Effect of organic biostimulants on cannabis productivity and soil microbial activity under outdoor conditions.

In 2019 and 2020, we investigated the individual and combined effects of two biofertilizers (manure tea and bioinoculant) and one humic acid (HA) product on cannabis biochemical and physiological parameters and soil CO2 evolution under outdoor conditions. Our hypothesis was that HA would increase the microbial activity in the biofertilizers and synergy of both compounds would promote better plant performance and stimulate soil microbial activity. In 2020, the individual and combined application of biofertilizers and HA increased cannabis height, chlorophyll content, photosynthetic efficiency, aboveground biomass, and bucked biomass by 105, 52, 43, 122, and 117%, respectively. Impacts were greater under suboptimal growing conditions caused by planting delay experienced in 2020. In 2019, planting date occurred in-between the most favorable period and chlorophyll content and photosynthetic efficiency were the only parameters influenced by the application of biostimulants. The discrepancies between the two growing seasons reinforce the evidence of other studies that biostimulants efficacy is maximized under stress conditions. This study could not conclusively confirm that the combined use of biofertilizer + HA is a superior practice since affected plant parameters did not differ from application of the compounds singly. Similarly, only one biofertilizer + HA treatment increased soil microbial activity. More research is needed to define optimum rates and combinations of biofertilizer and stimulants for cannabis.

Aerial high-throughput phenotyping of peanut leaf area index and lateral growth.

Leaf area index (LAI) is the ratio of the total one-sided leaf area to the ground area, whereas lateral growth (LG) is the measure of canopy expansion. They are indicators for light capture, plant growth, and yield. Although LAI and LG can be directly measured, this is time consuming. Healthy leaves absorb in the blue and red, and reflect in the green regions of the electromagnetic spectrum. Aerial high-throughput phenotyping (HTP) may enable rapid acquisition of LAI and LG from leaf reflectance in these regions. In this paper, we report novel models to estimate peanut (Arachis hypogaea L.) LAI and LG from vegetation indices (VIs) derived relatively fast and inexpensively from the red, green, and blue (RGB) leaf reflectance collected with an unmanned aerial vehicle (UAV). In addition, we evaluate the models' suitability to identify phenotypic variation for LAI and LG and predict pod yield from early season estimated LAI and LG. The study included 18 peanut genotypes for model training in 2017, and 8 genotypes for model validation in 2019. The VIs included the blue green index (BGI), red-green ratio (RGR), normalized plant pigment ratio (NPPR), normalized green red difference index (NGRDI), normalized chlorophyll pigment index (NCPI), and plant pigment ratio (PPR). The models used multiple linear and artificial neural network (ANN) regression, and their predictive accuracy ranged from 84 to 97%, depending on the VIs combinations used in the models. The results concluded that the new models were time- and cost-effective for estimation of LAI and LG, and accessible for use in phenotypic selection of peanuts with desirable LAI, LG and pod yield.

Physiological and Molecular Traits Associated with Nitrogen Uptake under Limited Nitrogen in Soft Red Winter Wheat.

A sufficient nitrogen (N) supply is pivotal for high grain yield and desired grain protein content in wheat (Triticum aestivum L.). Elucidation of physiological and molecular mechanisms underlying nitrogen use efficiency (NUE) will enhance our ability to develop new N-saving varieties in wheat. In this study, we analyzed two soft red winter wheat genotypes, VA08MAS-369 and VA07W-415, with contrasting NUE under limited N. Our previous study demonstrated that higher NUE in VA08MAS-369 resulted from accelerated senescence and N remobilization in flag leaves at low N. The present study revealed that VA08MAS-369 also exhibited higher nitrogen uptake efficiency (NUpE) than VA07W-415 under limited N. VA08MAS-369 consistently maintained root growth parameters such as maximum root depth, total root diameter, total root surface area, and total root volume under N limitation, relative to VA07W-415. Our time-course N content analysis indicated that VA08MAS-369 absorbed N more abundantly than VA07W-415 after the anthesis stage at low N. More efficient N uptake in VA08MAS-369 was associated with the increased expression of genes encoding a two-component high-affinity nitrate transport system, including four NRT2s and three NAR2s, in roots at low N. Altogether, these results demonstrate that VA08MAS-369 can absorb N efficiently even under limited N due to maintained root development and increased function of N uptake. The ability of VA08MAS-369 in N remobilization and uptake suggests that this genotype could be a valuable genetic material for the improvement of NUE in soft red winter wheat.

Genotypic and phenotypic characterization of a large, diverse population of maize near-isogenic lines.

