IntroductionThe fodder crisis is widening due to changing socio-economic preferences and a decline in the area under fodder cultivation. Therefore, there is an immediate need to explore the potential of dual-purpose crops for both food and fodder production. This study evaluated the effects of nitrogen levels, planting geometry, and harvesting stages on the productivity and quality of barnyard millet fodder.MethodsA field experiment was conducted at the Zonal Agricultural Research Station (ZARS), University of Agricultural Sciences (UAS), Gandhi Krishi Vignana Kendra (GKVK), Bengaluru, during August–November in 2024 and 2025. The experiment was laid out in a factorial randomized complete block design (RCBD) with three replications. The 12 treatment combinations comprised three nitrogen levels (N1: 40 kg N ha-1, N2: 60 kg N ha-1, and N3: 80 kg N ha-1), two planting geometries (P1: 30 × 10 cm and P2: 22.5 × 10 cm), and two harvesting stages (H1: earhead emergence and H2: physiological maturity) .ResultsApplication of 80 kg N ha-1 produced the highest green fodder yield (15,731 kg ha-1) and dry fodder yield (3,969 kg ha-1), followed by 60 kg N ha-1, whereas the lowest yields were recorded with 40 kg N ha-1. Closer spacing (22.5 × 10 cm) significantly increased biomass production, producing 14,999 kg ha-1 green fodder and 3,601 kg ha-1 dry fodder compared with 30 × 10 cm spacing. Harvesting at earhead emergence resulted in the highest green fodder yield (16,263 kg ha-1), whereas harvesting at physiological maturity produced the highest dry fodder yield (3,602 kg ha-1). Crude protein concentration was higher at earhead emergence (8.17%), while crude fiber concentration increased at physiological maturity (32.29%). Planting geometry did not significantly influence the qualitative fodder parameters.DiscussionIncreasing nitrogen application from 40 to 80 kg N ha-1 progressively improved fodder productivity, while closer planting enhanced biomass production. Early harvesting at earhead emergence favoured crude protein concentration and green fodder yield, whereas harvesting at physiological maturity increased dry matter production and crude fiber concentration. Overall, closer spacing (22.5 × 10 cm) combined with 80 kg N ha-1 is recommended for improving fodder productivity, while the choice of harvesting stage can be adjusted according to the desired balance between yield and fodder quality.
Coffee husk composting is constrained by high lignocellulose content, slow decomposition, and residual phytotoxicity. Whether microbial inoculation can accelerate this process while producing a horticultural growing medium remains unclear. We compared coffee husks composted with a commercial microbial agent (a consortium of photosynthetic bacteria, lactic acid bacteria, yeast, filamentous fungi, and actinomycetes) (CHM) versus without (CH) over 180 days. The CHM treatment reached a higher peak temperature (55.6 °C vs. 43.5 °C) and at the end of composting achieved a numerically greater seed germination index (93.2% vs. 71.2%), indicating enhanced maturation and reduced phytotoxicity. High throughput sequencing showed that CHM did not drastically alter overall microbial α diversity but the final compost exhibited a marked reduction in the relative abundance of the genus Fusarium compared to CH. Beneficial bacterial genera such as Pseudomonas, Sphingomonas, and Alcaligenes showed a non-significant but consistent trend toward enrichment in CHM. When the mature CHM compost was blended with vermiculite, perlite, and decomposed cow manure, blends with lower compost inclusion (1:5 or 1:3 volume ratio of CHM compost to other components) supported tomato seedling growth comparable to a conventional peat based medium. These results demonstrate that microbial inoculation promote a more intense thermophilic phase and enhances final maturity in coffee husk composting, yielding a product with potential to partially substitute for peat in horticultural substrates. This approach offers a practical strategy for recycling coffee processing byproducts into a compost-based growing medium component.
