Agronomy

Global demand for pseudocereals, including buckwheat, has surged in recent years due to their higher nutritional and pharmaceutical value than cereals and also due to them being a climate-resilient, gluten-free, and potential crop for combating cancer, type ll diabetes, and overcoming micronutrients hidden hunger problems that lack in cereals. Major efforts are needed to make its cultivation more popular by improving its quantitative and qualitative traits through crop genetics by adopting modern genetic, molecular, and mutational approaches, which also necessitate the induction of genetic variation for better yielding and improved varieties. In this experimental study, the induced mutant populations of widely recommended VL-7 and PRB-1 varieties of buckwheat were generated using different concentrations treatments of ethyl methane sulfonate (EMS). Investigation on induced phenotypical and genotypical variations in individual plants of M1 population of different treatments resulted in morphological and cytological mutant types affecting plant germination, survival, height and morphology, leaf morphology, flower morphology, growth period, chlorophyll and pigments abnormalities in leaves, leaf growth pattern, plant fertility, yield, and cytological aberrations. This experiment showed that plant survival decreased with the concentration of the mutagen doses. The lower doses resulted in dwarf varieties suitable for cultivation as they increased yield by having higher breaking force and lower lodging index over the tall plants. Studies on various quantitative parameters revealed the general effectiveness of intermediate doses and stimulatory effectiveness of lower and higher concentrations in M1 generation.

Globally, heat waves (HWs) have become more frequent, intense, and prolonged, with extreme temperatures that reduce quality or result in crop loss in wine grapes. Irrigation prior to or during HWs is one of the most common means of mitigating damage to vines and berries. However, the effect of this practice on flavonoids is not well established. Red wine quality is directly impacted by phenolics, including anthocyanins and proanthocyanidins (PAs). This study was conducted over three vintages (2019-2021) in a commercial vineyard to evaluate the impact of supplemental irrigation - applied before and during HWs - on winegrape chemistry in Cabernet Sauvignon. Results demonstrated that supplemental irrigation significantly reduced anthocyanin loss compared to a control treatment maintained at 60% evapotranspiration (ET), and that pre-HW irrigation can mitigate some of the deleterious effects on classes of flavonoids important to red wine quality. Furthermore, applying excessive water (3x, or 180% ET) had no additional beneficial effects on flavonoids relative to a moderate supplemental application (2x, or 120% ET).

BackgroundControlled-environment cultivation of medicinal cannabis (Cannabis sativa L.) typically optimizes light conditions to enhance the biosynthesis of pharmaceutically important metabolites like cannabinoids. Such experimental strategies may also influence other specialized metabolites like terpenoids, flavonoids, alkaloids, among others. Previous untargeted metabolomics studies testing short wavelength conditions like UV and blue light have shown that terpenoids and prenylated flavonoids in cannabis leaves respond differentially. However, since metabolomic studies in cannabis have so far mostly focused on floral cannabinoids, a comprehensive untargeted study into cannabis floral metabolome response to short wavelengths is currently lacking. ObjectivesOur study investigates the impact of short wavelength usage on cannabis specialized metabolism, and in particular the influence of UVB, UVA, and blue light on the cannabis floral flavonoid metabolome and associated glycosylation moieties. MethodsCannabis plants were grown under a white background light and exposed to supplemental UVB, UVA, or blue light during the generative phase of the cultivation cycle. Treatments were compared to a reference white background light without UV or blue light. Metabolites from floral tissue were extracted and analyzed via ultra-performance liquid chromatography-tandem mass spectrometry. A comparative metabolomics workflow was designed and used to characterize the floral flavonoid metabolome and associated glycosylation moieties. ResultsOur results demonstrate how short wavelengths differentially affect the metabolism of natural product compound classes including polyketides and phenylpropanoids/shikimates. Blue light induced flavonoids similarly to how UVB did, while both UVA and blue light specifically induced flavanones accumulation. UVB showed the strongest regulatory effect on flavonoids production and glycosylation patterns. ConclusionsUVB reshapes the cannabis floral flavonoid metabolome by selectively stimulating the accumulation and structural modification of flavonoids. Therefore, UVB application in cannabis cultivation represents a useful horticultural strategy to increase inflorescence medicinal quality without affecting cannabinoid levels.

