Crop Science

Variety mixtures provide a potential avenue in US cropping systems to improve yield stability and disease resistance. However, implementation of variety mixtures requires an understanding of the competitive dynamics of the crop. In this study, we examine the effects of plant competition both between and within plots through five unique experiments: 1) 5,000 diverse inbred lines in single-row plots, 2) hybrids in two-row plots developed from the above inbred lines, 3) over 4,000 hybrids measured in 141 locations in two-row plots as part of Genomes to Fields, 4) mixtures of two hybrids within a two-row plot planted across two years and five locations, and 5) mixtures of up to twenty hybrids in four-row plots in three locations. Across all experiments, we find that competitive interactions are extremely limited. Within inbred lines, height of the neighboring plot accounts for 1.2% of the variance in focal plot height. Similarly, neighbor height explains 1.7% of the variance in focal plot yield in hybrids developed from the inbred lines. The genetics of neighboring plots explains 1.55% of the variation in yield across 141 location-year environments, reinforcing the generally modest impacts of neighbor competition. In evaluating mixtures of hybrids in both two and four-row plots, we observe no yield penalty compared to conventional single hybrid plots, even with large height differentials of the hybrids included in the mixture or in mixtures of up to 20 hybrids within a plot. Finally, we observe that mixtures have more yield stability compared to conventional plots, highlighting a new avenue for increased stability in higher risk environments. The lack of yield penalty and stability benefits are promising for future investigations of mixtures that may complement each other in disease resistance or abiotic stress tolerance and increase overall yield stability in the field.

CONTEXTRapeseed is a globally significant oil crop, exhibiting highly plastic responses among seed yield components (seed number and weight). However, there remains a notable gap in knowing the distribution of quality traits among seed size categories and understanding how seed size and source-sink (S-S) ratio influence comprehensive seed quality traits. OBJECTIVEThis study investigated the effects of seed size and S-S ratio reduction on the quality traits of winter and spring rapeseed genotypes. METHODSThe experiments were carried out at field conditions in Valdivia, Chile, where seed yield, yield components, oil, protein, and element concentrations (P, K, S, Ca, Mg, B, Cu, Fe, Mn, Zn, and Na) were evaluated across five seed size categories; very small (< 1.4 mm), small (1.4-1.7 mm), medium (1.7-2.0 mm), large (2.0-2.36 mm), and very large (> 2.36 mm). Treatments included a control and a reduced S-S ratio (75% shading), which significantly increased seed weight (P < 0.05). RESULTSBoth genotype and seed size affected (P< 0.050) the quality traits. Larger seeds exhibited higher Mg and B concentrations, as well as lower K, Ca, Fe and Na. Shading affected seed size distribution, favouring a higher proportion of large seeds. Under the shading treatment, the small seed category reached 5% lower oil concentration, while protein seed concentration increases 6% in both genotypes. Principal component analysis highlighted the complex interaction between yield, yield components, and quality traits, since there was no clear separation between different seed size categories and S-S ratio treatments. CONCLUSIONThese results provide insights into the plasticity of rapeseed quality traits, highlighting their collective impact on nutrient profiles. SIGNIFICANCEThis information is helpful for optimising cultivation practices and informing breeding programmes aimed at improving seed quality, particularly in high-yielding environments susceptible to environmental stresses. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=90 SRC="FIGDIR/small/707178v1_ufig1.gif" ALT="Figure 1"> View larger version (34K): org.highwire.dtl.DTLVardef@19d16eforg.highwire.dtl.DTLVardef@4cc16forg.highwire.dtl.DTLVardef@12f741borg.highwire.dtl.DTLVardef@6fa37a_HPS_FORMAT_FIGEXP M_FIG C_FIG