Sesame is an important oilseed crop, but its germination stage growth is increasingly limited by heat stress under climate warming. However, the molecular responses underlying heat tolerance in sesame germination stage remain unclear. In this study, a heat-tolerant genotype (G14) and a heat-sensitive genotype (G9) were compared under different durations of high-temperature treatment using phenotypic, metabolomic, and transcriptomic analyses. The results showed that G14 maintained better growth than G9 under both normal and heat stress conditions, with a more pronounced advantage under high temperature. G14 also accumulated lower levels of hydrogen peroxide (H2O2) under heat stress, suggesting reduced oxidative damage and enhanced heat tolerance. Metabolomic analysis showed that differentially accumulated metabolites (DAMs) in G14 were mainly enriched in lipid metabolism, antioxidant systems, and secondary metabolism, which were activated at early stages and maintained throughout heat stress. In contrast, DAMs in G9 were primarily associated with hormone signaling, carbon metabolism, energy metabolism, and vitamin metabolism. Transcriptomic analysis further showed that heat stress induced extensive changes in gene expression. KEGG enrichment analysis suggested that differentially expressed genes (DEGs) in G14 were mainly involved in maintaining key physiological processes, including photosynthesis, protein processing, and lipid metabolism, whereas those in G9 were predominantly associated with defense and signaling pathways. Integrated metabolomic and transcriptomic analyses supported these patterns and indicated a close coordination between gene expression and metabolic changes. Transcription factor analysis identified members of the ERF and bHLH families as candidate transcription factors associated with the heat stress response in sesame. These findings provide new insights into the molecular responses underlying heat tolerance during sesame germination.
Soil salinity restricts the yield of winter Brassica rapa, yet it remains unclear whether gamma-aminobutyric acid (GABA) alleviates salt stress through universal physiological responses or genotype-specific regulatory patterns. To resolve this question, salt-tolerant KY and salt-sensitive Qin were subjected to four treatments: blank control (CK), sole GABA supplementation(G), single salt stress(S), and combined salt stress plus GABA(S+G). Multiple indicators covering seedling growth status, membrane impairment, reactive oxygen species buildup, antioxidant performance, Na+/K+ balance and ion transportation were measured. Transcriptome profiling, DIA proteomic detection and qRT-PCR confirmation were also conducted for multi-omics exploration. Exogenous GABA relieved salt-triggered growth suppression, oxidative injury and ion disorder across both genotypes, with KY displaying stronger physiological and molecular responses associated with salt stress adaptation. Under NaCl stress conditions, KY possessed stronger antioxidant buffering potential, steadier Na+/K+ homeostasis, as well as enhanced native capacities to take in K+ and expel Na+. Omics data identified a KY-enriched regulatory module associated with phenylpropanoid and flavonoid metabolism, where BrPAL2, BrCSE, BrGSTU25, BrGASA7 and BrCYP74A were identified as candidate genes potentially associated with GABA-responsive salt tolerance. Collectively, GABA exerts non-universal salt-mitigating effects; its protective performance depends on genotype-matched coordination of physiological defense, ionic equilibrium and stress-responsive molecular pathways. These findings provide insights into genotype-dependent GABA responses and may contribute to future evaluation of GABA application and saline-adapted germplasm improvement in B. rapa.
IntroductionBiological soil crusts (BSCs) are key components of dryland ecosystems, yet their physiological stability under concurrent changes in UV-B radiation, temperature, and precipitation remains poorly understood. In particular, how BSCs at different developmental stages regulate carbon acquisition and secondary metabolism under multifactor climate stress remains unclear.MethodsIn this study, we investigated the physiological and metabolic responses of algal, lichen, and moss crusts exposed for two years to factorial combinations of warming and reduced precipitation (+1.5 °C and -8%) and UV-B enhancement (ambient, +18%, +24%) in open-top chambers (OTCs). We quantified photosynthetic traits (chlorophyll a, chlorophyll b, and gross primary productivity) and secondary metabolites (flavonoids, total phenolics, carotenoids, and extracellular polysaccharides).ResultsThe results revealed that UV-B radiation was the dominant driver of physiological and metabolic variation in BSCs, consistently suppressing photosynthetic performance and secondary metabolite accumulation across all BSC types. The strongest inhibition occurred in algal crusts, indicating high sensitivity but limited physiological plasticity. In contrast, lichen and moss crusts exhibited greater regulatory capacity and partial recovery under combined warming and reduced precipitation, suggesting stress-buffered metabolic adjustment. Notably, several physiological and metabolic traits exhibited partial recovery under combined stress treatments relative to the UV-B-only treatments, suggesting that altered temperature and moisture conditions may modulate the effects of UV-B through physiological buffering rather than yielding simple additive effects.DiscussionThis study reveals the divergent adaptation strategies of BSCs at different developmental stages under combined climatic stresses. The results highlight the importance of incorporating successional-stage heterogeneity and physiological trade-offs into predictions of dryland ecosystem responses under future climate change.