Soybean (Glycine max [L.] Merr.) productivity is frequently compromised by soil-borne pathogens. Macrophomina phaseolina (Mp), the causal agent of charcoal rot, can produce important soybean yield losses especially when hot and dry weather prevails. Integrating biological control agents with chemical seed treatments represents a promising strategy for improving disease management. This study aimed to (i) assess the in vitro compatibility of Trichoderma koningiopsis with commercial fungicide seed treatments, and (ii) evaluate the field performance of T. koningiopsis, alone or combined with compatible fungicides, across three soybean growing seasons. Compatibility assays revealed fungicide-specific effects, with Acronis(R) classified as non-fungitoxic and Topseed Extra as moderately fungitoxic. Across field seasons, Mp inoculation reduced seedling emergence, while several seed treatments improved emergence compared to the inoculated control, however, treatment effects varied markedly among years. Disease severity did not differ significantly among treatments in any season, and yield responses were strongly modified by environmental conditions rather than treatment effects. Temperature-response assays showed that T. koningiopsis exhibited optimal growth between 28 to 30{degrees}C and complete inhibition above 40{degrees}C, indicating high thermal sensitivity. The results demonstrate that T. koningiopsis can be integrated with compatible fungicides and may enhance early stand establishment under favorable conditions, but its field performance is strongly limited by high temperatures. These findings highlight the importance of environmental conditions when biological seed treatments are used.

Pennycress (Thlaspi arvense L.) is an intermediate winter oilseed crop that has only recently been domesticated for agronomic use. Improving agronomic traits requires sources of genetic variation, and mutagenesis is frequently used to help overcome the limitations of natural populations. We investigate the impact of Ethyl methanesulfonate (EMS) on genetically effective cells (GECs) to characterize the intra-individual genetic variation of EMS mutagenesis in pennycress. We identified that pennycress contains at least 4 GECs which, when treated with EMS, create unique mutations across different branches within the same individual plant. We then propagated the M2 plants for whole genome sequencing, providing extensive characterization of the EMS mutation profile and developing a gene index as a resource for future reverse genetic screenings. Article SummaryPennycress is an emerging winter oil seed crop in the American Midwest. Domestication efforts have advanced rapidly through a combination of genetic techniques. One of the most successful methods has been the use of a mutant gene index, a large collection of pennycress seed where new genetic variation has been created through Ethyl methanesulfonate (EMS). EMS mutations are not uniform however, and a single treated seed can have wide genetic variation within the resulting plant. We investigate the role of genetically effective cells on EMS variation, and present the full EMS population as a resource for further pennycress domestication efforts.

Metribuzin is a versatile herbicide effective against various annual grasses and broadleaf weeds found in wheat fields. However, it can cause foliar damage to wheat, impacting plant health and yield. A clearer understanding of the genetic architecture associated with metribuzin tolerance is necessary to guide marker-based breeding strategies. This study evaluated 351 historic Gulf Atlantic Wheat Nursery (GAWN) wheat breeding lines representative of southern US soft red winter wheat (SRWW) germplasm. Field trials were conducted at Winnsboro (WN) and Baton Rouge (BR), Louisiana, in 2016 and 2017. Metribuzin was applied at specific growth stages[DN1.1], and tolerance was assessed based on visual foliar damage. Genomic data from 6,252 filtered single nucleotide polymorphism (SNP) markers were used to estimate narrow-sense heritability, conduct genome-wide association (GWAS), and assess genomic prediction accuracy using genomic best linear unbiased prediction (GBLUP). Broad-sense heritability ranged from 0.54 to 0.69 within environments and reached 0.77 across environments, while narrow-sense heritability ranged from 0.35 to 0.47, indicating moderate additive genetic control. No SNP surpassed the significance threshold, but genomic prediction (GP) showed moderate to strong predictive ability (PA) across environments, with the highest accuracy (r = 0.62) observed between BR17 and WN17. These results indicate that metribuzin tolerance in SRWW is primarily controlled by multiple small-effect loci and that GS provides a more effective breeding strategy than marker-assisted selection for improving tolerance in southern wheat germplasm.