This study evaluated the effectiveness of genomic selection (GS) in loblolly pine (Pinus taeda) using a two-generation closed breeding population and a genetically diverse Mainline population. Single-step genomic best linear unbiased prediction (ssGBLUP) models were used to include all phenotypic, genotypic, and pedigree information. Prediction accuracies of genomic estimated breeding values reached up to 0.70 for stem volume and stem straightness. Prediction accuracy showed a strong linear relationship with mean relatedness between training and validation populations (r > 0.92). Adjusting the scaling between genomic and pedigree relationship matrices improved model stability, increased prediction accuracy, and reduced bias in genomic estimated breeding values. Estimates of heritability and variance components from ssGBLUP were consistent with pedigree-based models, particularly when genomic relationships were properly scaled. Genomic selection had approximately 50% more genetic gain per year relative to conventional selection. Overall, these results demonstrate that GS can be effectively integrated into operational conifer breeding programs, given sustained investment in large, well-connected training populations with high-quality phenotypic data. We also outline the planned implementation of GS in the North Carolina State University Cooperative Tree Improvement Program to increase genetic gain.

CoverCress is a new winter annual oilseed crop developed from field pennycress within the past 20 years. Field pennycress is commonly considered to be self-pollinated but little basic research has been published and there is some misalignment of conclusions. Our experience working with pennycress plant growth in greenhouse and field conditions over the past 13 years suggests that outcrossing is uncommon. We conducted lab, greenhouse, and field experiments to strengthen the body of work. Pollen viability kinetics analysis showed that longevity of pollen viability is negatively impacted by increasing temperatures and by direct exposure to light. Samples treated at 4C declined to 50% viability in 12 hours while it took just 2.5 hrs at 37C, and 1.6 hrs in full sunlight on a cool early April day. Cross-pollination was absent among greenhouse-grown plants flowering inside an agitated plastic pollen-containment covering. Across greenhouse tests, high rates of cross-pollination occurred only in an emasculation treatment that rendered flowers male sterile and opened the pistil to cross-fertilization. Field trials designed to measure pollen flow distance using a trackable fae1 knockout reporter gene failed to show detectable movement of pollen under field conditions in two locations. This data strongly suggests that domesticated field pennycress may be considered a self-pollinated crop and managed as such.

The early 20th-century discovery of heterosis and the establishment of heterotic groups transformed maize (Zea mays L.) into a keystone of global agriculture. However, maize breeding faces two significant challenges: the gradual decline of general combining ability (GCA) variance within heterotic groups and the impracticality of testing all possible single crosses in the early stages of a breeding program. Here, we developed genomic best linear unbiased prediction (GBLUP)-based multi-kernel models, using additive and two alternative non-additive genomic relationship matrices, to estimate the variance components associated with the GCA of Stiff Stalk (SS) and Non-Stiff Stalk (NSS) heterotic groups and the specific combining ability (SCA) arising from their crosses. We further applied these models to predict the performance of untested single-cross combinations under varying levels of parental information. We showed that the SS and NSS groups retained significant GCA variance across traits in both early- and late-maturity groups. The SS group, in contrast, exhibited no detectable GCA variance in grain yield for the intermediate-flowering subset of hybrids, highlighting a limitation for future genetic improvement. Furthermore, our results showed that GBLUP-based multi-kernel models effectively identified superior hybrids when parental information was available. In the absence of this information, however, these models underperformed compared to covariance-based approaches. Both types of non-additive matrices produced similar results, affirming the robustness of the inferred genetic architecture. Overall, this study sheds light on the future use of US maize commercial germplasm and demonstrates how GBLUP-based multi-kernel models can improve the efficiency of hybrid breeding programs.

