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Hybrid development is one of the most promising strategies for boosting crop yields. Parental lines used to create hybrids must have good per se performance and disease resistance for developing superior hybrids. Indian wheat line HD3209 was developed by introducing the rust resistance genes Lr19/Sr25 into the background of popular wheat variety HD2932. The wheat line HD3209 carrying Lr19/Sr25 has been successfully and rapidly converted to the CMS line A-HD3209, with 96.01% background genome recovery, based on selection for agro-morphological traits, rust resistance, pollen sterility, and foreground and background analyses utilizing SSR markers. The converted CMS line A-HD3209 was completely sterile and nearly identical to the recurrent parent HD3209. Based on high per se performance and rust resistance, the study concludes that the derived CMS line A-HD3209 is promising and can be employed successfully in hybrid development. [ABSTRACT FROM AUTHOR]

The aim of current study was to prepared zinc oxide nanofertilzers by ecofriendly friendly, economically feasible, free of chemical contamination and safe for biological use. The study focused on crude extract of Withania coagulans as reducing agent for the green synthesis of ZnO nano-particles. Biosynthesized ZnO NPs were characterized by UV–Vis spectroscopy, XRD, FTIR and GC–MS analysis. However, zinc oxide as green Nano fertilizer was used to analyze responses induced by different doses of ZnO NPs [0, 25, 50,100, 200 mg/l and Zn acetate (100 mg/l)] in Triticum aestivum (wheat). The stimulatory and inhibitory effects of foliar application of ZnO NPs were studied on wheat (Triticum aestivum) with aspect of biomass accumulation, morphological attributes, biochemical parameters and anatomical modifications. Wheat plant showed significant (p < 0.01) enhancement of growth parameters upon exposure to ZnO NPs at specific concentrations. In addition, wheat plant showed significant increase in biochemical attributes, chlorophyll content, carotenoids, carbohydrate and protein contents. Antioxidant enzyme (POD, SOD, CAT) and total flavonoid content also confirmed nurturing impact on wheat plant. Increased stem, leaf and root anatomical parameters, all showed ZnO NPs mitigating capacity when applied to wheat. According to the current research, ZnO NPs application on wheat might be used to increase growth, yield, and Zn biofortification in wheat plants. [ABSTRACT FROM AUTHOR]

In bread wheat, a literature search gave 228 QTLs for six traits, including resistance against spot blotch and the following five other related traits: (i) stay green; (ii) flag leaf senescence; (iii) green leaf area duration; (iv) green leaf area of the main stem; and (v) black point resistance. These QTLs were used for metaQTL (MQTL) analysis. For this purpose, a consensus map with 72,788 markers was prepared; 69 of the above 228 QTLs, which were suitable for MQTL analysis, were projected on the consensus map. This exercise resulted in the identification of 16 meta-QTLs (MQTLs) located on 11 chromosomes, with the PVE ranging from 5.4% (MQTL7) to 21.8% (MQTL5), and the confidence intervals ranging from 1.5 to 20.7 cM (except five MQTLs with a range of 36.1–57.8 cM). The number of QTLs associated with individual MQTLs ranged from a maximum of 17 in MQTL3 to 8 each in MQTL5 and MQTL8 and 5 each in MQTL7 and MQTL14. The 16 MQTLs, included 12 multi-trait MQTLs; one of the MQTL also overlapped a genomic region carrying the major spot blotch resistance gene Sb1. Of the total 16 MQTLs, 12 MQTLs were also validated through marker-trait associations that were available from earlier genome-wide association studies. The genomic regions associated with MQTLs were also used for the identification of candidate genes (CGs) and led to the identification of 516 CGs encoding 508 proteins; 411 of these proteins are known to be associated with resistance against several biotic stresses. In silico expression analysis of CGs using transcriptome data allowed the identification of 71 differentially expressed CGs, which were examined for further possible studies. The findings of the present study should facilitate fine-mapping and cloning of genes, enabling Marker Assisted Selection. [ABSTRACT FROM AUTHOR]

Previous studies showed that Australian wheat cultivars Janz and Sunco carry leaf rust and stem rust resistance genes Lr24 and Sr24 derived from Thinopyrum ponticum chromosome arm 3AgL. However, the size of the alien segments carrying Lr24 and Sr24 in the lines were not determined. In this study, we used non-denaturing fluorescence in situ hybridization (ND-FISH), genomic in situ hybridization (GISH), and PCR-based landmark unique gene (PLUG) markers to visualize the alien segments in Janz and Sunco, and further compared them with the segments in US cultivars Agent and Amigo. The fraction length (FL) of the alien translocation in Agent was 0.70–1.00, whereas those in Janz, Sunco, and Amigo were smaller, at FL 0.85–1.00. It was deduced that the alien gene RAg encoding for red grain color and rust resistance genes Lr24 and Sr24 on chromosome arm 3AgL were in bins of FL 0.70–0.85 and 0.85–1.00, respectively. We retrieved and extracted nucleotide-binding site-leucine-rich repeat (NBS-LRR) receptor genes corresponding to the region of Lr24 and Sr24 on chromosomes 3E, and 3J, 3Js and 3St from the reference genome sequences of Th. elongatum and Th. intermedium, respectively. A set of molecular markers developed for Lr24 and Sr24 from those extracted NBS-LRR genes will provide valuable information for fine mapping and cloning of these genes. [ABSTRACT FROM AUTHOR]