Foxtail Millet (Setaria italica) is one of China’s earliest domesticated cereal crops and remains important for dryland farming, germplasm conservation, and climate-resilient agriculture. However, climate warming and altered precipitation regimes may reshape its agroclimatic suitability and challenge traditional production regions. Here, we integrated 1, 948 cleaned occurrence records with climatic, topographic, soil, and UV-B radiation variables, and used the biomod2 ensemble species distribution modelling framework to predict the potential suitable distribution of S. italica across China. Projections were conducted under the historical baseline and CMIP6 BCC-CSM2-MR future climate scenarios for SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5 across the 2030s, 2050s, 2070s, and 2090s. The selected EMwmeanByTSS ensemble showed good discrimination ability and acceptable predictive performance, with validation ROC and TSS values of 0.863 ± 0.011 and 0.581 ± 0.022, respectively. Annual precipitation (bio12, 29.61%), elevation (elev, 28.07%), minimum temperature of the coldest month (bio06, 14.23%), and UV-B seasonality (uvb2, 10.93%) were the dominant predictors, jointly contributing 82.82%. Under the historical baseline, the total potential suitable area was 4.09 × 106 km² (44.22% of China’s land area), with highly suitable areas concentrated in the North China Plain, eastern Loess Plateau, and southern margin of Northeast China. Under future SSP scenarios, the total suitable area increased to 4.29 × 106 – 4.87 × 106 km², representing a 4.77%–18.87% increase. Expansion was mainly projected along the northern and peripheral margins of the current suitable region, while contraction occurred along southern, southwestern, and transitional margins. The suitability centroid shifted slightly northward to northwestward from northern Henan toward southern–central Shanxi, with net displacement of 113.33–232.79 km by the 2090s. Overall, future suitability is projected to show a pattern of stable core areas, marginal expansion, localized contraction, and limited centroid migration. These findings provide a spatial basis for stable production-region protection, regional variety trials, germplasm conservation, and climate-adaptive dryland agricultural planning.
Preharvest soft rot poses a threat to the commercial development of ‘Ancui’ hardy kiwi (Actinidia arguta), a newly developed cultivar with increasing cultivation potential in the cold northern regions of China. However, the fungus associated with this disease and environmentally friendly strategies for its management remain insufficiently understood. In this study, a fungal isolate was recovered from symptomatic fruits and characterized through morphological observation, internal transcribed spacer (ITS) sequence analysis, phylogenetic analysis, and pathogenicity tests. Based on the combined evidence, the fungus was assigned to the genus Diaporthe and conservatively designated as Diaporthe sp. isolate B4. A commercial 6% allicin emulsifiable concentrate exhibited concentration-dependent antifungal activity against the isolate in vitro, with an EC50 of 326.90 mg/L on a formulation-concentration basis. In a field trial, two applications of allicin at 800–1,000 mg/L provided the highest disease control efficacy, reaching approximately 82%. Allicin treatment also reduced superoxide anion production and malondialdehyde accumulation while increasing the activities of superoxide dismutase, peroxidase, catalase, and phenylalanine ammonia-lyase in fruit tissues. These findings suggest that the suppression of preharvest soft rot by allicin may involve both direct antifungal activity and enhanced defense-related responses in hardy kiwi fruit. Allicin therefore represents a promising botanical option for the sustainable management of preharvest soft rot in ‘Ancui’ hardy kiwi.
