitivity of ET models to different model grid size/resolution in complex canopies, such as vineyards, is still unknown. The variability of row spacing, canopy structure, and distance between fields makes this information necessary because additional complexity processing individual fields. Therefore, processing the entire image at a fixed resolution that is potentially larger than the plant-row separation is more efficient. From a computational perspective, there would be an advantage to running models at much coarser resolutions than the very fine native pixel size from sUAS imagery for operational applications. In this study, the Two-Source Energy Balance with a dual temperature (TSEB2T) model, which uses remotely sensed soil/substrate and canopy temperature from sUAS imagery, was used to estimate ET and identify the impact of spatial domain scale under different vine phenological conditions. The analysis relies upon high-resolution imagery collected during multiple years and times by the Utah State University AggieAir™ sUAS program over a commercial vineyard located near Lodi, California. This project is part of the USDA-Agricultural Research Service Grape Remote Sensing Atmospheric Profile and Evapotranspiration eXperiment (GRAPEX). Original spectral and thermal imagery data from sUAS were at 10 cm and 60 cm per pixel, respectively, and multiple spatial domain scales (3.6, 7.2, 14.4, and 30 m) were evaluated and compared against eddy covariance (EC) measurements. Results indicated that the TSEB2T model is only slightly affected in the estimation of the net radiation (Rn) and the soil heat flux (G) at different spatial resolutions, while the sensible and latent heat fluxes (H and LE, respectively) are significantly affected by coarse grid sizes. The results indicated overestimation of H and underestimation of LE values, particularly at Landsat scale (30 m). This refers to the non-linear relationship between the land surface temperature (LST) and the normalized difference vegetation index (NDVI) at coarse model resolution. Another predominant reason for LE reduction in TSEB2T was the decrease in the aerodynamic resistance (Ra), which is a function of the friction velocity F*) that varies with mean canopy height and roughness length. While a small increase in grid size can be implemented, this increase should be limited to less than twice the smallest row spacing present in the sUAS imagery. The results also indicated that the mean LE at field scale is reduced by 10% to 20% at coarser resolutions, while the with-in field variability in LE values decreased significantly at the larger grid sizes and ranged between approximately 15% and 45%. This implies that, while the field-scale values of LE are fairly reliable at larger grid sizes, the with-in field variability limits its use for precision agriculture applications.

Winter wheat response to climate change under irrigated and dryland conditions in the US southern High Plains

A rise in global temperature has been observed since the 1980s. The objective of the study was to understand the winter wheat (Triticum aestivum L.) responses and yield performances to the changing climate. The study was performed using growing degree day (GDD) model and regression analysis method. Wheat data (1940 to 2016) were obtained from the Southern Regional Performance Nursery (SRPN) experiments at Bushland, Texas. Wheat genotypes were divided into three groups: Kharkof as a check cultivar, the highest yielding cultivar for each year, and all other cultivars. Climate data were obtained from USDA Agricultural Research Service at Bushland and the National Oceanic and Atmospheric Administration. Temperatures between 1940 and 2016 showed a curvilinear trend with a significant rise since 1980. Mean temperature during wheat growing season (September 15 to June 15) increased at a rate of 0.35°C per decade since 1980. Consequently, seasonal GDD and extreme degree days (EDD) increased at a rate of 69°C d and 19°C d per decade. From 1940 to 2016, wheat heading date has shifted earlier by 16 days for dryland wheat and 11 days for irrigated wheat. Maximum and minimum temperatures in March and April had a negative relationship with heading date, while precipitation had a positive relationship with heading date for both dryland and irrigated wheat. Early heading may have benefits for heat escape but also has the disadvantage of reducing precipitation prior to heading—a loss of 25 mm when heading shifted earlier by 16 days for dryland wheat. The five-year moving average yields increased steadily from about 1960 to 1980, plateaued until the late 1980s, and then declined significantly. However, average genetic yield gains were 505 kg ha−1 under dryland and 1,671.4 kg ha−1 under irrigated conditions for all new cultivars during 1940 to 2016. Yield trends for all three cultivar groups had similar patterns over the years. Increase in maximum temperature, frequencies of maximum temperature greater than or equal to 31°C, and minimum temperature during grain filling period had significant negative effect on grain filling days and yield (except for minimum temperature under dryland conditions). Precipitation during the vegetative growth (November, January, and March) and grain filling (May) had a significant positive effect on dryland wheat yields, but only the January precipitation had significant effect on wheat yield under irrigated conditions. The study indicated that the rising temperature and shifting precipitation timings as a result of early heading are less favorable conditions for winter wheat production in the US southern High Plains.