Genome-wide association (GWA) studies can identify quantitative trait loci (QTL) putatively underlying traits of interest, and nested association mapping (NAM) can further assess allelic series. Near-isogenic lines (NILs) can be used to characterize, dissect and validate QTL, but the development of NILs is costly. Previous studies have utilized limited numbers of NILs and introgression donors. We characterized a panel of 1270 maize NILs derived from crosses between 18 diverse inbred lines and the recurrent inbred parent B73, referred to as the nested NILs (nNILs). The nNILs were phenotyped for flowering time, height and resistance to three foliar diseases, and genotyped with genotyping-by-sequencing. Across traits, broad-sense heritability (0.4-0.8) was relatively high. The 896 genotyped nNILs contain 2638 introgressions, which span the entire genome with substantial overlap within and among allele donors. GWA with the whole panel identified 29 QTL for height and disease resistance with allelic variation across donors. To date, this is the largest and most diverse publicly available panel of maize NILs to be phenotypically and genotypically characterized. The nNILs are a valuable resource for the maize community, providing an extensive collection of introgressions from the founders of the maize NAM population in a B73 background combined with data on six agronomically important traits and from genotyping-by-sequencing. We demonstrate that the nNILs can be used for QTL mapping and allelic testing. The majority of nNILs had four or fewer introgressions, and could readily be used for future fine mapping studies.

Identification of quantitative trait loci associated with nitrogen use efficiency in winter wheat.

Maintaining winter wheat (Triticum aestivum L.) productivity with more efficient nitrogen (N) management will enable growers to increase profitability and reduce the negative environmental impacts associated with nitrogen loss. Wheat breeders would therefore benefit greatly from the identification and application of genetic markers associated with nitrogen use efficiency (NUE). To investigate the genetics underlying N response, two bi-parental mapping populations were developed and grown in four site-seasons under low and high N rates. The populations were derived from a cross between previously identified high NUE parents (VA05W-151 and VA09W-52) and a shared common low NUE parent, 'Yorktown.' The Yorktown × VA05W-151 population was comprised of 136 recombinant inbred lines while the Yorktown × VA09W-52 population was comprised of 138 doubled haploids. Phenotypic data was collected on parental lines and their progeny for 11 N-related traits and genotypes were sequenced using a genotyping-by-sequencing platform to detect more than 3,100 high quality single nucleotide polymorphisms in each population. A total of 130 quantitative trait loci (QTL) were detected on 20 chromosomes, six of which were associated with NUE and N-related traits in multiple testing environments. Two of the six QTL for NUE were associated with known photoperiod (Ppd-D1 on chromosome 2D) and disease resistance (FHB-4A) genes, two were reported in previous investigations, and one QTL, QNue.151-1D, was novel. The NUE QTL on 1D, 6A, 7A, and 7D had LOD scores ranging from 2.63 to 8.33 and explained up to 18.1% of the phenotypic variation. The QTL identified in this study have potential for marker-assisted breeding for NUE traits in soft red winter wheat.

Validation and Characterization of Maize Multiple Disease Resistance QTL.

Southern Leaf Blight, Northern Leaf Blight, and Gray Leaf Spot, caused by ascomycete fungi, are among the most important foliar diseases of maize worldwide. Previously, disease resistance quantitative trait loci (QTL) for all three diseases were identified in a connected set of chromosome segment substitution line (CSSL) populations designed for the identification of disease resistance QTL. Some QTL for different diseases co-localized, indicating the presence of multiple disease resistance (MDR) QTL. The goal of this study was to perform an independent test of several of the MDR QTL identified to confirm their existence and derive a more precise estimate of allele additive and dominance effects. Twelve F2:3 family populations were produced, in which selected QTL were segregating in an otherwise uniform genetic background. The populations were assessed for each of the three diseases in replicated trials and genotyped with markers previously associated with disease resistance. Pairwise phenotypic correlations across all the populations for resistance to the three diseases ranged from 0.2 to 0.3 and were all significant at the alpha level of 0.01. Of the 44 QTL tested, 16 were validated (identified at the same genomic location for the same disease or diseases) and several novel QTL/disease associations were found. Two MDR QTL were associated with resistance to all three diseases. This study identifies several potentially important MDR QTL and demonstrates the importance of independently evaluating QTL effects following their initial identification.

Cyberbiosecurity: A New Perspective on Protecting U.S. Food and Agricultural System.

Our national data and infrastructure security issues affecting the "bioeconomy" are evolving rapidly. Simultaneously, the conversation about cyber security of the U.S. food and agricultural system (cyber biosecurity) is incomplete and disjointed. The food and agricultural production sectors influence over 20% of the nation's economy ($6.7T) and 15% of U.S. employment (43.3M jobs). The food and agricultural sectors are immensely diverse and they require advanced technologies and efficiencies that rely on computer technologies, big data, cloud-based data storage, and internet accessibility. There is a critical need to safeguard the cyber biosecurity of our bio economy, but currently protections are minimal and do not broadly exist across the food and agricultural system. Using the food safety management Hazard Analysis Critical Control Point system concept as an introductory point of reference, we identify important features in broad food and agricultural production and food systems: dairy, food animals, row crops, fruits and vegetables, and environmental resources (water). This analysis explores the relevant concepts of cyber biosecurity from food production to the end product user (such as the consumer) and considers the integration of diverse transportation, supplier, and retailer networks. We describe common challenges and unique barriers across these systems and recommend solutions to advance the role of cyber biosecurity in the food and agricultural sectors.