Given that the problem of insufficient light intensity is prevalent in the cultivation of rice seedlings under facility conditions, and light quality plays a crucial role in regulating crop growth, it is necessary to explore the most suitable proportion of red light for improving the quality and photosynthetic capacity of the seedlings. In this study, two different types of rice varieties (conventional rice, Xiangzaoxian 24, XZX24 and hybrid rice, Huazheyou 261, HZY261) were selected as experimental materials. A systematic investigation was conducted to examine the effects of different red light ratios on the morphological development of rice seedlings, the structure development of leaves and roots, as well as the photosynthetic characteristics. Six light quality treatments were applied, including white light (W, control), monochromatic red light (R), and combined white plus red light with different ratios (WR20, WR40, WR60, WR80). The results demonstrated that appropriate compound white-red light significantly coordinated shoot and root development; under the WR40 treatment (60% white light + 40% red light), the total seedling dry weight of the two varieties increased by 25.75% and 28.56% relative to the white light control, respectively. Gradually elevated red light proportion continuously boosted leaf pigment accumulation, with WR80 achieving the maximum total chlorophyll content, while WR60 optimized the non-photochemical quenching (NPQ) photoprotective capacity of leaves. Moderate red supplementation (WR20–WR60) maintained high Rubisco activity and upregulated the transcription of OsRBCS2 and OsRBCS3, whereas the expression of OsRBCS4 showed no significant difference across all light treatments. Single monochromatic red light failed to balance root branching and carbon assimilation efficiency despite promoting vertical leaf and stem elongation. This work provides quantitative spectral reference parameters for intelligent supplementary lighting in factory rice seedling raising, and clarifies the multi-dimensional physiological and molecular response differences of rice seedlings to graded red-white composite spectra. Further field verification trials are required to validate the applicability of the WR40 scheme under fluctuating natural environmental conditions.
More frequent short-term episodes of extreme high temperatures caused by global warming seriously threaten plant growth and development around the world. Although heat stress can occur throughout the plant life cycle, exposure during the seedling stage severely impacts subsequent plant growth and productivity. In this study, we found that the Arabidopsis metacaspase mutant atmc1 exhibited a heat-sensitive phenotype at the seedling stage, and restoration of AtMC1 expression in the atmc1 substantially rescued the heat-sensitive phenotype, indicating an important role of AtMC1 in thermotolerance. To investigate the underlying molecular responses associated with AtMC1 under heat stress, RNA sequencing was performed to compare the transcriptomic profiles of wild-type and atmc1 seedlings under normal and heat treatment conditions. Gene set enrichment analysis (GSEA) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses identified key genes related to heat acclimation, protein folding, and endoplasmic reticulum-associated degradation (ERAD). Genes involved in reactive oxygen species (ROS) homeostasis also displayed differential expression patterns under heat stress. In addition, 45 transcription factors belonging to the ERF, HSF, WRKY, NAC, and MYB families were differentially expressed between wild-type and atmc1 in response to heat stress. Protein-protein interaction analysis revealed 27 key heat-responsive genes, most of which were heat-induced but exhibited attenuated upregulation in atmc1. Collectively, our findings provide transcriptomic insights into the heat stress responses associated with loss of AtMC1 in Arabidopsis seedlings and provide a foundation for future mechanistic studies of AtMC1-mediated thermotolerance.