Neonicotinoid seed treatments protect maize during early growth but can induce phytotoxicity that intensifies during storage. Despite recognized genotypic variation in tolerance, standardized phenotyping methods are lacking. We evaluated nine commercial maize hybrids under three seed treatments (control, one neonicotinoid [1N], and two neonicotinoids [2N]) across two storage periods (0 and 6 months at 25 {degrees}C) using germination, accelerated aging, and cold tests. A Seed Treatment Tolerance Index (STTI) was analyzed through hierarchical clustering, principal component analysis, and multivariate analysis of variance. Results showed a significant triple interaction among genotype, seed treatment, and storage. Hybrids from female line A maintained STTI above 0.95, while female C hybrids showed germination reductions up to 48 percentage points and vigor losses up to 90 percentage points under 2N after six months. Tolerance was associated with hydrogen peroxide regulation by catalase and ascorbate peroxidase. The STTI proved a reliable tool for classifying genotypic tolerance, with direct applications for breeding programs and seed industry logistics.

Spinach (Spinacia oleraceae) is a principal vegetable crop commercially grown in Controlled Environment Agriculture (CEA). Recent research suggests that root morphological and architectural differences among crop species influence yield, resource use efficiency, and environmental stress tolerance. These root traits may be exploited to increase yield, promote efficient nutrient use, and mitigate environmental stressors. This study measured differences between various spinach cultivars in CEA systems to reveal morphological and anatomical variation. We grew three spinach cultivars with different reported growing rates ( Income, Darkside, and El-Majestic) under NFT hydroponic and substrate-based systems in a controlled greenhouse environment over 45 days with destructive harvests at days 15, 30, and 45. Supplemental light (250 {micro}mol/m2/s) with 12-hour photoperiod and periodic fertigation was used. Harvests included the collection of leaf and root biomass, and scanning of root systems in WinRhizo software, measuring ten variables. On day 45, root cross-sections from orders 1-5 were embedded in JB-4 resin, sectioned, stained, and analyzed for diameter, vasculature, and rhizodermis characteristics. Results indicate that in spinach, differences in root system morphology are linked to cultivation systems over cultivar identity. Vascular and root anatomical alterations are minor compared to morphological differences in response to the cultivation system. Hydroponic-style growth systems are associated with the proliferation of fine-root ideotypes compared with substrate-based conditions. Such findings affirm previous studies, which suggest plastic root morphology in response to growth systems, and may be used to help create more resilient, resource-efficient cultivars. HighlightsO_LIIn spinach, root system morphology differences are linked to cultivation systems. C_LIO_LIRoot vascular and anatomical alterations are minor in response to cultivation system. C_LIO_LIHydroponic growth systems are linked to fine-root ideotype proliferation in spinach. C_LIO_LIFine-root ideotype proliferation may be a breeding target for CEA spinach. C_LI

AimsHarnessing rhizosphere processes offers a valuable opportunity to optimize nutrient use efficiency in agroecosystems. In nutrient-limited soils, plants discharge part of photosynthate surplus via root exudation, including carboxylates, which may enhance mineral dissolution and nutrient mobilization. We aimed to assess how plant responses to nutrient limitation translated into changes in exudate profiles, and how these exudates, in turn, drive bioweathering across soils of contrasting mineralogy and weathering degree. MethodsWe conducted a hydroponic experiment with Lupinus albus grown in a phosphorus (P) gradient over seven weeks. We measured plant biomass and root traits, performed a metabolomics analysis and quantified seven carboxylates in root exudates using gas chromatography-mass spectrometry. To assess bioweathering across contrasted soil domains, we conducted batch dissolution tests with exudates using three soil horizons--each with distinct physicochemical properties: enriched in organic matter, iron oxides, or primary silicates. ResultsAt the intermediate level of P supply, shoot biomass was comparable to that under high P, but plants produced more root biomass and a higher total carboxylate exudation rate. Despite low carboxylate concentrations (<100 ppb), exudates promoted the dissolution of Ca, Mg, Si, Fe, P and K in all soils. Yet, the degree of element released varied among soil types. ConclusionThese findings highlight the importance of root exudates in enhancing mineral dissolution, with effects dependent on soil physicochemical properties. The results suggest that managing agroecosystems under moderate nutrient limitation could be a sustainable strategy to increase root-to-shoot ratios, enhance bioweathering and nutrient release in rhizosphere.