Using Maize Chromosome Segment Substitution Line Populations for the Identification of Loci Associated with Multiple Disease Resistance.

Southern Leaf Blight (SLB), Northern Leaf Blight (NLB), and Gray Leaf Spot (GLS) caused by Cochliobolus heterostrophus, Setosphaeria turcica, and Cercospora zeae-maydis respectively, are among the most important diseases of corn worldwide. Previously, moderately high and significantly positive genetic correlations between resistance levels to each of these diseases were identified in a panel of 253 diverse maize inbred lines. The goal of this study was to identify loci underlying disease resistance in some of the most multiple disease resistant (MDR) lines by the creation of chromosome segment substitution line (CSSL) populations in multiple disease susceptible (MDS) backgrounds. Four MDR lines (NC304, NC344, Ki3, NC262) were used as donor parents and two MDS lines (Oh7B, H100) were used as recurrent parents to produce eight BC3F4:5 CSSL populations comprising 1,611 lines in total. Each population was genotyped and assessed for each disease in replicated trials in two environments. Moderate to high heritabilities on an entry mean basis were observed (0.32 to 0.83). Several lines in each population were significantly more resistant than the MDS parental lines for each disease. Multiple quantitative trait loci (QTL) for disease resistance were detected for each disease in most of the populations. Seventeen QTL were associated with variation in resistance to more than one disease (SLB/NLB: 2; SLB/GLS: 7; NLB/GLS: 2 and 6 to all three diseases). For most populations and most disease combinations, significant correlations were observed between disease scores and also between marker effects for each disease. The number of lines that were resistant to more than one disease was significantly higher than would be expected by chance. Using the results from individual QTL analyses, a composite statistic based on Mahalanobis distance (Md) was used to identify joint marker associations with multiple diseases. Across all populations and diseases, 246 markers had significant Md values. However further analysis revealed that most of these associations were due to strong QTL effects on a single disease. Together, these findings reinforce our previous conclusions that loci associated with resistance to different diseases are clustered in the genome more often than would be expected by chance. Nevertheless true MDR loci which have significant effects on more than one disease are still much rarer than loci with single disease effects.

Fine mapping of a quantitative resistance gene for gray leaf spot of maize (Zea mays L.) derived from teosinte (Z. mays ssp. parviglumis).

KEY MESSAGE: In this study we mapped the QTL Qgls8 for gray leaf spot (GLS) resistance in maize to a ~130 kb region on chromosome 8 including five predicted genes. In previous work, using near isogenic line (NIL) populations in which segments of the teosinte (Zea mays ssp. parviglumis) genome had been introgressed into the background of the maize line B73, we had identified a QTL on chromosome 8, here called Qgls8, for gray leaf spot (GLS) resistance. We identified alternate teosinte alleles at this QTL, one conferring increased GLS resistance and one increased susceptibility relative to the B73 allele. Using segregating populations derived from NIL parents carrying these contrasting alleles, we were able to delimit the QTL region to a ~130 kb (based on the B73 genome) which encompassed five predicted genes.

The suitability of teff flour in bread, layer cakes, cookies and biscuits.

A niche market in alternative foods has emerged in response to interest in a health conscientious diet. The purpose of this study was to evaluate the baking characteristics of teff to determine whether teff could produce satisfactory baked products. Cakes, cookies, biscuits and bread were made in triplicate from composites of wheat flour with 0, 10, 20, 30, 40 and 100% teff flour. Objective tests on size, shape, color and texture were used to evaluate the quality of the baked products. Increases in percent teff resulted in decreases in bread and cake volume (p > 0.05). The fracture strength of the cookies were not significantly different (p > 0.05) but spread was significantly greater for cookies made with 40% and 100% teff flour (p ≤ 0.05). There was also significant difference (p ≤ 0.05) in biscuit height and color among teff treatments. Overall, this study showed that teff flour is best suited for use in cookies and biscuits.

The Spread of a Released Clone of Gibberella zeae from Different Amounts of Infested Corn Residue.

Corn residue is a significant source of inoculum for epidemics of Fusarium head blight (FHB) in wheat and barley, but little is known about the influence of different amounts of corn residue on FHB. We monitored the spread of a released clone of Gibberella zeae (Fusarium graminearum), causal agent of FHB, from small 0.84-m-diameter research plots containing 45, 200, or 410 g of infested corn stalk pieces in winter wheat and barley fields in Virginia over 3 years (2008 to 2010). The fungus was recaptured through the collection of wheat and barley spikes at 0 and 3 m from the source and the released clone was identified in heterogeneous background populations using amplified fragment length polymorphisms. Results showed a slightly greater intensity of recovery of the clone at a greater distance when more infested residue was present. Plots containing larger amounts of inoculum (410 g) generally resulted in a smaller decline of recovery of the clone at 3 m from the source, indicating a greater spread from the larger inoculum source. The clone was also recovered at distances ≥18 m from inoculum sources. Larger amounts of corn residue generally had less influence on clone recovery in plots containing a moderately resistant wheat cultivar than those containing a susceptible wheat cultivar.