Salinity stress significantly impacts crops, disrupting their water balance and nutrient uptake, reducing growth, yield, and overall plant health. High salinity in soil can adversely affect plants by disrupting their water balance. Excessive salt levels can lead to dehydration, hinder nutrient absorption, and damage plant cells, ultimately impairing growth and reducing crop yields. Gallic acid (GA) and zinc ferrite (ZnFNP) can effectively overcome this problem. GA can promote root growth, boost photosynthesis, and help plants absorb nutrients efficiently. However, their combined application as an amendment against drought still needs scientific justification. Zinc ferrite nanoparticles possess many beneficial properties for soil remediation and medical applications. That's why the current study used a combination of GA and ZnFNP as amendments to wheat. There were 4 treatments, i.e., 0, 10 µM GA, 15 μM GA, and 20 µM GA, without and with 5 μM ZnFNP applied in 4 replications following a completely randomized design. Results exhibited that 20 µM GA + 5 μM ZnFNP caused significant improvement in wheat shoot length (28.62%), shoot fresh weight (16.52%), shoot dry weight (11.38%), root length (3.64%), root fresh weight (14.72%), and root dry weight (9.71%) in contrast to the control. Significant enrichment in wheat chlorophyll a (19.76%), chlorophyll b (25.16%), total chlorophyll (21.35%), photosynthetic rate (12.72%), transpiration rate (10.09%), and stomatal conductance (15.25%) over the control validate the potential of 20 µM GA + 5 μM ZnFNP. Furthermore, improvement in N, P, and K concentration in grain and shoot verified the effective functioning of 20 µM GA + 5 μM ZnFNP compared to control. In conclusion, 20 µM GA + 5 μM ZnFNP can potentially improve the growth, chlorophyll contents and gas exchange attributes of wheat cultivated in salinity stress. More investigations are suggested to declare 20 µM GA + 5 μM ZnFNP as the best amendment for alleviating salinity stress in different cereal crops. [ABSTRACT FROM AUTHOR]

The aim of this study was to compare the baking value of wholegrain flours obtained from common wheat grain, spelt wheat grain and purple wheat grain, and to select the optimum method for dough fermentation from the examined wheat flour. The overall study of both flours and doughs showed the need to adjust the dough fermentation method to the variety of wheat grain from which the flour was made. A comparison of the baking value of purple wheat grain flour with common wheat and spelt grain flour indicated that it could be used for bread production, however, due to the poorer gluten quality of the dough, a double phase method with leaven is recommended for dough fermentation. [ABSTRACT FROM AUTHOR]

The main ingredient of flour is processed wheat. Wheat is an agricultural product that is harvested once a year. It may be necessary to choose the variety of wheat for growing wheat and efficient harvesting. The variety of wheat is important for its economic value, taste, and crop yield. Although there are many varieties of wheat, they are very similar in colour, size, and shape, and it requires expertise to distinguish them by eye. This is very time consuming and can lead to human error. Using computer vision and artificial intelligence, such problems can be solved more quickly and objectively. In this study, an attempt was made to classify five bread wheat varieties belonging to different cultivars using Convolutional Neural Network (CNN) models. Three approaches have been proposed for classification. First, pre-trained CNN models (ResNet18, ResNet50, and ResNet101) were trained for bread wheat cultivars. Second, the features extracted from the fc1000 layer of the pre-trained CNN models ResNet18, ResNet50, and ResNet101 were classified using a support vector machine (SVM) classifier with different kernel features from machine learning techniques for classification with different variants. Finally, SVM methods were used in the second stage to classify the features obtained from the fc1000 layer of the pre-trained CNN models with an optimal set of features that can represent all features using the minimum redundancy maximum relevance (mRMR) feature selection algorithm.The accuracies obtained in the first, second, and last phases are as follows. In the first phase, the most successful method in classifying wheat grains was the ResNet18 model with 97.57%. In the second phase, the ResNet18 + ResNet50 + ResNet101 + Quadratic SVM model was the most successful model in classification using the features obtained from the ResNet CNN models with 94.08%.The accuracy for classification with the 1000 most effective features selected by the feature selection algorithm was 94.51%. Although the classification with features is slightly lower than deep learning, the classification time is much shorter and is 93%. This result confirms the great effectiveness of CNN models for wheat grain classification. [ABSTRACT FROM AUTHOR]

Studies on the wheat response under late sowing (LS) and salinity stress (SS) are available, however, in rice-wheat and cotton-wheat cropping systems, wheat planting is often delayed resulting in co-occurrence of LS and SS in salt affected soils. This two-year field study was conducted to evaluate the influence of foliar application of plant growth regulators (PGRs) [thiourea (TU), salicylic acid (SA) and hydrogen peroxide (H2O2); water and no application were taken as control] on the productivity, grain quality and economic returns of timely-sown (TS) and LS wheat under normal (NC) and natural saline conditions (SS; EC 11.27 dS m− 1). Delay in sowing and planting in naturally saline soils caused a significant decrease in plant growth, grain yield, grain quality and net economic returns during both years of study. Late planting and SS caused a significant reduction in grain yield reduction by 40.58% and 34.72% (LS) and 40.66% and 42.89% (SS) compared with respective controls during 2021 and 2022, respectively. However, the influence of co-occurrence of LS and SS was more devastating than the individual stress causing 62.17% and 60.18% reduction in grain yield than the respective control during 2021 and 2022, respectively. However, the application of all PGRs improved the grain yield, grain quality and economic turnover under SS and LS stress. The order of improvement in grain yield by the application of PGRs treatments was TU > SA > H2O2. In conclusion, the application of different plant growth regulators improved economic returns, grain yield and quality attributes of late-sown wheat under saline conditions. In this regard, TU application was the most effective. [ABSTRACT FROM AUTHOR]