Current optimum contribution selection (OCS) implementations use point estimates of estimated breeding values (EBVs), potentially leading to suboptimal selections when individuals have uncertain genetic evaluations. We developed a framework assessing how EBV uncertainty affects OCS decisions through MCMC-based approaches using the COSMO optimizer in Julia, evaluated on Norway spruce (Picea abies, n=5,525) and Loblolly pine (Pinus taeda, n=926) populations. Agreement between point estimate (MAP-OCS) and MCMC-OCS was surprisingly low: mean overlap of only 26.6 (4.8) individuals in Norway spruce genotyped subpopulation and 14.1 (3.6) in full pedigree, with Loblolly pine intermediate at 16.0 (9.6). Despite this low individual-level agreement, selection frequency across MCMC iterations corresponded well with EBV rankings (Spearman{rho} = 0.782 for Norway spruce), confirming that higher-EBV individuals were preferentially selected under posterior uncertainty. To comprehensively quantify uncertainty impacts, we employed two complementary metrics: individual robustness scores measuring genetic gain stability upon candidate removal, and population-level contribution distribution metrics capturing concentration of genetic gain across selected individuals. Applying these metrics identified 25 high-risk individuals in Norway spruce and nine in Loblolly pine, and constrained exclusion of these individuals improved individual robustness by 16.5% in Loblolly pine (3.00% genetic gain loss) and 29.8% in Norway spruce (2.14% genetic gain loss). Our uncertainty-aware OCS framework successfully identifies unstable selections that may compromise long-term genetic gain, and we recommend assessing EBV uncertainty through posterior distributions and evaluating population-specific trade-offs when implementing uncertainty-aware selection strategies.

Heat-tolerant rice cultivars are essential for mitigating global warming impacts. Basal anther dehiscence length (BDL) is a promising visible morphological marker for heat tolerance through stable pollination. We investigated the effects of sowing date on anther morphology, pollination, and fertility under controlled high-temperature conditions (35, 37, or 39 {degrees}C at flowering). Three japonica cultivars-- Akitakomachi (early heading), Koshihikari (medium), and Hatsushimo (late)--were sown monthly over 3 months and grown in pots. At heading, the plants were exposed to the temperature treatments for 3 days, and the proportion of florets with [&ge;]10 germinated pollen grains on the stigma (GP10) and seed set were assessed. Among anther traits, BDL showed the greatest variation, with all cultivars from the second sowing exhibiting the shortest BDL. Analysis of variance revealed significant effects of genotype, sowing date, and their interaction on anther traits and fertility. Regression analysis indicated that fertility was associated with GP10, with BDL contributing significantly to GP10 in the late-heading Hatsushimo, together with maximum temperature at flowering. Thus, both genotype and environment shape anther morphology, pollination, and fertility, indicating that BDL plasticity and genotype-specific environmental responses must be carefully considered when using BDL as a breeding marker for heat tolerance. HighlightVariation in sowing date significantly affects anther morphology and heat tolerance in rice. Genotype-specific responses to the growing environment require careful consideration for reliable breeding assessments.

Breadfruit (Artocarpus altilis (Parkinson) Fosberg) is a culturally and nutritionally significant perennial crop of the Pacific Islands. National Tropical Botanical Gardens Kahanu Garden (Maui, Hawai i) maintains a breadfruit collection representing more than 150 traditional varieties, some unique or irreplaceable and requiring safety duplication to safeguard genetic diversity. However, aging trees exhibit variable vigor, potentially limiting clonal propagation outcomes. We assessed air layering as a strategy for conservation duplication, conducting 163 air-layer attempts across 26 priority accessions. We evaluated the influence of tree vigor, age, and branch characteristics on rooting success and survival to out-planting. Overall, 17% successfully rooted and 75% of those survived to out-planting, resulting in successful duplication of 16 of 26 at-risk accessions. Rooting success differed among vigor classes (33% for high-vigor trees; 11-16% for normal and feeble trees) and increased modestly with source tree age, while survival to out-planting declined with increasing age. Branch length and fruiting season were not associated with outcomes. These findings indicate that air layering can support conservation propagation in living collections, but success is strongly influenced by source tree age and condition. Initiating safety duplication while trees are physiologically robust is likely to improve long-term conservation outcomes.