IntroductionConstraints to the adoption of early sowings in biomass sorghum were found in its sensitivity to cold stress during germination.MethodsA preliminary test was conducted in the laboratory on seven sorghums among sweet, fiber, and grain types, to assess their cold tolerance during germination. Sorghums were germinated at 8 °C and 25 °C (control). At the end of the test, final germination percentage (FG), mean germination time (MGT), and germination index (GI) were calculated. Thereafter, a first-year (2009) field study was conducted under the semi-arid climate of Southern Italy, using 10 cultivars of sorghum, including those from the laboratory test, to assess their response to cold during germination and subsequent seedling emergence. Five sowings were considered: 15 and 30 March (S1 and S2, respectively), 15 and 30 April (S3 and S4, respectively), and 15 May (S5, control). Field emergence was recorded from sowing up to approximately 5 weeks after sowing. At harvest, final plant density, number of leaves per plant, plant height and weight, and biomass yield were measured. A second-year (2010) field experiment was conducted in the same experimental site, using four sorghums among those that performed best in the previous year. Sorghums were sown on 16 March (S1) and 15 May (S5).ResultsFG as assessed in the laboratory was >90% while, at 8 °C, it dropped to 54.9%. At 8 °C, the most tolerant cultivar, in terms of FG, MGT, and GI, was “H128”. Results from the first-year experiment revealed a low seedling emergence (<17%) in all cultivars in S1 (mid-March). Field emergence was positively correlated with maximum air temperature recorded during the 10-day period following sowing, in all cultivars except “Kaoliang” (control). Very low field emergence in early sowing (S1) led to poor plant density in all cultivars except “NK180”, where it matched the predicted value (11 plants m−2). Very low temperatures in S1 decreased plant productivity, which was maintained at <8 t ha−1 in most cultivars. Biomass yield in S2 (late March) matched that measured in S5 (mid-May). Warmer temperatures (+4–5 °C) in S1 in the second year induced greater field emergence and dry biomass than those measured in the first year for the same sowing times.DiscussionThe availability of cold-tolerant cultivars of sorghum during the early stage of germination and seedling growth may help breeders in their genetic studies for the development of new cultivars that combine cold resilience and high productivity, and help farmers to predict sowing rate based on the expected temperature conditions. In this regard, the sorghum “NK180”, resilient to cold, although low-yielding even in regular sowings, may represent a valuable genetic source for breeding programs to enhance chilling tolerance in the field during the very early stages of growth, among the existing cultivars of sorghum. The cultivar “H128”, also resistant to cold, showed more stable production over sowing times, thus becoming agronomically more suitable. Although seed germination in the laboratory may not be considered a reliable predictor of successful field emergence under very limiting environmental conditions, it can help in a first screening within the available germplasm of sorghum for cold tolerance.
Gibberellin 20-oxidase is a key enzyme controlling gibberellin biosynthesis and represents an attractive target for engineering plant architecture and drought tolerance in maize. In this study, we developed a structure-guided computational workflow to investigate functionally important residues in maize gibberellin 20-oxidase 3 (ZmGA20ox3), integrating AI-based structural prediction, molecular docking, molecular dynamics simulations, and in vitroCRISPR/Cas9 guide RNA cleavage analysis. Structural analysis revealed the conserved Fe²+-binding catalytic triad (His147-Asp149-His166) surrounded by an aromatic substrate-recognition pocket comprising Phe151, Trp157, and Phe163. Docking analyses showed that native gibberellin substrates and the co-substrate 2-oxoglutarate occupied the predicted catalytic cavity, while prohexadione exhibited the most favourable predicted docking score among the tested ligands. Computational mutagenesis revealed generally less favourable predicted docking scores for the catalytic-site substitutions H147A, D149A, and H166A, whereas substitutions at aromatic substrate-recognition residues produced ligand-dependent effects. Subsequent 100 ns molecular dynamics simulations revealed distinct ligand-dependent conformational behaviours, with H147A affecting the stability of the predicted catalytic environment, whereas W157A primarily influenced ligand accommodation within the substrate-binding pocket. MM/GBSA analyses further indicated that favourable predicted ligand interactions do not necessarily imply a catalytically competent active-site configuration, highlighting the importance of productive active-site organization. Finally, in vitro CRISPR/Cas9 cleavage assays demonstrated sequence-specific cleavage of guide RNAs targeting the ZmGA20ox3 regions containing H147 and W157, supporting the feasibility of targeting these sites in subsequent genome-editing experiments. Collectively, this study provides structure-guided computational insights into the potential roles of key residues in ZmGA20ox3 and establishes a predictive framework for prioritizing candidate residues for future biochemical and genome-editing validation.