Research Priorities of the Environmental Horticultural Industry Founded through Consensus1

Abstract Environmental horticulture production (EHP) generates and employs approximately one-third of all specialty crop revenue and workforce, respectively. In recent years, however, EHP received only 12% of federal funds earmarked for specialty crops research from the USDA-Agricultural Research Service or the USDA-Specialty Crops Research Initiative. To increase leverage and accumulate more resources for EHP, stakeholder-driven consensus of research priorities needed to be constructed. Therefore, the Horticultural Research Institute led a professionally facilitated stakeholder roundtable discussion to achieve these priorities. Stakeholders identified trends and forces affecting EHP, its current state, a vision, and outcomes needed for success. Through consensus, four equal research priorities were constructed: 1) quantitate and validate the ecosystem services and benefits of plants on human health and wellness, 2) develop innovations in biological, mechanical, and technological systems that provide efficient, productive, and profitable solutions relevant to producer size and segment, 3) evaluate consumer-driven preferences that optimize industry-wide profitability and growth, and 4) solve ongoing and emergent industry challenges. These priorities and the successful future of EHP will be made possible by strong leaders and advocates positioned throughout industry, successfully communicating the human health, social, and economic benefits of plants, state-of-the-art technological and efficiently-designed systems, and an understanding of current and future consumers. Index words: forces, greenhouse, innovation, nursery, roadmap, stakeholders, trends, vision.

Cover Image, Volume 75, Issue 11

The cover image is by Stephen Ausmus, USDA Agricultural Research Service, Image Number D288‐4. image

Cover Image, Volume 75, Issue 10

The cover image is based on “Photo by Stephen Ausmus, USDA Agricultural Research Service”. image

For president-elect: H. N. Cheng

ACS ELECTIONS For president-elect: H. N. Cheng ShareShare onFacebookTwitterWechatLinked InRedditEmail C&EN, 2019, 97 (35), pp 44–46September 9, 2019Cite this:C&EN 97, 35, 44-46AbstractLouisiana Section. US Department of Agriculture, Agricultural Research Service, Southern Regional Research Center, New Orleans. Academic record: University of California, Los Angeles, BS; University of Illinois at Urbana-Champaign, PhD. Honors: ACS Fellow, 2009; Fellow, ACS Division of Agricultural and Food Chemistry, 2018; Fellow, ACS Division of Polymer Chemistry, 2010; ACS Volunteer Service Award, 2016; Special Service Award, ACS Polymer Chemistry Division, 2015; Distinguished Service Award, ACS Polymer Chemistry Division, 2005; Tillmanns-Skolnik Award, ACS Delaware Section, 2006; ACS Delaware Section Award, 1994; Outstanding Contributor to Cultural Diversity at USDA Southern Regional Research Center, 2017, 2011; Outstanding Scientist of the Year, USDA Southern Regional Research Center, 2014; Hercules Accountability Award, 1997; Hercules Research Fellow Award, 1990; Hercules High Achievement Awards, 1984, 1987; Sigma Xi; Phi Lambda Upsilon; Phi Kappa Phi; Phi Beta Kappa. Professional positions (for past 10 years): USDA Agricultural Research Service, Southern Regional Research Center, research chemist, 2009–; Hercules (laterView: PDF | Full Text HTML

41 Management effects on long-term crop yield stability in central and eastern nebraska

Abstract The sustainability and resilience of cropping systems will depend on how different management practices impact yield stability over the long-term. Here, we summarize the effects of crop rotation, tillage, crop residue removal, and nitrogen fertilizer rate on corn and soybean yield responses from several long-term research experiments maintained by the USDA-Agricultural Research Service in eastern and central Nebraska. Across all study sites, we found that yield stability is affected most by crop rotation, then tillage, then residue management, where stability can be further improved in all systems by using the optimum N fertilizer rate. While crop rotation and rotation complexity tend to have the greatest impact on long-term yield stability in the western Corn Belt, nearly all combinations of management can produce stable yields if well managed.