Glufosinate-ammonium (GA) has been widely used in Midwestern fields, and in recent years a growing number of failures to control waterhemp [Amaranthus tuberculatus (Moq.) Sauer] have raised concerns about the potential evolution of resistance. The goal of this study was to investigate four independent cases of suspected resistance to GA in A. tuberculatus from Illinois using greenhouse, field, and transcriptomics studies. Greenhouse dose-response experiments revealed resistance ratios ranging from 2.2- to 3.4-fold based on survival and from 1.3- to 2.8-fold based on dry biomass relative to a susceptible population. A subsequent field study where one of the populations originated confirmed that twenty percent of treated plants survived the labeled GA field-recommended rate. Screening for other herbicide sites of action revealed that most populations showed reduced sensitivity to atrazine, glyphosate, and imazethapyr, surviving up to three times the field-recommended rates, and to a lesser extent, lactofen and fomesafen. Transcriptomic analysis of plants surviving GA revealed no resistance-associated mutations or differential transcript abundance in the plastidic and cytosolic isoforms of glutamine synthetase. Among the four suspected resistant populations, there were 182 genes differentially expressed relative to two susceptible populations. Different sets of genes were differentially expressed among the populations studied, with only one gene (upregulated relative to two susceptible populations) shared among all four. Many of the differentially expressed genes, including cytochrome P450s, glutathione S-transferases, glycosyltransferases, transporters, and transcriptional regulators, are commonly associated with metabolic resistance. Gene ontology enrichment analyses indicated significant overrepresentation of stress response, defense regulation, and secondary metabolism categories across the populations. Together, these findings provide evidence for the evolution of GA resistance in populations of A. tuberculatus in Illinois. While more in-depth studies are needed to fully characterize the underlying mechanisms, the consistent differential expression of metabolism-related genes and no indication of target-site mechanisms points to a potential metabolic basis for resistance.

O_LIClimate change is reshaping agriculture through both gradual shifts and increasingly unpredictable extremes. Plants cope using developmental plasticity and bet-hedging, but it is unclear how these biological strategies align with the ways farmers perceive and respond to climate risks. This study investigates: (1) whether farmers understand climate change as incremental trends or recurrent shocks, (2) how their adaptations parallel plant plasticity and bet-hedging, and (3) under which climate scenarios these adaptations best support yield stability. C_LIO_LIWe combined qualitative research and modelling by conducting fifty semi-structured interviews with farmers, agricultural associations and public administrators across three climatically distinct Italian regions, and by developing an agent-based stochastic simulation that represents farmer-like plasticity (delayed sowing) and bet-hedging (staggered sowing) under drought and flood scenarios. C_LIO_LIFarmers described climate change as both gradual transformation and intensifying volatility. Their adaptive responses - adjusting calendars, switching crops and diversifying production - closely aligned with plant strategies, though articulated in practical rather than scientific terms. Simulation results showed that plasticity enhanced yields under systematic shifts in conditions, whereas bet-hedging reduced losses in highly variable climates characterised by frequent transitions between extremes. C_LIO_LITogether, the qualitative and modelling findings demonstrate that plant and farmer adaptation logics converge in complementary ways. Plasticity supports performance under gradual change, while bet-hedging buffers unpredictability. These insights highlight the potential for co-designed tools that link plant traits, farmer decision-making and ecological risk, strengthening climate-resilient agricultural planning and improving communication between farmers, breeders and plant scientists. C_LI Societal Impact StatementClimate change is transforming agriculture through both gradual shifts and increasingly unpredictable extremes, challenging farmers ability to protect crops and livelihoods. This study brings together farmer experiences and plant adaptation strategies to explore how people and plants respond to similar climate pressures. By showing that farmers practices mirror plant plasticity and bet-hedging, our findings highlight opportunities to design climate-resilient agriculture that aligns biological traits with real-world decision-making. This work can inform plant breeders, extension services and policymakers seeking to support farmers through clearer communication, better risk-management tools and more adaptable crop varieties, ultimately strengthening resilience in food systems.

