Crop Science

Soybean, a widely cultivated leguminous crop valued for its protein, amino acids, and oil, faces the challenge of maintaining protein levels, which have an inverse correlation with yield. Reducing leaf chlorophyll levels could increase seed protein levels without compromising yield; however, this is yet to be tested. Therefore, to understand the impacts of low chlorophyll mutations on soybean yield and seed composition, we screened and compared 25 low chlorophyll soybean mutants to their 11 dark green parents. PI548210 (Lincoln mutant) demonstrates a higher concentration of protein without affecting yield compared to its dark green parent PI548362 (Lincoln), suggesting it as a good candidate for further large-scale field trials. PI547555 (Y11/y11, Clark mutant) demonstrates a lower concentration of oil without impacting yield, alongside lower gross photosynthesis, but with chlorophyll levels in the pod and seed tissues that are comparable to its dark green parent PI548533 (Clark). These findings are consistent with the oil concentration of the soybean being influenced by pod and seed photosynthesis, which is correlated with pod height and row spacing. Chlorophyll levels in the leaf do not necessarily correlate with those in the pod and seed of low chlorophyll mutants, possibly due to substantially lower expression of chlorophyll synthesis genes in the pod and seed. SIGNIFICANCEO_LIPI548210 (Lincoln mutant), one of twenty-five low chlorophyll soybean mutants, demonstrates a higher concentration of soybean protein without affecting yield compared to its dark green parent (Figure 1 and Table 1). C_LIO_LIPI547555 (Y11/y11, Clark mutant), a low chlorophyll soybean mutant, demonstrates a reduced concentration of soybean oil without impacting yield, alongside lower gross photosynthesis in pod and seed tissues compared to its dark green parent (Figures 3 and Table 2). These findings suggest that the oil concentration of the soybean is influenced by pod and seed photosynthesis, which is in turn influenced by pod height and row spacing (Figure 2). C_LIO_LIChlorophyll levels in the leaf do not necessarily correlate with those in the pod and seed of low chlorophyll mutants, possibly due to substantially lower expression of chlorophyll synthesis genes in the pod and seed (Figure 5-6). C_LI O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=84 SRC="FIGDIR/small/744892v1_fig1.gif" ALT="Figure 1"> View larger version (55K): org.highwire.dtl.DTLVardef@4282dcorg.highwire.dtl.DTLVardef@9d565forg.highwire.dtl.DTLVardef@1918292org.highwire.dtl.DTLVardef@1359b1_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 1.C_FLOATNO Two low chlorophyll mutants are as healthy as their dark green parents. Lincoln and its low chlorophyll mutant, left; Clark and its low chlorophyll mutant, known as Y11/y11, right. It can be seen by eye that the plants have low chlorophyll (light green/yellow leaves) but a similar growth habit to their dark green parents. See Supplemental Figures 1-4 for contrast, where low chlorophyll mutants are stunted in growth compared to their dark green parents. C_FIG O_TBL View this table: org.highwire.dtl.DTLVardef@657ec9org.highwire.dtl.DTLVardef@166e75borg.highwire.dtl.DTLVardef@df23c7org.highwire.dtl.DTLVardef@1a60124org.highwire.dtl.DTLVardef@194ed96_HPS_FORMAT_FIGEXP M_TBL O_FLOATNOTable 1.C_FLOATNO O_TABLECAPTIONComparison of seed yield, weight, seed composition between low chlorophyll mutants and their dark green parents. ANOVA is used with linear mixed model (random effect = block, fixed effect = variety). Least squares mean is used to compare. For yield and seed composition, N=4 blocks. For leaf chlorophyll (SPAD), N=40. Yield is average yield per plant (g). n.s. = not significant. C_TABLECAPTION C_TBL O_FIG O_LINKSMALLFIG WIDTH=179 HEIGHT=200 SRC="FIGDIR/small/744892v1_fig3.gif" ALT="Figure 3"> View larger version (26K): org.highwire.dtl.DTLVardef@7a368aorg.highwire.dtl.DTLVardef@192b8f0org.highwire.dtl.DTLVardef@1abb738org.highwire.dtl.DTLVardef@89e978_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 3.C_FLOATNO Light response curve of low chlorophyll mutant (Y11/y11, PI547555) and its parent (Clark, PI548533). Rates of net and gross photosynthesis of low chlorophyll (white) and dark green parents (black) pods