Associations of Lipid-related SNPs with Circulating Phylloquinone Are Proportional with Triglycerides (P15-008-19)

ObjectivesPhylloquinone is transported on triglyceride-rich lipoproteins. Preliminary evidence from a genome-wide association meta-analysis suggests that genetic variants that influence triglycerides (TGs), such as rs964184 at the APOA1/C3/A4/A5 gene cluster, also influence circulating phylloquinone. To further evaluate this overlap, we examined the linear relationship between a weighted TG genetic risk score (wTG-GRS) with circulating phylloquinone. MethodsWe constructed a wTG-GRS comprised of 20 SNPs that were previously associated with TGs in a genome-wide association meta-analysis for blood lipids (n > 188,000 individuals of European ancestry). The assigned weights corresponded to the effect-sizes (β) reported for each SNP’s association with TGs. With meta-analytic summary statistic data from a separate genome-wide association meta-analysis of circulating phylloquinone (n = 2138 individuals of European ancestry), a statistical technique was used to approximate the linear association of the wTG-GRS with circulating phylloquinone. A p-value of 0.05 for the estimate was considered statistically significant. First, the estimate was calculated without adjustment for TGs using Model 1 summary statistics, then calculated with adjustment for TGs using Model 2 summary statistics. ResultsThe estimate for the linear association of the wTG-GRS with circulating phylloquinone was significant without and with adjustment for TGs (Model 1: β = 0.052, P = < 0.0001, Model 2: β = 0.027, P = 0.0001, respectively). The goodness-of-fit of the model was improved from Model 1 (p-het = 0.022) to Model 2 (p-het = 0.054). ConclusionsThe associations of TG-related SNPs with circulating phylloquinone were proportional to their associations with TGs. This provides further evidence of the shared genetic links between TGs and phylloquinone and suggests genetic studies of vitamin K should consider TGs. Funding SourcesStudy supported by the USDA Agricultural Research Service under Cooperative Agreement No. 58-1950-7-707 and NHLBI T32HL069772.

How Accurate Is the Labeled Content of Prescription Prenatal Multivitamin/mineral (MVM)? -an Analytical Pilot Study for the Dietary Supplement Ingredient Database (DSID) (OR14-08-19)

ObjectivesUS national surveys report that pregnant women are at risk of dietary deficiency for several key nutrients, including calcium, iron, folate, and vitamin D. Most pregnant women take prenatal multivitamins (MVM). However intake studies have used only product label information, which may lead to incorrect estimates of their impact on nutrition status. It is unknown if the label information for prescription prenatal (RxP) MVM correctly reflects the composition of these products. The objective of this study was to investigate the relationship between labeled and analytically measured content of ingredients in RxP MVM. MethodsFrom a list of 338 Rx prenatal MVM sold by retail and mail order pharmacies from 06–2015 to 06–2016, a selection of representative products was generated using random sampling weighted by market share. Multiple lots of 24 products, representing 61% of the market were tested by commercial laboratories for their vitamin, mineral and docosahexaenoic acid (DHA) content. Laboratories were selected based on the results from quality control materials, including National Institute of Standards and Technology Standard Reference Materials. ResultsThe RxP MVM evaluated in this study varied in their labeled ingredient content. All RxP MVM labels listed folic acid, vitamins B-6, D, E and iron; 83–92% contained niacin, riboflavin, thiamin, and vitamins C, B-12, and zinc; and 71% contained calcium. Only 46–54% contained vitamin A, iodine and DHA. Analytical results showed mean overages of ≥20% for 6 vitamins (folic acid, niacin, riboflavin and vitamins A, B-12, D); 10–15% for vitamins B-6, C, E; and slightly below (−4%) label results for thiamin. For minerals and DHA, analytical content was close to labeled content, averaging 1–11% above label. ConclusionsMany of the less expensive, highly consumed products were formulated without iodine or DHA despite recommendations for iodine supplementation from leading health authorities in the US and worldwide and data indicating that DHA may improve pregnancy outcomes. Analytical testing revealed that most RxP MVM had vitamin and mineral levels above label, with vitamin D the highest, averaging 29% above label. Thus, the intake of some nutrients from Rx prenatal MVM could be underestimated. Funding SourcesNIH Office of Dietary Supplements and USDA Agricultural Research Service.

