Developing a Multi-Spectral NIR LED-Based Instrument for the Detection of Pesticide Residues Containing Chlorpyrifos-Methyl in Rough, Brown, and Milled Rice.

A recent study showed the potential of the DA Perten 7200 NIR Spectrometer in detecting chlorpyrifos-methyl pesticide residue in rough, brown, and milled rice. However, this instrument is still lab-based and generally suited for point-of-sale testing. To provide a field-deployable version of this technique, an existing light emitting diode (LED)-based instrument that provides discrete NIR wavelength illumination and reflectance spectra over the range of 850-1550 nm was tested. Spectra were collected from rough, brown, and milled rice at different pesticide concentrations and analyzed for quantitative and qualitative measurement using partial least squares regression (PLS) and discriminant analysis (DA). Simulations for two LED-based instruments were also evaluated using corresponding segments of spectra from the DA7200 to represent LED illumination. For the simulation of the existing LED-based instrument (LEDPrototype1) fitted with 850, 910, 940, 970, 1070, 1200, 1300, 1450, and 1550 nm LED wavelengths, resulting R2 ranged from 0.52 to 0.71, and the correct classification was 70.4% to 100%. The simulation of a second LED instrument (LEDPrototype2) fitted with 980, 1050, 1200, 1300, 1450, 1550, 1600, and 1650 nm LED wavelengths showed R2 of 0.59 to 0.82 and correct classifications of 66% to 100%. These LED wavelengths were selected based on the significant wavelength regions from the PLS regression coefficients of DA7200 and the commercial availability of LED wavelengths. Results showed that it is possible to use a multi-spectral LED-based instrument to detect varying levels of chlorpyrifos-methyl pesticide residue in rough, brown, and milled rice.

Identification and Candidate Gene Evaluation of a Large Fast Neutron-Induced Deletion Associated with a High-Oil Phenotype in Soybean Seeds.

Since the dawn of agriculture, crops have been genetically altered for desirable characteristics. This has included the selection of natural and induced mutants. Increasing the production of plant oils such as soybean (Glycine max) oil as a renewable resource for food and fuel is valuable. Successful breeding for higher oil levels in soybeans, however, usually results in reduced seed protein. A soybean fast neutron population was screened for oil content, and three high oil mutants with minimal reductions in protein levels were found. Three backcross F2 populations derived from these mutants exhibited segregation for seed oil content. DNA was pooled from the high-oil and normal-oil plants within each population and assessed by comparative genomic hybridization. A deletion encompassing 20 gene models on chromosome 14 was found to co-segregate with the high-oil trait in two of the three populations. Eighteen genes in the deleted region have known functions that appear unrelated to oil biosynthesis and accumulation pathways, while one of the unknown genes (Glyma.14G101900) may contribute to the regulation of lipid droplet formation. This high-oil trait can facilitate the breeding of high-oil soybeans without protein reduction, resulting in higher meal protein levels.

Compositional analysis in sorghum (Sorghum bicolor) NIR spectral techniques based on mean spectra from single seeds.

Sorghum (Sorghum bicolor) is an economically important cereal crop that can be used as human food, animal feed, and for industrial use such as bioenergy. In sorghum breeding programs, development of cultivars with desirable seed quality characteristics is important and development of rapid low-cost screening methods for seed nutritional traits are desired, since most standard methods are destructive, slow, and less environmentally friendly. This study investigates the feasibility of single kernel NIR spectroscopy (SKNIRS) for rapid determination of individual sorghum seed components. We developed successful multivariate prediction models based on partial least squares (PLS) regression for protein, oil, and weight in sorghum. The results showed that for sorghum protein content ranging from 8.92% to 18.7%, the model coefficients of determination obtained were R C A L 2 = 0.95 (RMSEC= 0.44) and R P R E D 2 = 0.87 (RMSEP= 0.69). The model coefficients of determination for oil prediction were R C A L 2 = 0.92 (RMSEC= 0.23) and R P R E D 2 = 0.71 (RMSEP= 0.41) for oil content ranging from 1.96% to 5.61%. For weight model coefficients of determination were R C A L 2 = 0.81 (RMSEC= 0.007) and R P R E D 2 = 0.63 (RMSEP= 0.007) for seeds ranging from 4.40 mg to 77.0 mg. In conclusion, mean spectra SKNIRS can be used to rapidly determine protein, oil, and weight in intact single seeds of sorghum seeds and can provide a nondestructive and quick method for screening sorghum samples for these traits for sorghum breeding and industry use.