under field conditions. Each dot represents a value (n=4) {+/-}SE. We assumed that the seeds greatly inhibited the transmittance of light through the pod and used photosynthetic photon flux density for a single-side. C_FIG O_TBL View this table: org.highwire.dtl.DTLVardef@3f0528org.highwire.dtl.DTLVardef@16ba712org.highwire.dtl.DTLVardef@a5ab2aorg.highwire.dtl.DTLVardef@889254org.highwire.dtl.DTLVardef@3efa4f_HPS_FORMAT_FIGEXP M_TBL O_FLOATNOTable 2.C_FLOATNO O_TABLECAPTIONPod photosynthetic parameters for low chlorophyll mutant (Y11/y11, PI547555) and its parent (Clark, PI548533). Photosynthesis was measured 1 September through 15 September 2021 at the University of Illinois Energy Farm in Urbana, IL, USA. The statistical analysis was done using ANOVA with linear mixed model (alpha=0.05). N=4 {+/-} SEM for Clark and N=3 {+/-} SEM for Y11. C_TABLECAPTION C_TBL O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=130 SRC="FIGDIR/small/744892v1_fig2.gif" ALT="Figure 2"> View larger version (23K): org.highwire.dtl.DTLVardef@a36c26org.highwire.dtl.DTLVardef@1116c8forg.highwire.dtl.DTLVardef@ee5e61org.highwire.dtl.DTLVardef@1766712_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 2.C_FLOATNO Low chlorophyll mutant (Y11/y11, PI547555) and its parent (Clark, PI548533) differ in concentration of seed oil, which interacts with height of pod and row spacing. The box plots show the median (central line), the lower and upper quartiles (box) and the minimum and maximum values (whiskers). The statistical analysis was done using ANOVA with linear mixed model (n=3 blocks, alpha=0.05). Least squares mean is used to compare. N.s., non- significant in the analysis. A. Concentration of oil in low chlorophyll mutant seeds from the upper canopy decreased by 4% compared to the dark green parent (18.2% vs 19%) while there was no difference between them in the seeds from the lower canopy (20.2% vs 20.6%). B. Schematic layout of 2013 field setting showing two different row spacings. C. Concentration of oil in low chlorophyll mutant decreased by 2% in 38cm spacing (21.4% vs 22%) while there was no difference in 19cm spacing (21.3% vs 21.7%) in 2013 field. C_FIG O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=162 SRC="FIGDIR/small/744892v1_fig5.gif" ALT="Figure 5"> View larger version (22K): org.highwire.dtl.DTLVardef@68e508org.highwire.dtl.DTLVardef@94a6ccorg.highwire.dtl.DTLVardef@152a187org.highwire.dtl.DTLVardef@1eae137_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 5C_FLOATNO (greenhouse). Correlation between the level of leaf chlorophyll (x-axis: SPAD reading) and the level of immature pod or seed chlorophyll (y-axis, mg/g DW). Line represents the linear regression model. R-squared is a coefficient of determination, the percentage of the response variable variation that is explained by the linear model. Pod is labeled by the fresh weight of seeds it contained. A. Level of chlorophyll of 25-100mg pod (n=18). B. Level of chlorophyll of 100-200mg pod (n=17) . C. Level of chlorophyll of 25-100mg seed (n=17). D. Level of chlorophyll of 100-200mg seed (n=20). C_FIG O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=180 SRC="FIGDIR/small/744892v1_fig6.gif" ALT="Figure 6"> View larger version (28K): org.highwire.dtl.DTLVardef@167fd88org.highwire.dtl.DTLVardef@361472org.highwire.dtl.DTLVardef@786325org.highwire.dtl.DTLVardef@1b53855_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 6.C_FLOATNO Levels of gene expression in chlorophyll synthesis pathway. A. CHL common pathway genes; Glutamyl-tRNA reductase (GluTR). Glutamate 1- semialdehyde aminotransferase (GSA-AT). ALA dehydratase (ALAD). Uroporphyrinogen III synthase (UROS). Uroporphyrinogen III decarboxylase (UROD). Protoporphyrinogen IX oxidase (PPO). B. Mg branch; Mg-chelatase (Mgch). Magnesium-protoporphyrin IX monomethyl ester cyclase (MPEC). Protochlorophyllide reductase (POR). 3,8-divinyl protochlorophyllide a 8-vinyl-reductase (4VCR). Heme pathway; Ferrochelatase (FECH). Heme oxygenase (HO). Phytochromobilin synthase (HY). Data come from Severin et al (2010). RPKM, reads per kilobase per million mapped reads. DAF, days after flowering. The source seed is experimental line A81-356022 which was generated by introgressing G. soja (PI468916) into G. max (A81-356022). C_FIG