Epigenome-wide Association Study of Plasma Phylloquinone Response to Phylloquinone Supplementation (OR31-04-19)

ObjectivesGenetics explains a small amount of the variability in the response of plasma phylloquinone to phylloquinone intake. Whether epigenetic modifications, which reflect interactions between the genome and environment, are related to the plasma phylloquinone response to supplementation has not been examined. The objective of this study was to conduct an epigenome-wide association study (EWAS) to identify genetic loci whose methylation levels associate with changes in circulating phylloquinone in response to phylloquinone supplementation. MethodsWe used data from a 3-year, randomized controlled, phylloquinone supplementation (500 ug/d) trial in healthy older adults. One hundred four white participants in the supplementation group who passed filters for adherence to the protocol (mean age = 68(5.0) years, 56% female) were classified as responders or non-responders according to their change in plasma phylloquinone. Of these, 24 participants with the smallest (non-responders) and 24 participants with the largest (responders) change in plasma phylloquinone were selected for DNA methylation analysis. DNA was isolated from baseline blood samples. Bisulfite-converted DNA for these 48 individuals was analyzed using the Illumina MethylationEPIC microarray platform at the Yale Center for Genome Analysis in New Haven, CT. The association of responder status with methylation beta-value at each site was examined using logistic regression adjusted for control-probe principal components. ResultsForty (38%) of the 104 participants had changes in plasma phylloquinone that classified them as non-responders. A single CpG site (cg10918016 in NCOR2) was associated with plasma phylloquinone responder status at genome-wide Bonferroni level of significance (P < 6.4 × 10−8). In the presence of moderate genomic inflation (λ = 1.21), 5239 sites showed suggestive associations (Benjamini-Hochberg FDR < 0.2). ConclusionsDNA methylation levels may contribute toward the inter-individual plasma phylloquinone response to supplementation. Larger studies in diverse populations are warranted to clarify the causal influence of methylation on the vitamin K status. Funding SourcesStudy supported by the USDA Agricultural Research Service under Cooperative Agreement No. 58-1950-7-707, NHLBI T32HL069772, and the Gerald Cassidy Student Research Award.*JMK and KW contributed equally to this research. Supporting Tables, Images and/or Graphs▪

Hydrologic model parameterization using dynamic Landsat-based vegetative estimates within a semiarid grassland

The use of hydrologic models to assess long-term watershed condition through repeated simulations of runoff and erosion is one common approach for rangeland health evaluation. However, obtaining vegetative data of appropriate spatiotemporal resolution for model parameterization can be difficult. The goal of this research was to assess the utility of using time-varying, Landsat-derived vegetative values to parameterize an event-based, watershed-scale hydrologic model. This study was conducted on a small, instrumented grassland watershed in the USDA Agricultural Research Service operated Walnut Gulch Experimental Watershed in southeastern, Arizona. Cloud-free Landsat scenes were acquired over the watershed for the years 1996–2014. The Soil Adjusted Total Vegetation Index (SATVI) was calculated for each image and calibrated using ground measured data to produce a time series of satellite-based foliar cover rasters. These values were used to parameterize the Rangeland Hydrology and Erosion Model (RHEM) for 26 rainfall-runoff events with corresponding observed data. Three parameterization scenarios using these data aggregated to different temporal resolutions (static, long-term mean, annual mean, and intra-annual values) were compared to a static literature-based scenario for evaluation. The linear relationship between field-measured foliar cover and SATVI showed statistically significant agreement with R2 = 0.85 and p < 0.05. Simulated runoff volume and peak flow rate using the three remotely sensed parameterization scenarios improved upon that of the literature-based scenario, with the annual mean scenario performing the best of the three temporal aggregations. The methodological framework outlined here provides a means for improved parameterization for watershed-scale modelling where vegetative data may be scarce or unobtainable for long-term analysis.

The impact of shadows on partitioning of radiometric temperature to canopy and soil temperature based on the contextual two-source energy balance model (TSEB-2T).