Creeping bentgrass (Agrostis stolonifera) is a turfgrass species established on golf course surfaces but is criticized for high irrigation requirements. While genetic variation for water deficit stress tolerance exists between cultivars, the lack of defined critical soil water potential thresholds (Soil {Psi}crit) for this species complicates precise irrigation strategies and benchmarks for plant breeding. This study utilized a polyethylene glycol (PEG) infused agar-based system to simulate water potential reductions and determine the water potential threshold ({Psi}crit) for seedling root elongation. Creeping bentgrass cv Pure distinction seedlings were subjected to six water potentials ({Psi}) ranging from -0.36 MPa (no PEG applied) to -1.72 MPa. Daily digital imaging was used to measure root elongation over 5 days. Results across two experiments demonstrated that creeping bentgrass seedlings are highly sensitive to mild reductions in {Psi}. A reduction to -0.61 MPa significantly decreased root length and growth rates by over 50% compared to the control. Regression models predicted that a {Psi}crit of approximately -0.45 MPa reduced daily root growth by 25%, while upwards {Psi} of -1.0 MPa resulted in a 75% reduction of seedlings root growth. Furthermore, seedlings exposed to the lowest water potentials were predicted to require an additional 30 to 46 days to achieve the same root length as control plants. These findings establish specific {Psi}crit benchmarks for water deficit stress tolerance using a PEG-based system to induce dehydration. These methods can be used in breeding programs, and will help develop more accurate experiments examining the mechanisms of water deficit stress tolerance.

To meet the growing demand for precision and intelligent agricultural management, crop simulation models offer substantial potential for optimizing farm planting strategies. By simulating crop growth processes and assessing the effects of different management practices, these models provide a scientific basis for planting decision-making. In this study, the DSSAT model was first used to optimize the planting strategies of Farm X in 2023. Based on the optimized plans, the model was further applied to predict crop yields per unit area for 2024 and to establish the relationships among yield, planting density, and fertilizer application rate. Subsequently, SPSS was employed to develop a regression model describing the relationship among net profit per unit area, planting density, and fertilizer application rate. A genetic algorithm was then used to identify the optimal solutions under different scenarios, generating prescription maps for the optimal planting density and fertilizer application rate for each plot of Farm X in 2024. The results provide a scientific reference for the mechanized and automated implementation of field management practices and support the dual optimization of economic returns and resource use efficiency. This study not only conducted a systematic optimization of Farm X planting strategies for 2023, but also provided detailed predictions and optimized prescriptions for 2024 in a visual and practical form. The proposed approach offers a scientific decision-support tool for farm planting strategy formulation and lays a foundation for the intelligent and automated development of modern agriculture.