Understanding the genetic diversity and population structure of breeding materials is essential for developing stress-resilient cultivars. In tropical maize, where drought and low soil nitrogen (low N) severely limit productivity, continuous development of tolerant varieties remains a priority. This study assessed the genetic diversity and population structure of 250 doubled haploid lines (DHLs) derived from five drought- and low N-tolerant tropical populations. Genotyping was performed using mid-density DArTseq markers, yielding 3,305 high-quality SNPs for analysis. Results revealed a moderate level of diversity among the DHLs, with an average genetic distance of 0.39, a polymorphism information content (PIC) of 0.33, and a minor allele frequency (MAF) of 0.29. These values reflect substantial allelic variation, important for identifying complementary parental combinations in hybrid development. Discriminant analysis of principal components (DAPC) grouped the DHLs into five distinct clusters, largely corresponding to their source populations, although some admixture was observed. This indicates that while the genetic backgrounds of the source populations were mostly retained, recombination introduced useful variation. Overall, the clear population structure and high diversity observed among these DHLs provide a strong genetic foundation for future maize improvement. These lines represent valuable resources for heterotic group formation, hybrid development, and recurrent selection schemes aimed at enhancing drought and low nitrogen tolerance in tropical maize.

Peanut smut, caused by Thecaphora frezzii, is an important constraint to peanut production in Argentina, but quantitative estimates of yield losses across environments remain limited. We quantified the relationship between disease incidence and kernel yield using 922 observations from 26 field studies conducted in Cordoba, Argentina, between 2021 and 2025. Study-specific incidence-yield relationships were analyzed using linear regression, random-effects meta-analysis, and linear mixed-effects models. Peanut smut incidence was consistently associated with yield reduction across studies. The estimated damage coefficient ranged from 24.2 to 28.7 kg ha-{superscript 1} per 1% increase in disease incidence, corresponding to a relative yield reduction of 0.74-0.87% of attainable yield. In contrast, attainable yield varied markedly among studies, ranging from 1,370 to 5,409 kg ha-{superscript 1}. Although an exploratory segmented analysis suggested a breakpoint near 12% incidence, subsequent moderator analyses, study- specific regressions, and normalized response curves provided no evidence of a biologically meaningful change in the damage coefficient across incidence or yield classes. These results indicate that differences among environments were primarily associated with attainable yield rather than with changes in the magnitude of disease-associated yield loss. The resulting damage function provides a quantitative basis for yield-loss assessment and disease management in peanut.

Context. Barley production requires advanced knowledge of its response to changing environmental conditions in order to keep it competitive and sustainable. Aim. Advance in the understanding of barley phenology and foliar development under South American field conditions. Methods. 8 spring barley genotypes with differential phenology were studied in four field experiments under different temperature (through years and sowing dates) and photoperiod (through sowing dates) conditions. Time to anthesis, emergence to onset of stem elongation, stem elongation to anthesis, photoperiod response (PR) in these three traits, number of final leaves at anthesis (FLN) and phyllochron were measured. Key Results. Time to anthesis and its subphases were shorter in late plantings but under similar photoperiod, temperature increased them. Cultivars have differential responses but with magnitude interactions and not crossover ones. Cultivar effects defined PR with no interaction with year (temperature). Temperature and photoperiod affected FLN, phyllochron and their relationship with time to anthesis. Under the shorter photoperiod, FLN and phyllochron were negatively correlated, FLN was higher in the warmer year and positively correlated with time to anthesis while phyllochron was not affected by temperature and had no correlation with time to anthesis. Under longer photoperiod, phyllochron was higher in the warmer year and time to anthesis was positively correlated with both FLN and phyllochron. Conclusions. Cultivar basal thermal requirements and PR were consistent under the different studied conditions. Changes in temperature and photoperiod affected the relationship between time to anthesis, FLN and phyllochron suggesting that, although the three traits are arithmetically related, environmental conditions affect their balance.

Perennial grains represent a promising frontier for sustainable agriculture, but breeding progress is constrained by the accessibility of genotyping and the difficulty of evaluating complex traits expressed for multiple years after establishment across heterogeneous environments. Phenomic selection may help address these challenges by using inexpensive, scalable, high-dimensional phenotypes collected early in development, although the robustness of such predictions across breeding cycles remains uncertain. Here, we compared genomic selection and phenomic selection across two breeding cycles of Thinopyrum intermedium (intermediate wheatgrass; IWG; Kernza(R)), comprising approximately 2,280 individuals from maternal half-sib families evaluated across multiple field sites and years. We constructed relationship matrices from genomic markers and early-life stage phenomic data, including seed and leaf color (HSV), CropReporter multispectral reflectance and indices, and cycle-specific hyperspectral reflectance sensors. Genomic models provided the strongest predictions on average across all field traits in both cycles. Among phenomic predictors, leaf HSV was consistently the most informative, whereas CropReporter and hyperspectral data showed lower and more trait-dependent performance and seed HSV provided little predictive value. Genomic, leaf HSV, and CropReporter models transferred across breeding cycles with little apparent loss of predictive ability relative to within-cycle validation, demonstrating that their predictive signals were not restricted to a single breeding cycle. Early-life stage leaf HSV emerged as a practical, accessible tool for germplasm thinning and early-stage prioritization in perennial breeding programs. Despite limited similarity among relationship matrices, multi-relationship-matrix models rarely improved prediction beyond the stronger constituent single-relationship-matrix model. Together, these results show that early-life stage phenomic data provide reproducible information about agronomic performance expressed years later, but that predictor complexity and data integration do not guarantee improved prediction.