Plant architecture, the spatial configuration of stems, branches, leaves, and inflorescences underpins essential physiological functions such as light capture, assimilate partitioning, flowering, and ultimately, yield. In cassava (Manihot esculenta), architectural traits such us plant height, branching level, and plant shape are agronomically important yet remain underexploited in breeding. Here, a large-scale analysis was conducted using phenotypic and genomic data from more than 14,000 cassava accessions evaluated across 34 field locations in Nigeria between 2010 and 2021, encompassing the national breeding programs of the National Root Crops Research Institute and the International Institute of Tropical Agriculture. The study aimed to dissect the genetic architecture, environmental stability, and breeding relevance of four key traits: plant full height, height to first branching, the branching level number (BranchlevelNum) and plant shape. Phenotypic analyses across breeding stages revealed consistent variation in plant height, branching height, and branching intensity, reflecting the cumulative effects of selection and evaluation across environments. Broad-sense heritability estimates ranged from 0.41 to 0.72, with BranchlevelNum and Cylindrical shape exhibiting strong genetic control and weak correlations with yield components, indicating their suitability for independent improvement. Genome-wide association analyses identified significant loci associated with BranchlevelNum, including a major region on chromosome 2 and an additional locus on chromosome 13, collectively explaining approximately 11% of the phenotypic variance. Candidate genes within these regions included regulators of meristem activity and hormone-related pathways, supporting a developmental basis for branching variation. Genomic prediction accuracy for BranchlevelNum reached 0.44, comparable to values reported for key agronomic traits in cassava. These results demonstrate that branching-related architectural traits are genetically tractable, largely independent of yield, and amenable to genomic selection. The findings support the integration of BranchlevelNum and plant shape into ideotype-driven breeding frameworks aimed at improving flowering efficiency, canopy structure, and field performance in cassava. Author SummaryCassava is a major food crop, and its plant shape plays an important role in how easily it can be grown, harvested, and improved through breeding. Traits such as plant height, branching, and canopy form affect flowering, seed production, and field management, yet they have received much less attention than yield or disease resistance. In this study, we examined plant architecture using field and genetic data from more than 14,000 cassava plants grown across Nigeria over twelve years. We focused on key traits describing plant height, branching level, and overall plant shape. We found that branching level is strongly controlled by genetics, remains stable across environments, and can be predicted accurately using genomic data. We also identified specific regions of the cassava genome linked to branching behavior. Our findings show that plant architecture can be improved using modern breeding tools without compromising yield. Incorporating branching traits into breeding programs can help develop cassava varieties that flower more reliably and perform better in farmers fields.