Genomic selection can increase the rate of genetic gain in crop breeding programs, but its effectiveness depends on the reliability of phenotypic data, the size and composition of the training population (TP), and the statistical model used to estimate genomic breeding values. These design choices are especially important in resource-limited breeding programs, where additional replication, larger TPs, and more extensive genotyping compete for the same resources. Using empirical data from a sweet sorghum [Sorghum bicolor (L.) Moench] breeding population, developed by CHIBAS, we evaluated the effects of phenotyping replication, TP size, training-validation genomic relatedness, and genomic prediction (GP) model on predictive ability (PA). Grain yield, plant height, stem weight, and total soluble solids were evaluated across three field environments. Few studies in sorghum have examined these factors together with comparable empirical rigor. Increasing replication improved genomic heritability and PA for all traits and environments, with the largest gains observed for grain yield. Larger TPs and increased training-validation genomic relatedness also improved PA, but their effects were most significant when phenotype estimates were based on multiple replicates. GP models showed largely comparable PAs across all evaluated traits. Different models produced similar PA, with a few exceptions. These findings provide practical guidance for optimizing genomic selection in resource-limited sorghum breeding programs. ARTICLE SUMMARYGenomic selection can accelerate breeding only when the phenotypes used to train prediction models have high reliability. Using a sweet sorghum breeding population evaluated in three Haitian field environments, we quantified how replication number, training population size, training-validation genomic relatedness, and prediction model affected genomic predictive ability for grain yield, plant height, stem weight, and total soluble solids. Replication increased genomic heritability and predictive ability for all traits, with the strongest effects for grain yield. Larger and more connected training populations improved prediction, mainly when replication was adequate. These results provide practical guidance for resource-limited breeding programs. Core ideasO_LIIn this empirical sweet sorghum breeding population, phenotyping replication was the dominant factor explaining variation in genomic predictive ability across traits and environments. C_LIO_LIThe benefit of larger training populations and greater training-validation genomic relatedness increased when phenotype estimates were based on more replicates. C_LIO_LIGrain yield, the most environmentally sensitive trait evaluated, showed the largest response to improved replication and training-population design. C_LIO_LIBayesian models, rrBLUP, and GBLUP showed similar predictive abilities across traits and environments, suggesting that phenotyping and experimental design may be more important than model complexity. C_LI

Polyphenols are compounds synthesized by plants as part of their chemical defense system to counteract biotic and abiotic stressors. These compounds share two key chemical characteristics: their aromatic groups make them insoluble in water, while hydroxy groups provide redox properties. These characteristics may explain how polyphenols interact with mitochondrial membranes (which are lipophilic) and participate in redox (electron scavenging) reactions of the electron transport chain, ultimately affecting ATP synthesis via oxidative phosphorylation. This interaction accounts for both the beneficial and adverse effects of polyphenols. However, no research has examined how hydroxyl groups or a lipophilic environment influence the biological activity of polyphenols. Therefore, this study aimed to explore the impact of hydroxy groups and a lipophilic environment on the biological activity of polyphenols. We tested four polyphenols (quercetin, naringenin, resveratrol, and gallic acid) with varying numbers of hydroxyl and other functional groups to determine how hydroxyl groups affect their biological activity (toxicity) in Saccharomyces cerevisiae. Additionally, we evaluated different fatty acids to understand how a lipophilic environment influences polyphenol biological activity. The results of this study support the two main ideas of our hypothesis: 1) a lipid solvent increases the toxicity of polyphenols, and 2) the molecule with the most hydroxyl groups is the most toxic (as seen with quercetin, which has five hydroxyl groups). Consequently, the increased toxicity of polyphenols in lipid solvents, along with their association with oxidizable groups, opens the door to the development of new technologies based on polyphenols.

Banana (Musa spp.) is a vital staple food and cash crop cultivated in over 140 countries, providing nourishment and livelihoods to more than 400 million people worldwide. In this context, Bhimkol (Musa balbisiana, BB genome), a diploid banana variety native to Northeast India holds significant nutritional and commercial value. Its high iron and nutrient content have already been commercially validated through products like Bhimvita and Bhimshakti, which utilize fresh fruit pulp as nutrient-rich food for infants. However, Bhimkol fruits typically contain 100-150 seeds, an undesirable trait for product development. The manual removal of these seeds significantly increases production time and labour costs. Furthermore, because bananas are recalcitrant to traditional breeding, there is a constant need for rapid in vitro transformation protocols. To address these challenges, as a proof of concept, our research aims to knockout the INNER NO OUTER (INO) gene, which is responsible for ovule development. Using CRISPR/Cas12a technology, we established an efficient and reproducible in vitro regeneration and transformation system using Embryogenic Cell Suspensions (ECS). The resulting CRISPR-edited plantlets exhibited various mutations, including insertions and deletions (INDELs) within the targeted INO gene. These INDELs resulted in frameshift mutations that triggered premature stop codons. While these genetic changes are expected to render the banana seedless, phenotypic verification is currently underway to confirm the absence of seeds in mature fruit. Significance StatementDespite its superior nutritional profile, the commercial viability of the Bhimkol banana (Musa balbisiana) is restricted due to abundance of seeds (100-150 per fruit). This study employs CRISPR/Cas12a-mediated knockout the INNER NO OUTER (INO) gene in Bhimkol and expected to develop seedless fruits. The resulting plantlets exhibit targeted indels that trigger frameshift mutations, effectively disrupting ovule developmental INO gene.