The transition to mycoheterotrophy has occurred repeatedly in Orchidaceae and is expected to impose contrasting evolutionary signatures on the plastome and mitogenome. However, quantitative comparisons between these two organellar compartments remain scarce, particularly within the Vanilloideae. Here, we report the first paired plastome and mitogenome of Galeola nudifolia Lour., a fully mycoheterotrophic orchid in the tribe Vanilleae (Vanilloideae), and integrate these data with published organellar genomes across photosynthetic and mycoheterotrophic Orchidaceae. The 852,490 bp mitogenome (24 linear contigs) encodes 38 protein-coding genes, eight tRNA genes, and three rRNA genes; the loss of rpl2 was confirmed by targeted re-assembly. The 101,856 bp plastome retained a typical quadripartite structure but exhibited extensive gene loss in photosynthesis-related genes. Forty-two plastome-derived regions, corresponding to 20 plastid protein-coding genes, were detected in the mitogenome; none retained intact open reading frames, indicating that physical transfer was extensive but functional transfer was absent. Branch-model (codeml) and RELAX analyses indicated a contrasting selective regime between the two genomes: relaxation of purifying selection in plastome genes was concentrated in the photosynthesis- and ATP synthesis-related loci (with atpI significant after multiple-testing correction, padj = 0.033, and further ATP synthase genes supported by RELAX), whereas the mitogenome largely retained purifying selection. Predicted RNA-editing density showed no substantial differences between trophic groups, though this analysis is exploratory. In the plastome-based phylogeny, Cyrtosia was recovered as paraphyletic with respect to G. nudifolia; however, given the limited sampling and weak support, this arrangement is preliminary and requires confirmation with denser sampling and nuclear data.
To address the low detection accuracy and frequent missed detections of citrus diseases caused by leaf occlusion, small lesion sizes, and high visual similarity among disease categories in complex orchard environments, this study proposes LCWG-DETR, a citrus disease detection method that combines wavelet edge features with Gaussian distance regression. First, an LGFE-ResNet18 network is developed for feature extraction. It integrates texture perception guided by the standard deviation of local intensity deviations with global structural encoding in the Fourier frequency domain. This design compensates for the attenuation of high frequency information from small lesions caused by stacked convolutional layers and improves the extraction of subtle disease features. Next, a cross scale adaptive feature fusion module, termed CAFF, is introduced. It employs progressive layerwise fusion and dynamic weighting to reduce the loss of spatial details during upsampling. In addition, a wavelet directional attention module, termed WDAM, is constructed. Haar wavelet decomposition is used to extract horizontal and vertical high frequency components and generate directional modulation weights, thereby guiding the network to focus more accurately on lesion boundaries and regions with abrupt texture variations. Finally, a Gaussian composite distance loss, termed GCD, is introduced. It represents bounding boxes as two dimensional Gaussian distributions with covariance matrices, which alleviates vanishing gradients and scale sensitivity during small lesion regression. Experimental results on the self collected JXDF dataset and the public OFDD dataset show that LCWG-DETR improves mAP by 5.07% and 3.41%, respectively, compared with the baseline model, while reducing the number of parameters by 0.35 M. These results demonstrate that the proposed method achieves a favorable balance between detection accuracy and real time performance. Moreover, it maintains stable detection performance and strong generalization under typical conditions involving occlusion, dense targets, backlighting, and complex backgrounds, providing reliable technical support for the visual perception systems of citrus harvesting robots.
The argan tree (Argania spinosa L.) is ecologically and economically important but its propagation is difficult on a large scale due to difficulty in rooting and grafting. This study provides a preliminary protocol for rootstock preparation and micrografting, and evaluated the compatibility of three scion genotypes (G41, G27, G27/41) grafted onto the rootstock G54. In vitro seed germination on basal MS medium without plant growth regulators resulted in an 82% germination rate, resulting in a sufficient quantity of healthy rootstocks suitable for micrografting. Shoot regeneration trials identified substantial genotypic differences; G41 had the highest level of shoot regeneration (100%), at 0.1mg L⁻¹ GA3, and had the highest levels of vegetative vigor and branching potential, as confirmed by principal component analysis (PCA), whereas G27 displayed more limited morphogenetic performance. Micrografting compatibility differed significantly among the graft combinations. The G41/G54 combination achieved the highest graft success rate (80%) and the lowest necrosis rate (20%) (p < 0.001). Histological examination of G41/G54 at two months after grafting revealed callus continuity, cambial organization and lignified vascular elements spanning the graft interface, features consistent with anatomical graft-union formation. Under the tested conditions, grafting performance differed among the three scion lines grafted onto G54. Because only one rootstock genotype and one histologically examined graft combination were evaluated, these findings require validation through additional and reciprocal graft combinations, comparative histology, acclimatization and long-term survival assessment. The findings provide a preliminary basis for further development of argan micrografting protocols.