Tillering plasticity is a key adaptive trait in sorghum influencing resource use efficiency via a plants ability to adjust branching to neighbour density. Neighbour detection through red:far-red (R:FR) light sensing regulates this plasticity. While molecular pathways regulating tiller outgrowth are partly known, the genetic architecture underlying density-responsive tillering has not been resolved in any grass species. A sorghum diversity panel (n = 895) was evaluated over two growing seasons (2023 and 2024) with plant spacing ranging from 5 to 60 cm. A linear mixed model incorporating neighbour distance and tiller counts estimated genotype-specific response. GWAS was conducted on isolated plants (no neighbours within 60 cm) and on estimated responsiveness to neighbours. GWAS identified 52 baseline tillering QTLs and 50 for spacing responsiveness, with 10 overlapping, suggesting shared genetic control. Comparison with 41 R:FR pathway candidate genes revealed enrichment in responsiveness QTLs (5/50, 10%) versus baseline (0/52, 0%) (Fishers exact test, P = 0.025). Our model identified 40 unique density-responsive tillering QTL regions. Reducing genotype response to neighbour absence could be a selection target to develop water-efficient sorghum varieties where controlled architecture may be more valuable than natural plasticity.

The rejection of self-incompatible (SI) Brassica pollen is mediated by three signaling branches that function in parallel in the stigma. The recognition of SI pollen by the stigma S-Receptor Kinase (SRK) results in activation of the ARM-Repeat-Containing 1 E3 ubiquitin ligase (ARC1) which mediates the degradation of compatibility factors, the FERONIA (FER) and ANJEA (ANJ) receptor kinases that induces ROS accumulation to inhibitory levels and the M Locus Protein Kinase (MLPK) which may also be connected to ROS production. Arabidopsis self-incompatibility is regulated by SRK as well, but the signaling events downstream of SRK following SI pollen perception are less well-understood. In this study, we evaluated the requirements of FER, ANJ and HERCULES RECEPTOR KINASE 1 (HERK1) for SI pollen rejection in the transgenic Arabidopsis thaliana SI-Col-0{psi} srka-1 line. The{psi} srka-1 T-DNA disrupting the expression of the endogenous{psi} SRKA gene was crossed into SI-Col-0 to prevent any potential SRK transgene silencing. T-DNA mutants for FER and ANJ/HERK1 were then crossed into the SI-Col-0{psi} srka-1 line. Using standard assays for pollen-stigma interactions, the SI phenotypes were assessed for the SI-Col-0 fer, SI-Col-0 anj-1 and SI-Col-0 anj-1 herk1-1 lines. Our results presented here indicated that FER and ANJ are not required in the stigma for Arabidopsis SI pollen rejection, further providing evidence for a divergence in the SI downstream signaling pathway in Arabidopsis.

White lupin (Lupinus albus L.) is a cool-season grain legume with seed crude protein of 33-47%, competitive with soybean (Glycine max L.) meal. It also fixes nitrogen and mobilizes soil phosphorus. Because soybean is a summer crop, white lupin can occupy Southeastern winter fields as a complementary protein source. Breeding for seed protein is limited by the cost and throughput of reference phenotyping. To determine how each is best deployed, we compared the utility of near-infrared spectroscopy (NIRS)-based phenomic selection with genomic selection based on 246,847 SNPs from low-pass, whole genome sequencing in a panel of Auburn University breeding lines and USDA National Plant Germplasm System germplasm. A handheld NIR calibration against Dumas reference protein reached screening-grade accuracy (R2 = 0.81). Under common cross-validation, phenomic predictive ability was 0.93 and genomic was 0.12. The low genomic value was consistent with moderate heritability (H2 = 0.33) and strong genotype-by-year interaction. Beyond predictive ability, NIRS recovered superior accessions the strictest selection intensity, and 40 to 60 reference assays sufficed to calibrate the model. Handheld NIRS is a low-cost tool for protein calibration and early-generation screening, while genomic prediction remains suited to parental selection, together supporting a complementary strategy for legume breeding Plain Language SummarySoybean meal is the main protein source for livestock and fish farms in the United States. Because soybean is a summer crop, many Southeastern fields sit idle or grow low-value cover crops in winter. White lupin, a cool-season legume whose seeds are as protein-rich as soybean meal, makes a good complementary winter crop: it yields high-protein grain while serving as a cover crop that fixes nitrogen and frees up soil phosphorus for later crops. In our early-stage lupin breeding program, measuring seed protein by standard lab methods is slow and costly. We built a calibration that lets a handheld scanner estimate protein from light, and compared it with predicting protein from the plants DNA. The scanner gave accurate, low-cost protein screening from only about 40-60 lab tests, while DNA-based prediction remains suited to guiding parent selection. Used together, these tools offer breeders a practical path to develop high-protein white lupin. Core ideasO_LIHandheld NIRS provides screening-grade prediction of white lupin seed crude protein. C_LIO_LISpectra carried more usable protein signal than markers by measuring seed chemistry directly. C_LIO_LINIRS and genomic prediction serve different stages of a white lupin breeding program. C_LIO_LIAbout 40 to 60 reference assays sufficed to calibrate NIRS to near-full accuracy. C_LI