Rice residue burning poses a significant challenge in the rice-wheat cropping system of India, leading to environmental pollution, health issues, and substantial nutrient loss. To combat this menace, a three-year study (2020-21 to 2022-23) was conducted, investigating the effects of rice residue retention (RRR) and rice residue incorporation (RRI) at graded N levels (0, 50, 100, 150, and 200 kg/ha) alongside farmers' practices. The primary objective was to enhance wheat productivity, profitability, and soil fertility within this system. Pooled analysis revealed that RRR outperformed RRI at lower nitrogen doses, while RRI excelled with 7.5%, 7.4%, and 10.0% higher biological yields at higher nitrogen doses (100, 150, and 200 kg/ha). The success of RRR and RRI was attributed to 10.5% and 5.0% higher effective tiller/m2, respectively, compared to farmers' practices at 150 kg N/ha. Notably, RRR exhibited superior NDVI values at the flag leaf stage (0.76) over farmers' practices (0.73). At the 150 kg N/ha, RRR displayed a 9.6% lower cost of cultivation compared to farmers' practices, with 19.6% higher net returns at lower N levels (50 kg/ha), suggesting its greater benefits under low-input conditions. Furthermore, RRR showed the highest benefit-cost ratio (2.75) at 150 kg N/ha, followed by RRI (2.59) and farmers' practices (2.55). Over the three-year period, RRR significantly increased organic carbon content (0.49–0.54%) compared to the initial value (0.38%), affirming its long-term benefits. Consequently, the adoption of RRR by farmers is a preferable eco-friendly option over RRI and present practices for enhancing wheat productivity within the rice-wheat system. Due to 60–65% saving of fuel with the practice of zero tillage along with rice residue retention, it can reduce CO2 emission by 120 kg/ha, therefore, its implementation can reduce CO2 release by 1.62 MT in South Asia per year. Ultimately, it can meet the target of Paris Agreement of limiting global warming to 1.5 °C above pre-industrial levels and reaching net-zero CO2 emissions globally by 2050. [ABSTRACT FROM AUTHOR]

MOCA1 encodes the last key glucuronosyltransferase for ionic stress sensor glycosyl inositol phosphoryl-ceramide (GIPCs) biosynthesis in Arabidopsis, which indicates that the MOCA gene family play important role in plant tolerance to salt stress. However, the isolation and function of MOCAs in staple crops have not been reported and the downstream targets of MOCAs in salt stress tolerance signalling pathway are not clear. In this study, we identified 110 MOCA genes in wheat which were classified into five clades and they differed in gene structure, protein length, conserved motifs and expression profiles in different tissues and under salt stress. TaMOCA1 was selected for further functional study in response to salt stress. TaMOCA1 was rapidly induced by NaCl treatment. The 35S::TaMOCA1-GFP construction showed the cell nucleus and cytoplasm location in wheat protoplast. TaMOCA1 over-expressing Arabidopsis seedlings formed longer primary roots and more lateral roots than the wild type ones under 50 mM NaCl treatment. The over-expressing Arabidopsis had higher expression levels of HKT1, but lower expression levels of NHX1 and SOS genes than the wild type. Also, the transgenic plants had higher SOD activity and lower MDA content than the wild Arabidopsis seedling under salt stress. These results may indicate that TaMOCA1 increases salt stress tolerance through decreasing Na+ loading from the xylem parenchyma cells to the xylem via SOS1 and HKT1, hence lowering root-to-shoot delivery of Na+ and superior antioxidant ability. All these results lay a foundation for further functional study of MOCAs in wheat. [ABSTRACT FROM AUTHOR]

Meteorological variables are essential inputs for agricultural simulation models and the lack of measured data is a big challenge for the application of these models in many agricultural zones. Studies indicated that gridded meteorological datasets can be proper replacements for measured data. This paper aimed to examine a new gridded meteorological dataset namely CRU-JRA for crop modeling intents. The CRU-JRA is a 6-hourly dataset with a spatial resolution of 0.5° × 0.5° that was primarily constructed for modeling purposes. The CERES-Wheat model in the Decision Support System for Agrotechnology Transfer (DSSAT) was used for the simulation of irrigated and rainfed wheat production systems in Iran. Results showed that the CRU-JRA maximum and minimum temperature values had a relatively fine accuracy with a normalized root mean square error (NRMSE) of 14% for the simulated grain yield. The performance of the CRU-JRA solar radiation values for the simulation of grain yield was similar with a NRMSE of 14.4%. The weakest performance was found for the CRU-JRA precipitation values with a NRMSE of 18.9%. Overall, the CRU-JRA dataset performed comparatively acceptable and similar to existing gridded meteorological datasets for crop modeling purposes in the study area, however further calibrations can improve the accuracy of the next versions of this dataset. More research is necessary for the investigation of the CRU-JRA dataset for agricultural modeling purposes across diverse climates. [ABSTRACT FROM AUTHOR]