Flax and Sorghum: Multi-Element Contents and Nutritional Values within 210 Varieties and Potential Selection for Future Climates to Sustain Food Security.

The Dietary Guidelines for Americans recommends giving priority to nutrient-dense foods while decreasing energy-dense foods. Although both flax (Linum usitatissimum) and sorghum (Sorghum bicolor) are rich in various essential minerals, their ionomes have yet to be investigated. Furthermore, previous studies have shown that elevated CO2 levels could reduce key nutrients in crops. In this study, we analyzed 102 flax and 108 sorghum varieties to investigate their ionomic variations (N, P, K, Ca, Mg, S, B, Zn, Mn, Fe, Cu, and Mo), elemental level interactions, and nutritional value. The results showed substantial genetic variations and elemental correlations in flax and sorghum. While a serving size of 28 g of flax delivers 37% daily value (DV) of Cu, 31% of Mn, 28% of Mg, and 19% of Zn, sorghum delivers 24% of Mn, 16% of Cu, 11% of Mg, and 10% of Zn of the recommended daily value (DV). We identified a set of promising flax and sorghum varieties with superior seed mineral composition that could complement breeding programs for improving the nutritional quality of flax and sorghum. Overall, we demonstrate additional minerals data and their corresponding health and food security benefits within flax and sorghum that could be considered by consumers and breeding programs to facilitate improving seed nutritional content and to help mitigate human malnutrition as well as the effects of rising CO2 stress.

A decade of rising alcoholic liver disease hospital admissions and deaths in Irish hospitals, 2007-2016: a retrospective cross-sectional analysis.

BACKGROUND: Alcoholic liver disease (ALD) is a major cause of both liver cirrhosis and hepatocellular carcinoma (HCC) in Ireland. AIMS: The aim of the study was to identify the epidemiological profile, temporal trends, development of complications and mortality arising from inpatient care episodes linked to ALD in Ireland from 2007 to 2016. METHODS: This was a national retrospective study that analysed data on patient discharges from hospitals across Ireland. The Hospital Inpatient Enquiry System was used to gather this data. The main outcome measures were the number of hospital discharges for patients with ALD or HCC, also expressed per 100 000 population, the mortality rate associated with ALD and the prevalence of complications associated with ALD. RESULTS: A total of 33 794 hospital discharges were examined. There was a 38% increase in hospital discharges and 300% increase in HCC coding for patients with ALD between 2006 and 2016. There were 73 hospital discharges with ALD per 100 000 population in 2016. That year, 40 482 bed days were required for inpatient management equating to 120 beds per day. Deaths from ALD rose by 29% over the 10-year period. Cirrhosis was diagnosed in 57% and 24% had ascites. Mortality was 9.8% rising to 16% with variceal bleeding and 42% with acute kidney injury. Only 31% were under the care of a gastroenterologist or hepatologist. CONCLUSION: Ireland is seeing a rise in ALD-related hospital admissions and deaths, including HCC which increased three-fold. ALD is a preventable disease, and public health interventions are of proven benefit and required to reverse this trend.

Protein, weight, and oil prediction by single-seed near-infrared spectroscopy for selection of seed quality and yield traits in pea (Pisum sativum).

BACKGROUND: Pea (Pisum sativum) is a prevalent cool-season crop that produces seeds valued for their high protein content. Modern cultivars have incorporated several traits that improved harvested yield. However, progress toward improving seed quality has received less emphasis, in part due to the lack of tools for easily and rapidly measuring seed traits. In this study we evaluated the accuracy of single-seed near-infrared spectroscopy (NIRS) for measuring pea-seed weight, protein, and oil content. A total of 96 diverse pea accessions were analyzed using both single-seed NIRS and wet chemistry methods. To demonstrate field relevance, the single-seed NIRS protein prediction model was used to determine the impact of seed treatments and foliar fungicides on the protein content of harvested dry peas in a field trial. RESULTS: External validation of partial least squares (PLS) regression models showed high prediction accuracy for protein and weight (R2 = 0.94 for both) and less accuracy for oil (R2 = 0.74). Single-seed weight was weakly correlated with protein and oil content in contrast with previous reports. In the field study, the single-seed NIRS predicted protein values were within 10 mg g-1 of an independent analytical reference measurement and were sufficiently precise to detect small treatment effects. CONCLUSION: The high accuracy of protein and weight estimation show that single-seed NIRS could be used in the dual selection of high-protein, high-weight peas early in the breeding cycle, allowing for faster genetic advancement toward improved pea nutritional quality. © 2020 Society of Chemical Industry.