Tomato production, yield and fruit quality face major challenges due to several factors, including the complex polygenic inheritance of agronomically relevant traits, biotic and abiotic stresses, and increasingly stringent regulations limiting the use of phytosanitary products. In this context, bioinoculants have emerged as a sustainable strategy capable of enhancing yield without compromising fruit quality, conferring protection against different stresses and exerting a minimal or no impact on environment and human health. In this study, we evaluated the effects and the underlying mechanisms by which Streptomyces sp. N2A, an actinobacteria isolated from soybean rhizosphere, promotes seed germination, vegetative growth and yield in tomato, without modifying fruit quality. The obtained results demonstrated that the bacterial treatment significantly improved seedlin[g]s emergence and growth and development in vegetative stage. At harvest, yield was also significantly enhanced, mainly driven by increased individual fruit weight, which was positively correlated with a thicker pericarp in fruits from N2A-treated plants. Transcriptional analysis during fruit development revealed a coordinated induction of auxin and cytokinin signaling pathways before and after anthesis, providing a hormonal framework that underlies the promotion of pericarp growth. This study provides evidence of the beneficial effect of inoculation with Streptomyces sp. N2A on tomato yield and constitutes the first report describing the modification of fruit morphology and expression of genes involved in phytohormonal modulation during early growth and development, induced by a plant growth-promoting Streptomyces.

Genetic gains for yield and yield-contributing traits are low or stagnant in sorghum especially under low soil moisture environments which have contributed to a yield gap of 3.0 in Africa. Exploring the extent of variation for yield-determining traits in sorghum will effective variety design to boost production in drought-stressed environments. Therefore, the objective of this study was to determine genetic variability, heritability and genetic gains for agronomic and physiological traits in sorghum under varying drought stress conditions to guide cultivar and trait selection for breeding. The study was conducted as a three-way factorial treatment structure involving a genetically diverse panel of two hundred and twenty-five (225) sorghum genotypes which were grown under three drought conditions [i.e., non-stressed (NS), pre-anthesis drought stress (PrADS), and post-anthesis drought stress (PoADS)] and two environments (e.g., field and glasshouse environments) using a 15 x 15 alpha lattice design in two replicates. Data were collected on agronomic and physiological traits, namely: days to anthesis (DA), days to maturity (DM), plant height (PH), stay-green (SG), seed weight (TKW), biomass yield (BM), harvest Index (HI), grain yield (GY), leaf area (LA), leaf chlorophyll content (SPAD) and stomatal conductance (SC) and subjected to various statistical analyses. Combined analysis of variance showed highly significant (P < 0.001) genotype, drought condition and environment, and their interactions for most traits under assessment. Genotypic coefficient of variation (GCV) was lower than phenotypic coefficient of variation (PCV) for all traits. Heritability in the broad-sense (H2) was moderate for GY (40%) under PrADS condition, but high under NS (60%) and PoADS (65%) conditions. Similarly, high genetic advance was recorded for traits with high heritability. GY positively and significantly correlated with HI under NS (r = 0.88), PrADS (r = 0.62) and PoADS (r = 0.61). Other agronomic and physiological traits poorly correlated with GY. The following genotypes were selected based on high grain yield and suitable agronomic and physiological traits under NS conditions; DAN YARA (5.7 t/ha and SC = 335.5) and JARWA (GY = 5.6 t/ha, SC = 326.3); under PrADS CSRO1 (GY = 2.9 t/ha, SC = 275.2) and ICNSL2014-021-1 (GY = 2.7 t/ha, SC = 268.2) and under PoADS conditions DANYAR BANA (GY = 4.2 t/ha, SC = 237.2) and DAN YARA (3.9 t/ha. SC = 330.0). The selected genotypes with the desirable traits are useful genetic resources for breeding high-performing sorghum hybrids to boost sorghum productivity in drought-prone areas in Africa.

Optimum irrigation and fertilizer nitrogen (N) rates are important to improve crop yield at reduced environmental risks in the form of NO3-N leaching losses, without any financial loss. The study aimed to investigate the impact of rational irrigation and nitrogen management on wheat and maize crop yield vs. NO3-N leaching losses, with field experiments conducted at the experimental station, University of Agriculture Faisalabad, Pakistan, for two years, with wheat-fallow-corn seasons each year. Suction lysimeter were installed for collection of leachates while soil water balance was computed using the HYDRUS-1D model. We explored the various management strategies, including three irrigation and N levels (sub-optimal, optimal, and supra-optimal, referred to as I1, I2, and I3 for irrigation, and N1, N2, and N3 for nitrogen, respectively) for wheat and maize crops. The three irrigation levels were 325, 400, and 475 mm for wheat, and 375, 525, and 675 mm for maize crops. The three N-levels were 100, 130, and 160 kg ha-1 for wheat, and 220, 270, and 320 kg ha-1 for maize. The results indicated that increasing the irrigation and nitrogen levels significantly improved the growth and yield of both crops during both seasons. The highest grain yield of wheat (4.0 t ha-1) and maize (7.8 t ha-1) was observed with I3N3; however, I2N3 showed statistically no difference in yield, while showing significantly reduced (28.6%) annual NO3-N leaching losses of 23.8 kg ha-1, and the highest financial benefits of 780$. Sub-optimal levels of irrigation and N, though reduced the NO3-N leaching losses, caused significant yield losses, generally unacceptable to the farmers. Irrigation water use efficiency (WUEi) also improved by 12% in wheat and 20% in maize under I2 than that of the I3 level. Besides, considering economic profit, the highest value cost ratio (1.64 and 2.04 in wheat and maize, respectively) was achieved under the I2N3 treatment, as opposed to the other treatments. Based on comprehensive analysis, the I2N3 treatment is recommended for sustainable yield and minimal environmental risk in the wheat-maize cropping system. Moreover, it was observed that the rainy fallow period contributes 14.0-31.5% of the total NO3-N leaching losses. Further investigation is needed to minimize NO3-N leaching losses, especially during the rainy fallow period, by early maize sowing and increasing the efficiency of N fertilizer (such as fertilizer coating) under the flood irrigation system, to achieve the potential goals of sustainable productivity and environmental security.