Heavy metal accumulation is one of the major agronomic challenges that has seriously threatened food safety. As a result, metal-induced phytotoxicity concerns require quick and urgent action to retain and maintain the physiological activities of microorganisms, the nitrogen pool of soils, and the continuous yields of wheat in a constantly worsening environment. The current study was conducted to evaluate the plant growth-promoting endophytic Aspergillus flavus AUMC 16,068 and its EPS for improvement of plant growth, phytoremediation capacity, and physiological consequences on wheat plants (Triticum aestivum) under lead stress. After 60 days of planting, the heading stage of wheat plants, data on growth metrics, physiological properties, minerals content, and lead content in wheat root, shoot, and grains were recorded. Results evoked that lead pollution reduced wheat plants' physiological traits as well as growth at all lead stress concentrations; however, inoculation with lead tolerant endophytic A. flavus AUMC 16,068 and its respective EPS alleviated the detrimental impact of lead on the plants and promoted the growth and physiological characteristics of wheat in lead-contaminated conditions and also lowering oxidative stress through decreasing (CAT, POD, and MDA), in contrast to plants growing in the un-inoculated lead polluted dealings. In conclusion, endophytic A. flavus AUMC 16,068 spores and its EPS are regarded as eco-friendly, safe, and powerful inducers of wheat plants versus contamination with heavy metals, with a view of protecting plant, soil, and human health. [ABSTRACT FROM AUTHOR]

Background: Growing wheat under climate change scenarios challenges, scientists to develop drought and heat-tolerant genotypes. The adaptive traits should therefore be explored and engineered for this purpose. Thus, this study aimed to dissect surface traits and optimizing the leaf architecture to enhance water use efficiency (WUE) and grain yield. Twenty-six wheat genotypes were assessed for five novel leaf traits (NLTs: leaf prickle hairs, groove type, rolling, angle and wettability) under normal, drought and heat conditions following triplicated factorial randomized complete block design (RCBD). The data for NLTs, physiological traits (stomatal conductance, WUE, transpiration, and photosynthesis), and standard morphological and yield traits were recorded. Leaves were sampled at the stem elongation stage (Zadoks 34) to measure the leaf water content (%), contact angle, and to obtain pictures through scanning electron microscopy (SEM). The air moisture harvesting efficiency was evaluated for five selected genotypes. The ideotype concept was applied to evaluate the best-performing genotypes. Results: The correlation analysis indicated that long leaf prickle hairs (> 100 μm), short stomatal aperture and density (40–60 mm− 2), inward to spiral leaf rolling, medium leaf indentation, low contact angle hysteresis (< 10°), and cuticular wax were positively associated with WUE. This, in turn, was significantly correlated to grain yield. Thus, the genotypes (E-1) with these traits and alternate leaf wettability had maximum grain yield (502 g m− 2) and WUE supported with high photosynthesis rate, and relative water content (94 and 75% under normal and stress conditions, respectively). However, the genotype (1-hooded) with dense leaf hairs on edges but droopy leaves, spiral leaf rolling, and lighter groove, also performed better in terms of grain yield (450 g m− 2) under heat stress conditions by maintaining high photosynthesis and WUE with low stomatal conductance and transpiration rate. Conclusion: The SEM analysis verified that the density of hairs on the leaf surface and epicuticular wax contributes towards alternate wettability patterns thereby increasing the water-use efficiency and yield of the wheat plant. This study paves a way towards screening and and developing heat and drought-tolerant cultivars that are water-saving and climate-resilient. [ABSTRACT FROM AUTHOR]

Phosphorus (P) is a crucial macronutrient for plant growth and development. Basic metabolic processes regulate growth; however, the molecular detail of these pathways under low phosphorous (LP) in wheat is still unclear. This study aims to elucidate the varied regulatory pathways responses to LP stress in wheat genotypes. Phenotypic, physiological, and transcriptome analyses were conducted on Fielder (P efficient) and Ardito (P inefficient) wheat genotypes after four days of normal phosphorous (NP) and LP stress. In response to LP, Fielder outperformed Ardito, displaying higher chlorophyll content-SPAD values (13%), plant height (45%), stem diameter (12%), shoot dry weight (42%), and root biomass (75%). Root structure analysis revealed that Fielder had greater total root length (50%), surface area (56%), volume (15%), and diameter (4%) than Ardito under LP. These findings highlight Fielder's superior performance and adaptation to LP stress. Transcriptome analysis of wheat genotype roots identified 3029 differentially expressed genes (DEGs) in Fielder and 1430 in Ardito, highlighting LP-induced changes. Key DEGs include acid phosphatases (PAPs), phosphate transporters (PHT1 and PHO1), SPX, and transcription factors (MYB, bHLH, and WRKY). KEGG enrichment analysis revealed key pathways like plant hormones signal transduction, biosynthesis of secondary metabolites, and carbohydrate biosynthesis metabolism. This study unveils crucial genes and the intricate regulatory process in wheat's response to LP stress, offering genetic insights for enhancing plant P utilization efficiency. [ABSTRACT FROM AUTHOR]

The presence of incompatibility alleles in primary amphidiploids constitutes a reproductive barrier in newly synthesized wheat-rye hybrids. To overcome this barrier, the genome stabilization process includes large-scale chromosome rearrangements. In incompatible crosses resulting in fertile amphidiploids, the elimination of one of the incompatible alleles Eml-A1 or Eml-R1b can occur already in the somatic tissue of the wheat × rye hybrid embryo. We observed that the interaction of incompatible loci Eml-A1 of wheat and Eml-R1b of rye after overcoming embryo lethality leads to hybrid sterility in primary triticale. During subsequent seed reproductions (R1, R2 or R3) most of the chromosomes of A, B, D and R subgenomes undergo rearrangement or eliminations to increase the fertility of the amphidiploid by natural selection. Genotyping-by-sequencing (GBS) coverage analysis showed that improved fertility is associated with the elimination of entire and partial chromosomes carrying factors that either cause the disruption of plant development in hybrid plants or lead to the restoration of the euploid number of chromosomes (2n = 56) in the absence of one of the incompatible alleles. Highly fertile offspring obtained in compatible and incompatible crosses can be successfully adapted for the production of triticale pre-breeding stocks. [ABSTRACT FROM AUTHOR]