IntroductionIn artificial intelligence (AI)-operated mobile potato harvesting, separating field impurities (stones and soil clods) from potatoes determines product quality. Because both types trigger the same pneumatic removal action, merging them into one impurity class is a natural simplification; we found that it degrades detection quality in every random seed tested, relative to a 3-label formulation (potato vs. stone vs. soil clod).MethodsWe trained YOLOX-Small under two label structures, with identical images, boxes, augmentation and hyper-parameters: 3-label (potato, stone, soil clod) and 2-label (potato, impurity). The models were fitted on 11,869 images of ten cultivars from seven Hokkaido farms collected up to the 2024 harvest — the training and validation splits of a 13,189-image corpus divided 7:2:1. The test set was a separate 2,960-image corpus from the 2025 season sharing no image or acquisition session with it (110,420 potato and 15,234 impurity instances; 12.1% prevalence). Each structure used five seeds. Both were scored on a common two-class target, potato versus impurity: the stone and soil-clod predictions of the 3-label model were pooled into a single impurity class before any metric was computed. Detection was assessed with potato misclassification rate (PMR), impurity detection rate (IDR), impurity precision and average precision (AP) over a 17×17 threshold grid; the 512-dimensional backbone representations were compared on the same target.ResultsThe 3-label structure achieved higher impurity precision than the 2-label structure at the default operating point (83.20 ± 0.85% vs. 70.07 ± 1.59%; +13.1 percentage points (pp); 95% confidence interval (CI) [10.5, 15.7]) and higher threshold-free impurity AP at 50% box overlap (79.8 ± 1.3% vs. 65.6 ± 0.8%; +14.2 pp), in every seed across the operational threshold region. The 2-label representation showed a 39% smaller centroid distance, 37% lower silhouette separability and 30–41% lower per-channel Fisher ratios. The advantage persisted although the subclass task failed asymmetrically: soil clods collapsed into stone (recall 1.84 ± 0.13%) while stones were correctly subclassed (80.69 ± 1.12%).DiscussionFine-grained supervision appears to shape the backbone representation independently of subclass accuracy: operational equivalence does not entail representational equivalence. The link between representation and performance is observational, and all results come from one detector architecture and region.
IntroductionSex expression in Cannabis sativa is determined by XX/XY sex chromosomes but remains plastic, with ethylene inhibition inducing male flowers on XX plants and ethylene release inducing female flowers on XY plants. Although ethylene is a central regulator of this process, the contribution of the gibberellin (GA) pathway to cannabis sex reversal remains poorly defined.MethodsWe reconstructed the GA biosynthesis, regulation, and signaling pathway in C. sativa using orthology-based searches, and profiled GA-related gene expression during chemically induced sex reversal through transcriptomic analyses spanning the vegetative baseline, early post-treatment leaves, and developing flowers.ResultsOrthology-based searches identified 50 putative C. sativa GA-related genes distributed across the genome, with 11 on the X chromosome, including six in the non-recombining region. Expression profiles were broadly similar between XX and XY plants at day 0, weakly perturbed at day 1, and strongly structured by floral phenotype at day 14. Early responses were limited to downregulation of CsGA3ox1 in ethephon-treated XY plants and CsGASA1 in STS-treated XX plants. By day 14, sex reversal was associated with differential expression of CsGA1, multiple GA20ox orthologs, CsGID1B, CsSLY2, and several GASA genes, indicating broad remodeling of GA-related transcription.DiscussionThese results show that ethylene-pathway manipulation is associated with time- and phenotype-dependent changes in GA-related gene expression, pointing to a contribution of the GA pathway to cannabis sex reversal.