Quinoa (Chenopodium quinoa Willd.) is a genetically diverse Andean crop valued for its nutrition and adaptability to varied agroclimatic conditions with potential for cultivation in European and Mediterranean, particularly on marginal lands. Low temperatures during early sowing can impair germination, while delayed sowing increases the risk of poor maturation due to unfavorable autumn weather. To assess the adaptation of quinoa to cold stress, we evaluated germination and phenotypic variation in 60 accessions from highland and coastal ecotypes across three sowing dates in South-Western Germany: late winter (S1), early spring (S2), and spring (S3). Cold stress in S1 delayed seedling-emergence and reduced emergence percentages, yet these plants produced the highest average seed yield per plot (64 g) compared to S2 (46 g) and S3 (35 g). Highland accessions showed earlier seedling-emergence and with higher emergence percentages, while coastal types matured earlier and gave higher yields across sowing dates. A complementary laboratory experiment assessed germination under cold (4.4 {degrees}C) and control (18.3 {degrees}C) conditions, using both manual scoring and image analysis via a Mask R Convolutional Neural Network, to track seedling growth. This confirmed the beneficial germination performance of highland accessions under cold stress, with strong agreement between manual and automated scoring. Our findings suggest that quinoa demonstrates resilience to cold stress with highland quinoa exhibiting superior germination traits, and early sowing, despite reduced emergence, can lead to higher yields. We conclude that combining favorable traits such as faster maturity and higher yield of coastal ecotypes with superior germination traits of highland accessions is a promising avenue for breeding improved quinoa varieties for cold climatic regions.

Under climate change, understanding how plants and crops respond to drought is essential for basic research in ecology and evolution, and improving agricultural resilience. One common method of simulating drought in experimental conditions is by applying polyethylene glycol (PEG) to plants. We investigated drought growth responses in Medicago lupulina (black medic) using PEG to simulate drought stress. We grew Medicago lupulina plants inoculated with Sinorhizobium meliloti in Magenta boxes under controlled conditions and randomly assigned them to one of three treatments: a control, PEG applied to the bottom (PEG added to the bottom-watering container of a magenta box), or PEG applied from the top (PEG poured over the growth media). After 60 days, we measured true leaf number, nodule count, and below- and above-ground dry biomass. PEG treatments significantly reduced above-ground growth, including total biomass and leaf number, but unexpectedly increased nodulation. Our results suggest that while PEG effectively simulates drought stress on above-ground growth parameters, it may not accurately simulate drought effects on rhizobial symbiosis. PEG treatments had no effect on below-ground biomass, suggesting that increased nodulation is not a result of increased plant investment in below-ground growth under simulated drought. We hypothesize that PEG, as a persistent liquid that plants do not absorb, created conditions favorable for nodulation. Overall, these results highlight the importance of interpreting PEG-simulated drought experiments with caution when assessing mutualistic interactions.

The self-incompatibility, perennial growth habit, large tree size, and long juvenility present challenges in applying traditional breeding approaches in almond (Prunus dulcis Mill. D. A. Webb). Moreover, nut and kernel traits in almond are mainly controlled by a large number of small-effect quantitative trait loci (QTLs) and improving complex traits through conventional breeding approaches is slow and often inefficient. Genome-wide selection represents a promising strategy to enhance the efficiency of cultivar identification and selection of superior parents in almond breeding programs by estimating the breeding values (BVs) at early maturity. The main aim of this study was to implement genomic (GBLUP) and pedigree-based (ABLUP) prediction approaches to estimate BVs to identify the superior parental candidates for improving nut and kernel traits in almond. Here, we estimated BVs for nine traits that are commonly used in the primary evaluation stage of the almond breeding using genomic data from 61 parents and phenotypic data of 15,281 progeny derived from 205 unique families. Breeding values obtained from both approaches showed a strong correlation (r [&ge;] 0.94) for all traits except shell seal (r = 0.87). The population structure analysis conducted using high-quality 90K single nucleotide polymorphisms (SNPs) indicated clear separation of the Californian, European and some old Australian almond cultivars, with considerable admixture across some cultivars. Following further validation, both prediction approaches could be useful in early identification of superior candidates. The slightly higher breeding values obtained using the GBLUP compared to the ABLUP approach suggest that accounting for within-family variations and realised genomic relationships can enhance prediction accuracy, reliability, and overall genomic prediction performance in almond.