Drought stress is the major yield limiting factor in upland rice production where the moisture availability is highly variable. Understanding and evaluating how upland rice responds to drought stress is critical to improving resilience and yield stability. In this study performance of sixteen upland rice varieties were evaluated under non-stressed, moderately stressed and highly stressed conditions. Drought stress was introduced by irrigating upland rice at 70% and 50% field capacity (FC) whereas non-stress treatment was irrigated at 100% FC. Irrigation in moderately stressed and highly stressed conditions was also withheld for six days at lateral crop stages to observe temporary wilting by inducing a stress interval. Data on agronomic traits of upland rice was collected in three experimental replications. Results indicated that performance of upland rice varieties was significantly altered under stress conditions and highest performance was observed under non-stressed conditions. Yield losses for short duration and long duration varieties ranged 35-60% and 24-62% under moderate stress whereas it ranged 43-78% and 52-73% under highly stressed conditions, respectively. Overall varieties Dawk Kha, Khao/ Sai and Dawk Pa-yawm, indicated higher stability under stressed conditions therefore, these long duration varieties could be used for obtaining better yields under diverse agroclimatic conditions and under unpredicted weather patterns. Short duration Ma-led-nai-fai and long duration Goo Meung Lung and Bow Leb Nahag could be used for acquiring traits for higher tillering and panicle bearing capacity. Short heighted varieties such as Jao Daeng, Sahm Deuan and Ma-led-nai-fai could be used in breeding for short heighted new varieties to overcome lodging concerns. Strong significant association of GMP, STI, MPRO, MHAR with grain yield under non-stressed, moderately stressed and highly stressed conditions indicated that these indices were appropriate for their use as selection criteria for drought resilience.

This study aims to investigate changes in protein secondary structures (-helix, -sheet, random coils, and -turn) and macronutrient distribution in different cool-season oat varieties and steam-pressure toasting durations using synchrotron-based mid-infrared (Mid-IR) spectroscopy and Fourier Transform Infrared spectroscopy (FTIR) imaging. All oat samples, provided by the Crop Development Center at the University of Saskatchewan, were harvested over three consecutive years (2018, 2019, and 2020). The first experiment compared four oat varieties (CDC Arborg, CDC Nasser, CDC Haymaker, and Summit), while the second examined CDC Nasser oats subjected to steam-pressure toasting (SPT) at 121 for 0, 30, 60, 90, and 120 minutes. FTIR chemical imaging revealed that carbohydrates, proteins and lipids in the four oat varieties were mainly concentrated in the endosperm, aleurone layer and embryo, crease region, and remained unchanged after SPT. Peak-fitting deconvolution of the Amide I band (1700-1600 cm-1) and subsequent quantitative analysis revealed that the four oat varieties exhibited broadly similar protein secondary structure profiles, with statistically significant but subtle variety effects detected for -helix (P = 0.026), -turn (P = 0.047), and the -helix to -sheet ratio (P = 0.048), however, -sheet and random coil proportions did not differ significantly among varieties. In contrast, SPT induced pronounced structural rearrangements, with significant increase in -sheet proportion (P = 0.003) and significant decreases in random coil content (P = 0.026). Notably, 30 minutes of toasting was sufficient to significantly increase -sheet and decrease the random coil contents. These changes are consistent with heat-induced protein denaturation and intermolecular -sheet aggregation, where thermal energy breaks the hydrogen bonds that stabilize the disordered random coil conformation, causing the unfolded polypeptide chains to reassemble into highly ordered -sheet aggregates. After SPT, the peak centers of Amide I and II bands shifted to lower wavenumbers and both bands broadened while their intensities were maintained, reflecting the reorganization of the remaining protein into -sheet aggregates rather than any loss of amide-active protein. These findings suggest that, although genotype has a relatively minor effect on the protein secondary structure of oats, hydrothermal treatments fundamentally reorganize the protein matrix from a disordered to an ordered conformation, which may have implications for protein digestibility, solubility, and nutritional function.