Structured AbstractO_ST_ABSContext and ObjectiveC_ST_ABSDelayed sowing can expose chickpea crops to stress during the critical period for yield determination, but the effect of yield components and phenology to grain yield variation is not well characterised in diverse germplasm under rainfed conditions. Identifying genetic resources for grain yield improvement requires integration of multi-environment trial and genomic analyses to disentangle direct yield effects from indirect effects of phenology. This study aimed to (1) characterise genotype by environment interaction patterns for grain yield, yield components and phenology across times of sowing and seasons, and (2) identify genomic regions associated with improved grain yield that are present in genebank accessions but absent from current Australian commercial cultivars. MethodsA diversity panel of 141 kabuli chickpea genotypes, including six commercial Australian cultivars and 135 genebank accessions, was evaluated across six rainfed trials at Narrabri, New South Wales over three seasons (2018 to 2020) under typical (MAIN) and delayed (LATE) sowing. Multi-environment trial analyses with factor analytic models partitioned genotype by environment interactions for grain yield, 100-seed weight, seed number, and thermal time to flowering, podding, and maturity. Haplotype block analysis identified high variance blocks associated with seed number, classified by their overlap with high variance thermal time to flowering blocks, to distinguish from effects mediated by phenology. Results and ConclusionsDelayed sowing reduced grain yield by up to 1.04 t ha-{superscript 1}, driven primarily by reductions in seed number rather than 100-seed weight. Accelerated phenology was a key component of adaptation among commercial cultivars. Four haploblocks with high block variance for seed number were identified across all six trials. SignificanceSeed number was the dominant driver of grain yield variation in this diverse kabuli chickpea panel. Targeted introgression of rare superior haplotypes from genebank accessions provides an opportunity to broaden the genetic base of Australian kabuli chickpea and improve yield through higher seed number, with relevance to chickpea production systems facing similar climate variability. HighlightsDelayed sowing reduced grain yield in diverse kabuli chickpea germplasm by up to 1.04 t ha-1 across three years and six trials in northern New South Wales. Seed number, not seed weight, was the dominant driver of grain yield variation, and a shorter phenological duration was associated with higher seed number. Across all six trials, haplotype block analysis identified four genomic regions in high linkage disequilibrium with high variance for seed number and low variance for flowering time. The accession FLIP 94 62C uniquely carried rare superior haplotypes at two chromosome 4 blocks, the haplotype at the 17.0 Mb block was the most superior haplotype in all trials while the haplotype at the 8.5Mb block was most superior only in the most heat stressed environment.