Calcium-dependent protein kinase (CDPK) is member of one of the most important signalling cascades operating inside the plant system due to its peculiar role as thermo-sensor. Here, we identified 28 full length putative CDPKs from wheat designated as TaCDPK (1-28). Based on digital gene expression, we cloned full length TaCPK-1 gene of 1691 nucleotides with open reading frame (ORF) of 548 amino acids (accession number OP125853). The expression of TaCPK-1 was observed maximum (3.1-fold) in leaf of wheat cv. HD2985 (thermotolerant) under T2 (38 ± 3 °C, 2 h), as compared to control. A positive correlation was observed between the expression of TaCPK-1 and other stress-associated genes (MAPK6, CDPK4, HSFA6e, HSF3, HSP17, HSP70, SOD and CAT) involved in thermotolerance. Global protein kinase assay showed maximum activity in leaves, as compared to root, stem and spike under heat stress. Immunoblot analysis showed abundance of CDPK protein in wheat cv. HD2985 (thermotolerant) in response to T2 (38 ± 3 °C, 2 h), as compared to HD2329 (thermosusceptible). Calcium ion (Ca2+), being inducer of CDPK, showed strong Ca-signature in the leaf tissue (Ca—622 ppm) of thermotolerant wheat cv. under heat stress, whereas it was minimum (Ca—201 ppm) in spike tissue. We observed significant variations in the ionome of wheat under HS. To conclude, TaCPK-1 plays important role in triggering signaling network and in modulation of HS-tolerance in wheat. [ABSTRACT FROM AUTHOR]

Climate change affects the established crop production practices by altering rainfall, temperature, and solar radiation—leading to reduced resource use and economic efficiencies. Pertaining to this, we analysed the optimum fertiliser-Nitrogen (N) recommendation of rice and wheat crops for Kharagpur station, West Bengal, India under projected climate change conditions by using six mathematical models, namely, quadratic, square root, linear plateau, quadratic plateau, square root plateau, and the Mitscherlich model. Models were parameterised using field experiment observations at Kharagpur and tested for historical crop yield. The historical (1976–2005) and future (2006–2100) yield responses of rice and wheat to the different N doses are simulated by using a calibrated and validated process-based crop simulation model—Crop Environment and Resource Synthesis (CERES). Eight bias-corrected Global Climate Model (GCM) outputs for the four Representative Concentration Pathways (RCP2.6, RCP4.5, RCP6.0, and RCP8.5) were used to simulate the yield of both crops for the period of 1976 to 2100. Results revealed that the quadratic plateau model represents crop yield response to fertiliser-N application better than other mathematical models. The estimated optimum N dose (OND) increased from an average historical 121 kg N/ha to 138, 143, and 146 kg N/ha for rice, and from an average historical 98 kg N/ha to 119, 124, and 127 kg N/ha for wheat in three future times, respectively, 2006–2035, 2036–2065, and 2066–2095 under all RCPs scenarios. On the other hand, the yield of both crops is expected to decrease in the future due to an increase in N losses, leading to reduced N use efficiency. [ABSTRACT FROM AUTHOR]

Wheat plant is one of the most basic food sources for the whole world. There are many species of wheat that differ according to the conditions of the region where they are grown. In this context, wheat species can exhibit different characteristics. Issues such as resistance to geographical conditions and productivity are at the forefront in this plant as in all other plants. The wheat species should be correctly distinguished for correct agricultural practice. In this study, a hybrid model based on the Vision Transformer (VT) approach and the Convolutional Neural Network (CNN) model was developed to classify wheat species. For this purpose, ResMLP architecture was modified and the EfficientNetV2b0 model was fine-tuned and improved. A hybrid transformer model has been developed by combining these two methods. As a result of the experiments, the overall accuracy performance has been determined as 98.33%. The potential power of the proposed method for computer-aided agricultural analysis systems is demonstrated. [ABSTRACT FROM AUTHOR]

Fusarium head blight (FHB) is a significantly important disease in cereals primarily caused by Fusarium species. FHB control is largely executed through chemical strategies, which are costlier to sustainable wheat production, resulting in leaning towards sustainable sources such as resistance breeding and biological control methods for FHB. The present investigation was aimed at evaluating newly identified bacterial consortium (BCM) as biocontrol agents for FHB and understanding the morpho-physiological traits associated with the disease resistance of spring wheat. Preliminary evaluation through antagonistic plate assay and in vivo assessment indicated that BCM effectively inhibited Fusarium growth in spring wheat, reducing area under disease progress curve (AUDPC) and deoxynivalenol (DON), potentially causing type II and V resistance, and improving single spike yield (SSPY). Endurance to FHB infection with the application of BCM is associated with better sustenance of spike photosynthetic performance by improving the light energy harvesting and its utilization. Correlation and path-coefficient analysis indicated that maximum quantum yield (QY_max) is directly influencing the improvement of SSPY and reduction of grain DON accumulation, which is corroborated by principal component analysis. The chlorophyll fluorescence traits identified in the present investigation might be applied as a phenotyping tool for the large-scale identification of wheat sensitivity to FHB. [ABSTRACT FROM AUTHOR]