Improving rice (Oryza sativa L.) yield requires a balanced enhancement of both sink size and source capacity. While many QTLs for sink size have been identified, only a few are known for source capacity, which is essential for achieving high yield. Here we identified qHP10 as a major QTL for increased photosynthetic rate by using chromosome segment substitution lines derived from a cross between the high-yielding indica cultivar Takanari and the average-yielding japonica cultivar Koshihikari. High-resolution mapping combined with CRISPR/Cas9-induced mutagenesis revealed that the causative gene underlying qHP10 is Mitogen-Activated Protein Kinase 4 (OsMPK4). A near-isogenic line carrying the OsMPK4Takanari allele (NIL-OsMPK4) had a 15-25% higher photosynthetic rate than Koshihikari. NIL-OsMPK4 also had higher stomatal conductance than Koshihikari but similar stomatal pore size and density, indicating that increased stomatal aperture increases photosynthetic rate. This enhancement is likely attributable to the down-regulation of OsMPK4 expression, which increases stomatal conductance and thus promotes CO2 uptake. Our findings demonstrate that OsMPK4 is a promising genetic target for increasing source capacity and, potentially, rice yield through molecular breeding. (175 words)

Lodging in sorghum presents a significant challenge for plant breeders due to the trade-off between lodging resistance and grain yield. Manually measuring lodging across thousands of plots is time-consuming, expensive, and error-prone, making selection for lodging resistance challenging in breeding programs. Unmanned Aerial Vehicle (UAV) derived metrics offer a potential high-throughput, cost-effective alternative for lodging phenotyping. This study developed a framework for predicting plot-level lodging from UAV imagery across 2,675 sorghum breeding plots. Multi-temporal canopy height data were collected at two critical time points: maximum crop height and at manual lodging assessment. Height percentiles were extracted from UAV derived point clouds generated using photogrammetric algorithms. These data were used to develop parametric, non-parametric, and ensemble prediction models, which were evaluated using three statistical metrics. The ensemble model, averaging predictions from all models, achieved the highest accuracy with Pearson correlations of r = 0.80-0.84 and lowest residual mean square error (RMSE=16-18), explaining 64-70% of variation in manual lodging counts. Model diagnostics and iterative refinement, including inspection of UAV imagery and dataset curation, had minimal impact on model performance, demonstrating the robustness of the approach. Model performance was consistent across sites, with minimal effects of stratified sampling on accuracy, confirming the ensemble approach as optimal for plot-level lodging assessment. This study demonstrates that integrated multi-temporal UAV imagery offers a practical alternative to labor-intensive manual evaluation methods by enabling high-throughput lodging assessment suitable for implementation in sorghum breeding programs.

Improving photosynthesis is a promising approach to enhance sugar beet productivity. However, genetic variation in leaf photosynthesis and its relationship with disease resistance remain underexplored. We evaluated 98 sugar beet genotypes representing different breeding categories, including commercial F1 hybrids, seed-parent lines, and pollinator lines, in Hokkaido, northern Japan. Leaf gas exchange was measured during early growth under field conditions around the infection period of Cercospora leaf spot (CLS). To account for fluctuating irradiance during large-scale phenotyping, we applied a multilevel mixed-effects light-response model to estimate genotype-specific photosynthetic characteristics. Substantial genotypic variations in photosynthetic characteristics were detected. F1 hybrids exhibited higher photosynthetic capacity than breeding lines, whereas differences among breeding categories were unclear due to large within-category variation. Some breeding lines exhibited photosynthetic rates higher than those of hybrids, indicating exploitable genetic resources within the present genetic panel. We did not detect statistically significant trade-off between leaf photosynthesis and CLS resistance among 98 genotypes; in a subset of 19 genotypes analysed in detail, the relationship was even synergistic. Our results highlight the genetic diversity of leaf photosynthesis and its category-dependent structure, and suggest that selection for enhanced photosynthesis can proceed without substantial trade-off with CLS resistance. HighlightLeaf photosynthesis of 98 sugar beet genotypes showed significant genetic variation and dependence on breeding category. Active photosynthesis incurred minimal trade-off with Cercospora leaf spot resistance.