Glycosidic nitriles (GN) in barley are precursors to carcinogens formed during distillation, making GN reduction a critical breeding objective for malting and distilling industries. Measurement of GN is time-consuming. Grain must first be malted before GN can be quantified, and generally cannot be completed before selections must be made in a winter barley breeding program. Here, feasibility of same-season genomic selection against GN content was evaluated in elite Virginia Tech winter barley germplasm. In 2023, all 176 elite breeding lines screened for presence of GN were shown to be GN producers. A subset of 95 lines was then quantitatively measured for GN concentration to determine the genetic variability for the trait. Efficacy of genomic selection for GN was first assessed using a divergent selection approach on the remaining 81 predicted lines. The highest 16 and lowest 16 of the predicted lines were chosen for GN quantification. A significant phenotypic difference was found between the predicted high and low group means (0.8 ppm; P = 0.003). An additional 120 lines were quantified the following year to determine repeatability. GN exhibited moderate narrow-sense heritability (h2 = 0.42) and a high genetic correlation (r = 0.79) across years. Moderate predictive ability as was observed in cross-validation (range 0.38 - 0.61), and forward prediction using 2023 to predict 2024 (r = 0.39). A genome-wide scan did not identify any major-effect loci, suggesting GN content is polygenic, thus enabling same-season genomic selection to reduce GN content in this germplasm.

Sustainable agriculture has driven increased exploration of microbial inoculants as a promising strategy to boost plant growth for higher yield and enhance secondary metabolism to increase crop nutritional value. However, their influence on fruit-specific metabolites under field conditions remains understudied. This study investigated the impact of inoculating cranberry (Vaccinium macrocarpon) plants with Bacillus velezensis EB37 and Lachnum sp. EC5, applied individually and in combination, on cranberry fruit phytochemistry. Over two growing seasons (2019 and 2021), cranberries were collected from treated and control plots and analysed using untargeted and targeted LC-MS-based metabolomics. Multivariate analysis revealed no significant metabolomic differences due to treatments. However, samples clustered strongly by year of harvest, highlighting a pronounced environmental effect. Quantitative analysis of six representative phenolic compounds: chlorogenic acid, catechin, p-coumaric acid, phloridzin, myricetin, and quercetin, showed no statistically significant differences between treated and control cranberries. These findings indicate that microbial inoculation alone does not alter cranberry fruit metabolome, including phenolic levels, at field conditions. This study underscores how multiple factors, such as environmental conditions, can affect the outcome of microbial inoculation under field conditions and suggests that additional interventions may be required to achieve microbiome-based improvements in cranberry fruit quality.

Micro-dwarf tomato cultivars are increasingly considered for urban and controlled-environment agriculture due to their compact architecture and suitability for high-density planting. However, optimal canopy management strategies for these cultivars remain poorly defined. In this study, we evaluated the effects of different leaf removal intensities on leaf-level physiological performance, fruit yield, and fruit quality in three micro-dwarf tomato cultivars (Mohammed, Hahms Gelbe Topftomate, and Red Robin) grown under contrasting seasonal light conditions. Plants were subjected to low (15%), moderate (30%), or severe (90%) leaf removal, and leaf-level gas exchange was measured across canopy layers, along with yield and fruit quality assessments. Severe leaf removal (90%) increased carbon assimilation, transpiration, and stomatal conductance in middle and lower canopy leaves by up to approximately twofold compared with control plants, indicating improved light availability at the leaf level. However, these physiological enhancements did not consistently translate into higher yield, reflecting reduced whole-plant source capacity under excessive leaf removal. Low to moderate leaf removal (15-30%) generally increased or maintained yield and fruit number, whereas severe leaf removal reduced yield in Hahms Gelbe and Red Robin, particularly under low seasonal radiation. In contrast, Mohammed exhibited yield increases of up to 220% under low leaf removal and maintained increased yield even under severe leaf removal under high-light conditions. Fruit quality was largely unaffected by leaf removal, except for total soluble solids, which declined by approximately 12% under severe leaf removal across cultivars, consistent with sugar dilution under source limitation. Overall, these results demonstrate that optimal leaf removal in micro-dwarf tomatoes requires balancing improved canopy light distribution with maintenance of sufficient leaf area for carbon assimilation. Leaf removal thresholds are strongly cultivar- and light-dependent, emphasizing the need for cultivar-specific canopy management strategies in compact tomato systems and controlled-environment agriculture.