Plant structure type (PT) is an important complex and quantitative trait to regulating yield potential and stress tolerance in wheat (Triticum aestivum L.). In this study, a recombinant inbred line (RIL) population genotyped by wheat 50 K SNP chip was employed to detect quantitative trait loci (QTL) controlling plant structure type and seed-related eight traits in seven environments. A total of 13 QTL were detected in multiple environments. By comparing previous studies, QKw-5D-2-2 (kernel width) and QSnl-6B (spike neck length), on chromosomes 5D and 6B, respectively, were regarded as two new multi-environmental stable QTLs explaining 5.01–11.51% and 9.79–15.01% of the phenotypic variation, correspondingly. In addition, we predicted two genes associated with grain width in the interval QKw-5D-2-2, and seven multi-environmentally stable QTLs on chromosome 4D were found to be distributed in clusters; significant correlations were found between plant height (PH) and, PT, spike neck length (SNL), basal two internode length (BL), kernel width (KW) and thousand kernel weights (TKW) by genetic and correlation analyses. In summary, our results will provide help to understand the genetic relationship between plant structure type and yield potential. And the newly identified QTLs and QTL clusters lay the genetic foundation for fine localization of plant structure type related traits and molecular marker-assisted breeding in wheat genetic improvement. [ABSTRACT FROM AUTHOR]

The yield and production of several crops, including wheat (Triticum aestivum L.), which is the most significant crop in the world, have been significantly affected by drought occurrences in various parts of the world. By Using the randomized complete block design, which is based on three replications, a set of 100 wheat accessions were examined under normal and drought stress condition. The analysis of variance revealed that the genotypes significantly varied in all of the qualities in both condition under normal and drought stress, which demonstrating the wide range of genotypes that can be used in breeding strategies for improvement. The study revealed significant differences among genotypes under both normal and drought conditions, highlighting the varying responses to stress. According to the results of the correlation study, in normal conditions, the grain yield per plant exhibits a significant and favorable link with every trait that was studied. Under drought conditions, grain yield per plant has a negative association with plant height, which has an impact on grain production and results in a significant decrease in the wheat crop's output. The genotypes G27, G28, G71, G72, and G89 performed best under drought conditions and were termed drought resistant genotypes, according to the mean variability, whereas the genotypes G50, G53, G54, G80, and G88 performed poorly and were considered as drought sensitive. Highest broad-sense heritability (84–96%) and genetic advance exceeded 20% that emphasized the role of genetic factors in influencing studied traits which exhibited significant potential for improvement through selective breeding, particularly in drought-stress. Results obtained from principal component analysis, only 4 PCs showed the significant variability due to having eigenvalues > 1. These 4 PCs cumulatively accounted for 66.1% and 63.8% of the total variability under normal and drought conditions. Eigenvalues, proportions, and cumulative values of principal components were analyzed, indicating that the first few principal components captured the majority of the variance in the dataset. Loading factor analysis further revealed the correlation between original variables and principal components, aiding in understanding the contribution of each trait to overall variance. The identification of drought-tolerant genotypes and the delineation of trait relationships provide crucial information for future breeding endeavors, aiming at enhancing wheat resilience and ensuring sustainable wheat production in the face of environmental challenges. This study will also enhance the understanding of genetic basis of wheat traits and their responses to drought stress. [ABSTRACT FROM AUTHOR]

In the present study, a new approach that uses ultrasound-assisted extraction clean-up combined with dispersive liquid-liquid microextraction has been developed for the preconcentration of trace amounts of clodinafop-propargyl herbicide in wheat samples. The clodinafop-propargyl was then determined using gas chromatography with flame ionization detection. In this technique, wheat samples were extracted by ultrasound-assisted extraction followed by a dispersive liquid-liquid microextraction (DLLME) step for further purification and enrichment of clodinafop-propargyl. By using a Pasteur pipette as an extraction device, a low-density extraction solvent like water is possible to use in the DLLME method. The effects of various parameters on the extraction efficiency of the proposed technique were investigated and optimized. Good linearity was obtained from 20 to 1000 µg/kg. The limit of detection was 10 µg/kg (S/N = 3). The relative recoveries at the three spiked levels ranged from 88 to 96% with an RSD less than 13% (n = 3). The technique has been successfully applied to the determination of clodinafop-propargyl herbicide in wheat samples. [ABSTRACT FROM AUTHOR]

Wheat head detection and counting using deep learning techniques has gained considerable attention in precision agriculture applications such as wheat growth monitoring, yield estimation, and resource allocation. However, the accurate detection of small and dense wheat heads remains challenging due to the inherent variations in their size, orientation, appearance, aspect ratios, density, and the complexity of imaging conditions. To address these challenges, we propose a novel approach called the Oriented Feature Pyramid Network (OFPN) that focuses on detecting rotated wheat heads by utilizing oriented bounding boxes. In order to facilitate the development and evaluation of our proposed method, we introduce a novel dataset named the Rotated Global Wheat Head Dataset (RGWHD). This dataset is constructed by manually annotating images from the Global Wheat Head Detection (GWHD) dataset with oriented bounding boxes. Furthermore, we incorporate a Path-aggregation and Balanced Feature Pyramid Network into our architecture to effectively extract both semantic and positional information from the input images. This is achieved by leveraging feature fusion techniques at multiple scales, enhancing the detection capabilities for small wheat heads. To improve the localization and detection accuracy of dense and overlapping wheat heads, we employ the Soft-NMS algorithm to filter the proposed bounding boxes. Experimental results indicate the superior performance of the OFPN model, achieving a remarkable mean average precision of 85.77% in oriented wheat head detection, surpassing six other state-of-the-art models. Moreover, we observe a substantial improvement in the accuracy of wheat head counting, with an accuracy of 93.97%. This represents an increase of 3.12% compared to the Faster R-CNN method. Both qualitative and quantitative results demonstrate the effectiveness of the proposed OFPN model in accurately localizing and counting wheat heads within various challenging scenarios. [ABSTRACT FROM AUTHOR]