Cassava (Manihot esculenta Crantz) is a major staple crop across tropical and subtropical regions. Despite advances in genomic selection, delayed, non-flowering, and asynchronous flowering remain key bottlenecks in breeding programs. To better understand the molecular basis of flowering-time variation, we performed RNA sequencing across three genotypes with contrasting flowering phenotypes (early, late, and non-flowering) sampled at three developmental stages under contrasting light regimes in field conditions (natural light and three-hour night-break with white light). Comparative transcriptomic analysis revealed distinct gene expression patterns associated with flowering responses. Genotype comparisons with no light supplementation revealed stage-specific enrichment of biological processes. Light supplementation was associated with changes in the expression of key components of photoperiodic and circadian regulation, as well as pathways involved in flowering-time integration and hormone and sugar-related signaling. These findings suggest that coordinated changes across multiple biological pathways regulate flowering behavior in cassava. The candidate genes and expression patterns reported provide a foundation for functional studies and advance our understanding of molecular mechanisms governing flowering-time regulation in cassava.

Accelerating grapevine breeding for disease resistance and climate adaptation remains constrained by long generation cycles. We benchmarked genomic (SNP), phenomic (NIRS), and metabolomic (untargeted LC-MS) prediction for 24 agronomic traits in a biparental population phenotyped over three years. Seven statistical frameworks and four tissue x timepoint combinations (wood; vineyard leaves at budbreak and flowering; greenhouse leaves at flowering) were evaluated, together with feature-wise BLUPs across samples. Cross-year and cross-population analyses with two additional populations assessed temporal robustness and transferability. Genomic prediction was most accurate (up to r = 0.83), metabolomic prediction was intermediate (up to r = 0.59), and phenomic prediction was lowest (up to r = 0.39) despite its lower acquisition cost. Metabolite features were more heritable than NIR wavelengths, for which most unexplained variation remained residual under the fitted model. Multi-omics integration produced limited overall gains. These results support genomic selection as the primary approach, with metabolomic or phenomic screening considered only for traits and sampling designs that show reproducible predictive signal.

Photosynthesis is among the most consequential yet genetically complex traits in crop plants, and translating its natural variation into actionable genomic targets remains a central challenge for breeding climate-resilient varieties. To start addressing this, researchers are generating increasingly large, multi-environment field photosynthesis datasets. Yet, these data have been structurally under-analysed since their inception. Here we report the outcomes of the first dedicated hackathon focused on computational mining of such field data held in Accra, Ghana, in March 2026. Bringing together data scientists, plant physiologists, geneticists, and breeders from Europe and Africa, these interdisciplinary teams used photosynthetic data collected with hand-held fluorometers to genome-wide marker data across four crop species: cowpea (Vigna unguiculata), barley (Hordeum vulgare), common bean (Phaseolus vulgaris), and potato (Solanum tuberosum). Despite using different species and methods, independent teams identified the same three key findings. First, mechanism-informed feature engineering and dynamic modelling recover genetic signals that are not detected or discarded in standard analysis pipelines, resulting in traits with improved heritability and meaningful associations with yield. Secondly, machine learning methods proved effective at uncovering genetic associations, with temporally resolved features substantially outperforming single time-point measurements. Third, raw chlorophyll fluorescence and absorbance traces consistently contained more information and predictive power than the extracted parameters currently used. A defining feature of this event was having experimentalists and data scientists working together, enabling AI approaches to be grounded in domain knowledge and biological mechanisms rather than relying on data alone.

A strategy to improve agricultural water productivity is to increase water use efficiency (WUE) at the level of plant transpiration through genetic selection. This requires detectable genetic variability in WUE and the ability to phenotype and select plants with higher WUE within a population. A proxy for phenotyping leaf level WUE by measuring carbon isotope signature ({delta}13Cleaf) has been supported by theory and data in C4 species. However, the functional relationship of {delta}13Cleaf and WUE in C4 species can be driven by genetics and environment. Therefore, a wide survey of existing natural variation is needed to quantify the heritability and identify various genetic factors that influence {delta}13Cleaf and WUE. In this study a genome-wide association panel was used to quantify the heritability of {delta}13Cleaf. We measured {delta}13Cleaf across a population of 360 genetically diverse lines of the C4 species Sorghum bicolor with single nucleotide polymorphic (SNP) markers determined from whole-genome resequencing. This analysis was conducted on two independent field environments where heritability of {delta}13Cleaf was evident and was driven by small genetic effects from loci that were consistently identified across environments. Candidate genes are presented that offer insights on future targets to manipulate and explore the functional relationship between {delta}13Cleaf and WUEi in C4 plants.