Tests of the most recent version of the two-source energy balance model have demonstrated that canopy and soil temperatures can be retrieved from high-resolution thermal imagery captured by an unmanned aerial vehicle (UAV). This work has assumed a linear relationship between vegetation indices (VIs) and radiometric temperature in a square grid (i.e., 3.6 m × 3.6 m) that is coarser than the resolution of the imagery acquired by the UAV. In this method, with visible, near infrared (VNIR), and thermal bands available at the same high-resolution, a linear fit can be obtained over the pixels located in a grid, where the x-axis is a vegetation index (VI) and the y-axis is radiometric temperature. Next, with an accurate VI threshold that separates soil and vegetation pixels from one another, the corresponding soil and vegetation temperatures can be extracted from the linear equation. Although this method is simpler than other approaches, such as TSEB with Priestly-Taylor (TSEB-PT), it could be sensitive to VIs and the parameters that affect VIs, such as shadows. Recent studies have revealed that, on average, the values of VIs, such as normalized difference vegetation index (NDVI) and leaf area index (LAI), that are located in sunlit areas are greater than those in shaded areas. This means that involving or compensating for shadows will affect the linear relationship parameters (slope and bias) between radiometric temperature and VI, as well as thresholds that separate soil and vegetation pixels. This study evaluates the impact of shadows on the retrieval of canopy and soil temperature data from four UAV images before and after applying shadow compensation techniques. The retrieved temperatures, using the TSEB-2T approach, both before and after shadow correction, are compared to the average temperature values for both soil and canopy in each grid. The imagery was acquired by the Utah State University AggieAir UAV system over a commercial vineyard located in California as part of the USDA Agricultural Research Service Grape Remote sensing Atmospheric Profile and Evapotranspiration Experiment (GRAPEX) Program during 2014 to 2016. The results of this study show when it is necessary to employ shadow compensation methods to retrieve vegetation and soil temperature directly.

Validation of digital surface models (DSMs) retrieved from unmanned aerial vehicle (UAV) point clouds using geometrical information from shadows.

Theoretically, the appearance of shadows in aerial imagery is not desirable for researchers because it leads to errors in object classification and bias in the calculation of indices. In contrast, shadows contain useful geometrical information about the objects blocking the light. Several studies have focused on estimation of building heights in urban areas using the length of shadows. This type of information can be used to predict the population of a region, water demand, etc., in urban areas. With the emergence of unmanned aerial vehicles (UAVs) and the availability of high- to super-high-resolution imagery, the important questions relating to shadows have received more attention. Three-dimensional imagery generated using UAV-based photogrammetric techniques can be very useful, particularly in agricultural applications such as in the development of an empirical equation between biomass or yield and the geometrical information of canopies or crops. However, evaluating the accuracy of the canopy or crop height requires labor-intensive efforts. In contrast, the geometrical relationship between the length of the shadows and the crop or canopy height can be inversely solved using the shadow length measured. In this study, object heights retrieved from UAV point clouds are validated using the geometrical shadow information retrieved from three sets of high-resolution imagery captured by Utah State University's AggieAir UAV system. These flights were conducted in 2014 and 2015 over a commercial vineyard located in California for the USDA Agricultural Research Service Grape Remote sensing Atmospheric Profile and Evapotranspiration Experiment (GRAPEX) Program. The results showed that, although this approach could be computationally expensive, it is faster than fieldwork and does not require an expensive and accurate instrument such as a real-time kinematic (RTK) GPS.

An R Framework for the Partitioning of Linkage Disequilibrium between and Within Populations

Patterns of linkage disequilibrium (LD) across the genome result from a myriad of contributing factors including selection and genetic drift. Natural selection can increase LD near individually selected loci, or it can influence LD between epistatically selected groups of loci. Statistics have previously been derived which compare levels of linkage disequilibrium in subpopulations relative to the total population. These statistics may be leveraged to identify loci that may be under selection or epistatic selection. This is a powerful approach, but to date no framework exists to support its use on a genome-wide scale. We present ohtadstats , an R package designed to facilitate the implementation of Ohta’s D statistics in a variety of use cases. Statistics calculated by this package can be used to determine whether a locus is under selection or not, and can provide insight into the nature of the selection that is taking place (hard sweep or epistatic selection). This package is available on the Comprehensive R Archive Network (CRAN). Funding statement: This research was supported by funding from the USDA Agricultural Research Service. PFP is funded by the University of Missouri Life Sciences Fellowship and a training grant from the National Institute of Health (T32GM008396).