Diversification of agricultural practices, including changes in crop rotation, intercropping or cover cropping, influence the soil microbiome. Here the impact of tillage and crop diversification on the soil microbiome is reported, being one of the few boreal studies. The field experiment consisted of four treatments with four replications all having a short cereal rotation practice namely an oat (Avena sativa) – spring barley (Hordeum vulgare) – wheat (Triticum aestivum) rotation for the past 10 years until spring 2018. During that period two of the treatments were conventionally tilled with moldboard ploughing whereas the other two were no-tillage treatments. From the growing season 2018 until fall 2020 the main crop in all treatments was spring barley. The first conventional tillage treatment was diversified with English ryegrass (Lolium perenne) as an undersown cover crop for the next three growing seasons. The first no-tillage treatment continued with spring barley only. The second conventional tillage and no-tillage treatment had winter rapeseed in rotation in 2019. Bulk soils were sampled in May 2018 before diversification and then in October 2018, 2019, and 2020. The results showed a clear effect of tillage on the beta-diversity of the soil microbiome and an increase in fungal richness. Barley monoculture interrupted with winter rapeseed resulted in a minor change of the fungal and bacterial community composition. Other fungal and bacterial alpha diversity measures did not react to tillage or diversification nor did the gene copy abundances involved in the N cycle. In conclusion tillage had a profound effect on the soil microbiome hindering impact of the diversification. [ABSTRACT FROM AUTHOR]

Inflorescence structure affects final grain yield (GY) in wheat (Triticum aestivum L.). Recent breeding efforts have focused on improving grain number per spike, which is positively correlated with GY. Grain Number Increase 1 (GNI-A1) encodes a homeodomain leucine zipper class I (HD-Zip I) transcription factor that controls the number of grains per spike and GY. However, how this increase in grain number affects grain quality, especially grain protein content (GPC) in wheat, remains elusive. Here we investigated within-spikelet variation in GPC using GNI-A1 near-isogenic lines. Yield trials in two seasons and at two sites demonstrated that lines harboring a reduced-function allele, GNI-A1 (105Y), consistently showed improved GY due to a 27% increase in grain number per spike, along with a 1.7% reduction in GPC compared with lines containing a functional allele, GNI-A1 (105N). We confirmed the positive correlation between GY and grain number and the negative correlation between GY and GPC, but we observed no correlation between GY and thousand-grain weight. The increased grain number conferred by the 105Y allele was due to better floret fertility around the central part of the spike and whole florets. In-depth phenotypic analysis using dissected grain samples revealed that GPC was nearly uniform among spikelets and florets. These results suggest that in plants carrying a mutation in GNI-A1, the increase in the total number of grains is accompanied by a reduction in GPC. [ABSTRACT FROM AUTHOR]

The flag leaf size of wheat is an “ideotypic” morphological trait that plays a critical role in plant architecture and grain yield by providing photosynthetic assimilates in wheat. Although many of the genomics research studies covered the flag leaf traits, including flag leaf length (FLL), width (FLW), area (FLA), thickness (FLT), and volume (FLV), for a better understanding, this research used a recombinant inbred line (RIL) population derived from a cross between DH118 and Jinmai 919 to evaluate the genetic regions across six environments, including BLUP under both drought stress (DS) and well-watered (WW) conditions and analyze their correlation with traits related to grain yield. A total of 40 (QTL) quantitative trait loci controlling the five traits were detected across all environments, with phenotypic variance explaining (PVE) 5.09%-15.26%. Among them, 12 QTL were identified as stable, including two QTL for FLL, two for FLW, three for FLA, two for FLT and three for FLV, in which nine QTL were found to be validated in more than three environments through a double haploid (DH) population Jinchun 7 × Jinmai 919. The Qflw.saw-2A, Qfla.saw-2A, Qflv.saw-2A, Qflt.saw-2B, and Qflt.saw-3B were stated as novel due to not being reported by any of the previous research studies related to flag leaf traits. In addition, traits related to flag-leaf and grain yield were significantly correlated in both water regimes. These results provide a better understanding of the genetic basis underlying flag leaf traits. Also, target regions for fine mapping and marker-assisted selection (MAS) were identified and will be valuable for breeding high-yielding bread wheat. [ABSTRACT FROM AUTHOR]

High temperatures (HT) and drought are two major factors restricting wheat growth in the early growth stages. This study investigated the role of glutathione (GSH) amendment (0.0, 0.5, 1.0, and 2.0 mM) to soil in mitigating the adverse effect of HT (33 °C, with 25 °C as a control), water regimes (60% of field capacity and control), and their combinations. HT decreased the length, project area, surface area, volume, and forks of the root, while drought had the reverse effect. Shoot length, leaf area, leaf relative water content, and shoot and root dry matter were significantly decreased by HT and drought, and their combined impact was more noticeable. GSH significantly promoted the root system, shoot growth, and leaf relative water content. The combined treatment reduced chlorophyll a, chlorophyll b, and total chlorophyll. However, 0.5 mM GSH raised chlorophyll a, chlorophyll b, and total chlorophyll by 28.6%, 41.4%, and 32.5%, respectively, relative to 0.0 mM GSH. At combined treatment, 0.5 mM GSH decreased malondialdehyde (MDA) by 29.5% and increased soluble protein content by 24.1%. GSH meaningfully enhanced the activity of superoxide dismutase, catalase, and ascorbate peroxide in different treatments. This study suggested that GSH could protect wheat seedlings from the adverse effects of HT and/or drought stresses. [ABSTRACT FROM AUTHOR]