In this study, the critical gap in understanding how fonio responds to contrasting pedoclimatic conditions, both within and outside its traditional production areas was addressed. A multi-environment trial was carried out to identify high-yielding genotypes with either broad stability or specific adaptation, thereby enabling targeted varietal recommendations to support the expansion of fonio cultivation into new areas. Randomized complete block design was used in six environments with eleven genotypes to evaluate flowering and maturity times, and grain yield. The Additive Main effect and Multiplicative Interaction and the Genotype main effect and Genotype x Environment interaction biplots revealed a significant effect of the genotype-by-environment interactions on traits, with genotypes B12 and G31 identified as high-yielding, while genotypes M5 and M14 were revealed as early-flowering and maturing. Genotypes M14 and M15 were adapted to all environments and early maturing. Boukoumbe, known as the fonio production area in Benin, was the most desirable for earliness, while Ina was the most ideal for grain yield, proving that fonio could be cultivated in Sudanian and Sudano-Guinean areas. Factor analysis revealed precipitation, C:N ratio, soil pH and texture as the main environmental variables influencing the grain yield in fonio. Our findings contributed to selecting stable, adapted genotypes.

Herbicide resistance threatens effective weed control in modern agriculture, particularly in grass weeds such as Alopecurus myosuroides and Lolium multiflorum. Cinmethylin is a pre-emergence herbicide with a novel mode of action that inhibits plastidial fatty acid thioesterases (FATs), enzymes essential for fatty acid biosynthesis. Although no cases of field resistance to cinmethylin have been reported, its resistance risk has not been fully assessed. In this study, we biochemically characterized defined amino acid substitutions in FAT A and FAT B to evaluate their effects on cinmethylin inhibition profile. Some substitutions in FAT A reduced inhibition in vitro, with mutations at residue R171 causing the largest shifts in sensitivity. However, these highly resistant variants required multiple specific nucleotide polymorphisms and are therefore predicted to be unlikely to arise in weed populations. In FAT B, sensitivity shifts were generally moderate. Importantly, most substitutions that reduced cinmethylin sensitivity also impaired enzymatic activity, suggesting limited viability in planta. Overall, these results indicate that while theoretical target-site resistance mechanisms exist, the practical risk of rapid resistance evolution to cinmethylin is low, supporting its value for integrated grass weed management

Maximum utilization of existing genetic variability in a breeding program depends on the efficient classification of the inbred lines into heterotic groups, particularly under stress conditions. This study applied practical breeding approaches to determine the mode of genetic inheritance for Striga resistance and proposes a weighted heterotic grouping method based on the general combining ability of multiple traits (WHGCAMT) and compares its effectiveness with other existing methods in classifying the inbred lines into heterotic groups in Striga-infested and optimum environments. Using Diallel design IV, 300 crosses were generated from 21 inbred lines and 4 standard testers. The crosses, along with six checks, were evaluated in an 18 x 17 alpha lattice design with two replications at two locations, in both artificial Striga-infested and Striga-free environments. The inbred lines were genotyped using DArTtag SNP markers. Phenotypic and genotypic data were analyzed using R. Analysis of variance revealed significant mean squares for hybrid, general combining ability (GCA), specific combining ability (SCA) and their interactions with environment. Significant positive and negative GCA and SCA effects were detected for grain yield and other measured traits. However, a larger proportion of additive gene action than non-additive gene action was observed for grain yield and most measured traits. The analysis of molecular variance also showed substantial genetic differences within and between clusters. Except for HSCA, the mean grain yield between the inter-group and intra-group hybrids was significant for each method. Pairwise comparison of the inter- and intra-group hybrids of all the methods showed significant differences between the WHGCAMT and all other methods in most cases. WHGCAMT consistently produced higher-yielding inter-group hybrids and lower-yielding intra-group hybrids, achieving breeding efficiency improvements of 55.8%, 4.3%, 15.7%, and 11.4% over the HSCA, HSGCA, HGCAMT and molecular marker methods, respectively, under Striga infestation. Thus, WHGCAMT offers more precise, reliable and biologically meaningful heterotic groups among early-maturing maize inbred lines.