Efficient nutrient and water management is crucial for enhancing crop productivity, soil health, and mitigating environmental losses in cereal cropping systems of semi-arid regions. A two-year field experiment was conducted to evaluate the effects of dairy manure annual application of 50 Mg ha-1 to maintain recommended fertilizer N, compared to sole urea application with two different irrigation regimes (100% and 75% ETc) on crop yield, water use efficiency, deep percolation, nitrate leaching, and soil quality within a wheat-fallow-maize rotation in Pakistan. Suction lysimeters installed at a depth of 1.2 m were used to collect nitrate-N leachates, while HYDRUS-1D was used to assess daily deep percolation losses. Results indicate that the interaction between manure and irrigation was significant for yield, nitrate-N leaching, and soil health. Manure with deficit irrigation showed wheat and maize yield of 4.36 and 7.80 Mg/ha, irrigation water use efficiency (WUEi) of 1.09 and 1.59 kg/ha/mm, respectively, with no significant increase observed with full irrigation; while a significant decrease was observed in the absence of manure, either with full irrigation or deficit irrigation. Manure with deficit irrigation averaged annual nitrate-N leaching of 17.45 kg/ha, while urea and manure with full irrigation averaged 11.46 and 55.59% increases in nitrate-N leaching losses, respectively, without any yield benefits. Our results indicate that deficit irrigation with manure produces optimum yield with reduced nitrate-N leaching risk and improved soil physical properties.

Accelerating photoprotective regulation to improve carbon assimilation is a promising strategy to increase crop productivity. Although rapid non-photochemical quenching (NPQ) relaxation has been validated as a target through metabolic engineering, it remains unclear whether conventional breeding has improved this trait. Here, we investigated whether more than a century of soybean breeding enhanced NPQ relaxation alongside light-saturated carbon assimilation and seed traits. We evaluated a historical panel of 24 soybean genotypes across vegetative and reproductive developmental stages by integrating NPQ relaxation, gas exchange parameters, xanthophyll-cycle pigment profiles, expression of key photoprotective genes (VDE, PsbS, and ZEP), seed number and seed weight. NPQ relaxation parameters were not consistently associated with genotype release year, seed number, or seed weight at either developmental stage. The only exception was the amplitude of the rapidly relaxing NPQ component (AqE), which was negatively correlated with all three variables during the reproductive stage. In contrast, genotype release year was positively associated with maximum net CO2 assimilation rate (Amax), maximum carboxylation rate of Rubisco (Vcmax), maximum electron transport rate (Jmax), seed number, and seed weight, while Amax and Vcmax were positively correlated with seed number and seed weight. These findings indicate that the greater photosynthetic capacity of modern genotypes was not accompanied by faster photoprotective response. Thus, photoprotective regulation has not kept pace with gains in photosynthetic capacity under field conditions. We conclude that rapid NPQ relaxation remains an important target for synchronizing photoprotection with the high photosynthetic capacity of modern soybean lines.

Adventitious root formation (ARF) is a critical trait for the cost-effective propagation of grapevines in commercial nurseries. Poor rooting ability can limit the use and adoption of new rootstocks derived from underutilized Vitis species, constraining breeding efforts largely to the traditional trio: Vitis riparia, V. rupestris, and V. berlandieri. Despite its agronomic relevance, the genetic basis of ARF remains poorly characterized across the broader Vitis genus. In this study, we evaluated 308 accessions representing 18 Vitis species over three growing seasons, quantifying rooting performance at two developmental stages, callus-stage and post-transplant, alongside root biomass, cutting weight, and a derived transplant-response index. We observed extensive phenotypic variation both within and across species, and species rankings depended on the trait considered. V. riparia, V. rupestris and V. californica ranked among the top five species for all four rooting traits, whereas V. cinerea and V. candicans ranked among the lowest for root weight and post-transplant rooting. V. arizonica and V. acerifolia rooted well at the callus stage but were intermediate after transplanting, and V. berlandieri was among the weakest at the callus stage yet intermediate for post-transplant rooting. Repeatability was moderate to high for root weight (0.74) and callus-stage rooting (0.66), and lower for post-transplant rooting (0.47), reflecting both genetic control and season-to-season variation. Between-species differences accounted for 68% of the genetic variance in callus-stage rooting but only 10% in cutting weight. Rooting was associated with the climate of each accession's wild site of origin: after removing differences among species, accessions originating from sites with lower dry-season precipitation rooted better and produced more root biomass. Genome-wide association analysis using 3.4 million SNPs identified 54 significant SNPs resolving into 18 independent loci across four traits, with root weight contributing 12 of them. Candidate genes in linkage with these loci include a mitogen-activated protein kinase, a SCARECROW-LIKE GRAS transcription factor, PASTICCINO1, expansin A1, an AP2/ERF-RAV1 transcription factor, a tandem array of caffeoyl-CoA O-methyltransferases, and several sugar, peptide and nitrate transporters, implicating auxin-linked cell proliferation, cell wall and lignin remodeling, and solute transport. Genomic and phenomic prediction models yielded moderate accuracies across traits and seasons; up to r = 0.67 for post-transplant rooting within a season and r = 0.65 for previously unevaluated accessions. Moreover, the integration of spectral and genotypic data further improved predictive performance. Prediction accuracy was essentially flat between 5,000 and 50,000 markers. This study establishes a foundational framework for the genetic improvement of grapevine rootstocks, promoting broader use of resilient, high-performing, and clonally-propagable germplasm in viticulture.