Cover Image, Volume 75, Issue 5

Cotton Bollworm. Photo by Scott Bauer, USDA Agricultural Research Service. image

Selection of Optimal Hyperspectral Wavebands for Detection of Discolored, Diseased Rice Seeds

This work was supported by the USDA Agricultural Research Service, Food Safety National Program [Project No. 8042-42000-020-00D]; and the National Institute of Agricultural Sciences, Rural Development Administration, Republic of Korea [Research Program for Agricultural Science & Technology Development, Project No. PJ012216].

Variation in floral antioxidant activities and phytochemical properties among butterfly pea (Clitoria ternatea L.) germplasm

Butterfly pea (Clitoria ternatea L.) is a climbing legume grown as a medicinal, ornamental, and forage plant, and used as a natural food colorant. Due to its various medicinal properties in different plant parts, pharmacological potential is evident. However, improvement of the plant for high phytochemical properties has been very limited, hence being pursued. For that improvement effort, butterfly pea germplasm was collected from different parts of Thailand in addition to accessions from 12 other countries acquired from a C. ternatea collection curated by the USDA-Agricultural Research Service National Plant Germplasm System. Characterization and evaluation for phytochemical properties of these germplasm is fundamental for breeding purposes. Floral antioxidant activities (Ferric reducing antioxidant power—FRAP and 2,2-diphenyl-1-picrylhydrazyl—DPPH), total phenolic compound (TPC), total anthocyanin content (TAC), and ascorbic acid content (AAC) were investigated for 126 individuals from 46 accessions of the combined collection. The plants were regenerated from seeds and grown at Kamphaeng Saen, Nakhon Pathom, Thailand, and flowers were harvested in August 2017. Significant differences of TAC and AAC were found among the included accessions. Both variations were correlated with petal color at a moderate level, but not in accordance with geographical locations of the samples. Grouping of the accessions based on antioxidant activities and compounds revealed by cluster and principal component analyses would be useful in the utilization and management of the germplasm for butterfly pea improvement.

Comparison of Stationary and Moving Infrared Thermometer Measurements Aboard a Center Pivot

HighlightsStationary and moving infrared thermometers aboard a center pivot were compared.Comparisons were in terms of directional brightness temperature discrepancies.Discrepancies were within 1.8°C, and many were within 1.0°C.Larger discrepancies tended to occur for sparser vegetation cover.Abstract. Infrared thermometers (IRTs) can measure canopy temperature, which is useful for irrigation and crop management. Center pivot and lateral move irrigation systems are suitable platforms to transport IRTs across cropped fields at regular intervals. IRTs aboard center pivots, when used in conjunction with irrigation scheduling algorithms, have resulted in crop yield and crop water productivity that is equivalent to or greater than what can be achieved using soil water measurements of the root zone profile with a field-calibrated neutron probe. Irrigation scheduling algorithms perform best when stationary IRT measurements are supplemented with moving IRT arrays, where the former provides time series data and the latter provides spatially distributed data. However, the normal deflection of moving irrigation systems and other confounding factors have caused concern that moving IRT measurements may be degraded relative to stationary IRT measurements. Directional brightness temperatures (TB) measured by stationary and moving IRTs were compared over two corn and one potato season at the USDA Agricultural Research Service, Bushland, Texas. Moving and stationary TB were compared in terms of root mean square error, mean absolute error, and mean bias error, and were all &amp;lt; 1.8°C, and many were &amp;lt; 1.0°C, and r2 = 0.95. Error terms tended to be larger for potato, which had less vegetation cover compared with corn. However, error terms were similar to previous studies of calibration and spatial variability for IRTs and thermal imagers. Therefore, TB measurements of moving IRTs did not appear to be degraded relative to TB measurements of stationary IRTs for this study. However, interpretation of stationary and moving IRT measurements may be aided by addition of low cost imagers to distinguish vegetation from soil background. Keywords: Canopy temperature, Crop management, Evapotranspiration, Irrigation, Remote sensing, Sensors.