Accurate detection of Munage grape clusters and abnormal berries in field scenes is hindered by several challenges: mature berries often exhibit colors similar to those of branches and leaves; cluster-level large targets coexist with medium- and small-scale abnormal berry targets; local abnormal cues within full-berry bounding boxes are easily diluted by responses from normal berry skin and waxy bloom; and shallow-level textures, specular highlights, and adjacent berry boundaries may induce false detections. To address these challenges, this study proposes YEIS, a YOLO11n-based detection method for Munage grape clusters and abnormal berries under color-similar backgrounds. Built upon YOLO11n, the proposed method first introduces EMBSFPN to construct multi-scale candidate features, thereby alleviating the scale-representation discrepancy between cluster-level targets and berry-level abnormal targets. Second, an intra-berry frequency–local evidence decoupling module, IB-FLED, is designed to enhance local abnormal cues within full-berry detection boxes through low-frequency appearance estimation, local residual modeling, and morphology-aware response branches. Finally, a semantic-guided recall compensation module, SGRCM, is developed to constrain P3 detail compensation using P4 semantic information refined by IB-FLED, reducing the interference of shallow-level textures, waxy bloom, and specular highlights in abnormal berry localization. Three random-seed experiments were conducted on a self-built field dataset. The results show that YEIS achieves Precision, Recall, mAP50, mAP75, and mAP50–95 values of 83.21%, 79.97%, 88.34%, 83.27%, and 76.91%, respectively. Compared with YOLO11n, the overall mAP50–95 is improved by 1.71 percentage points, and the mAP50–95 for lesion-like abnormal berries is increased by 1.61 percentage points. For scar-like abnormal berries, the F1-score and mAP50–95 are improved by 3.01 and 3.41 percentage points, respectively. Meanwhile, the number of model parameters is reduced from 2.583 M to 2.149 M, corresponding to a reduction of 16.8%. The proposed method improves the detection and localization of abnormal berries under color-similar backgrounds while reducing the parameter count relative to YOLO11n, providing a front-end visual detection approach for digital monitoring, grape-cluster localization, and abnormal-berry recognition in Munage vineyards.
To examine how pathogen coinfection influences the efficacy of single-pathogen host resistances, we investigated the interactions between the fungus (Leptosphaeria maculans) and turnip mosaic virus in canola (Brassica napus). A resistance-breaking (RB) virus strain was inoculated onto the cotyledons of three cultivars. These cultivars featured distinct host resistance profiles: fungal single dominant gene resistance (SDGR) and polygenic resistance (PGR) along with viral temperature sensitive systemic invasion resistance (TSSIR) as well as a cultivar without fungus resistance serving as a control. Subsequently, systemically virus-infected true leaves of varying maturity were inoculated with RB or non-resistance-breaking (non-RB, i.e., wild-type) fungal strains both individually and in combination. This allowed assessment of the impacts of already established virus infection upon fungal disease severity and the reciprocal effects of subsequent fungus infection upon virus concentration (VC). In the youngest leaves, high VC values corresponded with the complete absence of fungal disease, whereas the lowest VC values in the oldest leaves were associated with maximum fungal disease severity. When the RB fungal strain was present alone, it overcame SDGR more effectively when the virus was absent. Conversely, presence of the RB fungal strain in SDGR-carrying plants decreased the VC values, regardless of the presence or absence of the non-RB fungus strain. In plants possessing both fungal PGR and viral TSSIR, regardless of fungal strain, fungal infection only occurred in the lower leaves of older plants which developed consistently low VC values like those in plants inoculated with the virus alone. In the fully fungus-susceptible cultivar, fungal disease levels were consistently lower in virus-infected than virus-mock-inoculated plants. However, in coinfected plants of this cultivar, VC values increased or decreased depending upon whether the fungal RB or non-RB strain was inoculated first. By examining virus–fungus pathogen interactions across a range of host resistance backgrounds, leaf developmental stages, and plant ages, this research provides fundamental insights into the complex dynamics of agricultural plant pathogen coinfections.