Interplay between nitrogen fertilizer and biological nitrogen fixation in soybean: implications on seed yield and biomass allocation.

Legumes rely on soil mineral nitrogen (N) and biological N fixation (BNF). The interplay between these two sources is biologically interesting and agronomically relevant as the crop can accommodate the cost of BNF by five non-mutually exclusive mechanisms, whereby BNF: reduces shoot growth and seed yield, or maintains shoot growth and seed yield by enhanced photosynthesis, or reduced root:shoot ratio, or maintains shoot growth but reduces seed yield by reducing the fraction of shoot biomass allocated to seed (harvest index), or reducing concentration of oil and protein in seed. We explore the impact of N application on the seasonal dynamics of BNF, and its consequences for seed yield with emphasis on growth and shoot allocation mechanisms. Trials were established in 23 locations across the US Midwest under four N conditions. Fertilizer reduced the peak of BNF up to 16% in applications at the full flowering stage. Seed yield declined 13 kg ha-1 per % increase in RAUR6. Harvest index accounted for the decline in seed yield with increasing BNF. This indicates the cost of BNF was met by a relative change in dry matter allocation against the energetically rich seed, and in favor of energetically cheaper vegetative tissue.

Differences between conventional and glyphosate tolerant soybeans and moisture effect in their discrimination by near infrared spectroscopy.

Previous studies showed that Near Infrared Spectroscopy (NIRS) could distinguish between Roundup Ready® (RR) and conventional soybeans at the bulk and single seed sample level, but it was not clear which compounds drove the classification. In this research the varieties used did not show significant differences in major compounds between RR and conventional beans, but moisture content had a big impact on classification accuracies. Four of the five RR samples had slightly higher moistures and had a higher water uptake than their conventional counterparts. This could be linked with differences in their hulls, being either compositional or morphological. Because water absorption occurs in the same region as main compounds in hulls (mainly carbohydrates) and water causes physical changes from swelling, variations in moisture cause a complex interaction resulting in a large impact on discrimination accuracies.

Measurement of single soybean seed attributes by near-infrared technologies. A comparative study.

Four near-infrared spectrophotometers, and their associated spectral collection methods, were tested and compared for measuring three soybean single-seed attributes: weight (g), protein (%), and oil (%). Using partial least-squares (PLS) and four preprocessing methods, the attribute that was significantly most easily predicted was seed weight (RPD > 3 on average) and protein the least. The performance of all instruments differed from each other. Performances for oil and protein predictions were correlated with the instrument sampling system, with the best predictions using spectra taken from more than one seed angle. This was facilitated by the seed spinning or tumbling during spectral collection as opposed to static sampling methods. From the preprocessing methods utilized, no single one gave the best overall performances but weight measurements were often more successful with raw spectra, whereas protein and oil predictions were often enhanced by SNV and SNV + detrending.

Development and characterization of food-grade tracers for the global grain tracing and recall system.

Tracing grain from the farm to its final processing destination as it moves through multiple grain-handling systems, storage bins, and bulk carriers presents numerous challenges to existing record-keeping systems. This study examines the suitability of coded caplets to trace grain, in particular, to evaluate methodology to test tracers' ability to withstand the rigors of a commercial grain handling and storage systems as defined by physical properties using measurement technology commonly applied to assess grain hardness and end-use properties. Three types of tracers to dispense into bulk grains for tracing the grain back to its field of origin were developed using three food-grade substances [processed sugar, pregelatinized starch, and silicified microcrystalline cellulose (SMCC)] as a major component in formulations. Due to a different functionality of formulations, the manufacturing process conditions varied for each tracer type, resulting in unique variations in surface roughness, weight, dimensions, and physical and spectroscopic properties before and after coating. The applied two types of coating [pregelatinized starch and hydroxypropylmethylcellulose (HPMC)] using an aqueous coating system containing appropriate plasticizers showed uniform coverage and clear coating. Coating appeared to act as a barrier against moisture penetration, to protect against mechanical damage of the surface of the tracers, and to improve the mechanical strength of tracers. The results of analysis of variance (ANOVA) tests showed the type of tracer, coating material, conditioning time, and a theoretical weight gain significantly influenced the morphological and physical properties of tracers. Optimization of these factors needs to be pursued to produce desirable tracers with consistent quality and performance when they flow with bulk grains throughout the grain marketing channels.