Far-red light (FR; 700-750 nm) is increasingly incorporated into controlled-environment lighting because it can improve photosynthetic efficiency when combined with comparatively shorter wavelengths. In long-day leafy crops such as spinach, however, FR may also promote the transition from vegetative to reproductive growth and thereby reduce marketable yield. Most studies have evaluated FR fraction, intensity or end-of-day exposure, whereas the developmental timing of FR has rarely been tested, particularly in spinach. Here, we evaluated six commercial spinach cultivars (Amador, Harp, Renegade, Responder, Rubino and Santa Cruz) in an indoor vertical farm under a common red-green-blue background (PPFD 260-264 {micro}mol m-{superscript 2} s-{superscript 1}, 12 h photoperiod, 24 {degrees}C) and four FR timing treatments: no FR (Control), FR throughout production (FullFR), FR during early development only (EarlyFR), and FR during late development only (LateFR). LateFR increased marketable fresh weight relative to Control (244 vs 224 g) and reduced flowering incidence, whereas far-red supplied during early development reduced fresh weight (158 g) and increased flowering. The magnitude of the timing response differed among cultivars: switching from EarlyFR to LateFR recovered 0 % fresh weight in Amador but 107 % in Renegade and Rubino, with the largest penalties occurring in otherwise bolt-resistant cultivars. EarlyFR also increased total chlorophyll and reduced the chlorophyll a:b ratio. These results show that FR response in spinach is strongly conditioned by developmental stage and cultivar. Although LateFR received more total far-red than EarlyFR, it behaved like the Control, indicating that the penalty was set by far-red timing rather than dose. Treatment differences in bolting and yield tracked an estimated phytochrome photostationary-state deficit during early development: a phytochrome-deficit model markedly outperformed a cumulative-dose model ({Delta}AIC = 441), and the deficit x cultivar interaction was strong (p < 0.001), with bolt-resistant cultivars losing most yield when far-red coincided with the early developmental window. We therefore propose that FR should be treated as a genotype-dependent management variable rather than as a fixed spectral input, with late application and bolt-resistant cultivars offering the most favourable combination for vertical-farm spinach production. Framed within the breeders equation, the close match between the trial and production environment and the scope for shorter breeding cycles indoors suggest that genotype and far-red timing can be optimised jointly to accelerate genetic gain.

Seaweed cultivation has recently gained increased attention in North-West Europe as a sustainable source of biomass for biobased products. However, yields need to increase to make the seaweed sector economically viable. To achieve this, higher yielding varieties can be bred but this requires variation for yield and yield-related traits among genotypes. To reliably select high-yielding genotypes, an understanding is required of how both within-farm and between-farm environmental differences affect phenotypes and how to identify simple and reliable proxies for yield. In this study we evaluated growth of nine Saccharina latissima genotypes on two farms, 12 km apart, within the same season. We observed a threefold difference in yield among genotypes, demonstrating the potential for improvement through selection and breeding. Blade thickness and blade size-related traits were strongly correlated with yield, highlighting their potential to serve as rapid and non-destructive proxies for yield, thereby accelerating selection. Furthermore, we demonstrated the importance of adequate replication in farm trials to improve genotype performance estimation by correcting for within-farm spatial variation. Moreover, phenotypic variation was most explained by the genotype and environment, highlighting the importance of both genotype and site selection. Although genotype by environment interactions (GxE) were significant, its contributions were small, indicating stable genotype ranking across farms. Overall, these results are promising for breeding improved S. latissima as it indicates that genotype performance is consistent across close by locations and that local S. latissima populations harbour substantial phenotypic variation that can be used to breed for increased yield. Highlights- Local genetic resources harbour substantial variation in yield and morphology for breeding. - Minor GxE allows for breeding across farms. - Blade thickness and blade size related traits are good predictors of yield. - Correction for on-farm spatial variation improves genotype performance estimation.