In the modern era, intensive agricultural practices such as agrochemicals are applied in excessive amounts to enhance agricultural production. However, imbalanced adoption of these chemicals has arisen in the dwindling of agriculture factor productivity and soil quality. To maintain soil fertility and production, these chemical fertilizers must be supplemented with organic inputs. Keeping this in the backdrop, a research trail was established during 2018–19 and 2019–20 years at Research Farm of Agriculture University, Kota, India. The treatment setup was comprised of 5 treatment modules viz., conservation tillage + organic management (CAOM), conservation tillage + chemical management (CACM), conventional tillage + chemical management (CTCM), conventional tillage + organic management (CTOM) and the package of practices (PoPs) with four replications. Results indicated that the highest organic carbon (0.68%), bacterial (29.11 × 107 cfu g−1), fungal (4.77 × 104 cfu g−1), actinomycetes populations (5.67 × 104 cfu g−1), acid phosphatase (44.1 µg g−1 h−1), urease (45.3 µg g−1 h−1) and dehydrogenase (23.3 µg triphenylformazan [TPF] g−1 h−1) activity in soil were found in the treatment of conservation organic system during both the years of study at each soil depth. In contrast to other parameters, the highest system productivity was observed with conservation chemical crop management approaches, with a soybean equivalent yield of 4615 kg ha−1 in a soybean–wheat system of production. Furthermore, the soil quality index (SQI) significantly varied from the lowest score (0.30) at 45–60 cm layer of soil in the package of practices to the highest score (0.92) at 0–15 cm layer of soil with regards to the conservation organic which shows, 206.67 percent enhancement through the soil profile of various crop management practices. The SQI variation from 0–15 to 45–60 cm soil depth was 130.0, 81.08, 60.0, 175.0 and 83.33 percent, respectively, for CAOM, CACM, CTCM, CTOM and PoPs. Amongst, different systems, the highest mean performance was noticed under the conservation organic systems for physical and biological properties. Hence, in line with the salient outcome, we may propose that the conservation chemical system needs to be followed to improve crop productivity, whereas, conservation organic seems a good option for soil health with long-term viability. [ABSTRACT FROM AUTHOR]

Globally, salinity is an important abiotic stress in agriculture. It induced oxidative stress and nutritional imbalance in plants, resulting in poor crop productivity. Applying silicon (Si) can improve the uptake of macronutrients. On the other hand, using biochar as a soil amendment can also decrease salinity stress due to its high porosity, cation exchange capacity, and water-holding capacity. That's why the current experiment was conducted with novelty to explore the impact of silicon nanoparticle-based biochar (Si-BC) on wheat cultivated on salt-affected soil. There were 3 levels of Si-BC, i.e., control (0), 1% Si-BC1, and 2.5% Si-BC2 applied in 3 replicates under 0 and 200 mM NaCl following a completely randomized design. Results showed that treatment 2.5% Si-BC2 performed significantly better for the enhancement in shoot and root length, shoot and root fresh weight, shoot and root dry weight, number of leaves, number of tillers, number of spikelets, spike length, spike fresh and dry weight compared to control under no stress and salinity stress (200 mM NaCl). A significant enhancement in chlorophyll a (~ 18%), chlorophyll b (~ 22%), total chlorophyll (~ 20%), carotenoid (~ 60%), relative water contents (~ 58%) also signified the effectiveness of treatment 2.5% Si-BC2 than control under 200 mM NaCl. In conclusion, treatment 2.5% Si-BC2 can potentially mitigate the salinity stress in wheat by regulating antioxidants and improving N, K concentration, and gas exchange attributes while decreasing Na and Cl concentration and electrolyte leakage. More investigations at the field level are recommended for the declaration of treatment 2.5% Si-BC2 as the best amendment for alleviating salinity stress in different crops under variable climatic conditions. [ABSTRACT FROM AUTHOR]

Wheat gliadin is thought to be the main cause of wheat allergy leading to celiac disease. In this study, we reported an electrochemical immunosensor based on AuNPs/Zn/Ni-ZIF-8-800@graphene for simple, efficient, and sensitive detection of gliadin. A monoclonal antibody against gliadin were prepared by hybridoma technique. Zn/Ni-ZIF-8-800 with high stability was prepared by using zinc–nickel bimetallic organic framework MOFs, and graphene and gold nanoparticles with large surface area and excellent conductivity were introduced. Chitosan was used as a binder to fixed the composite on the surface of glassy carbon electrode. The fabricated materials and the corresponding sensors were comprehensively characterized by X-ray diffractometer, scanning electron microscope, transmission electron microscopy, Fourier transform infrared spectroscopy, Brunauer–Emmett–Teller, and cyclic voltammetry analyses. Under the optimal conditions, the linear range of the electrochemical immunosensor was 0.1–100 μg mL−1, and the detection limit was 0.950 μg mL−1. In addition, the fabricated sensor exhibited high selectivity and long-term stability. The recovery test showed that the prepared sensor was suitable for the detection of gliadin in real food and feed, exhibiting great promising of the developed sensor in practical application. [ABSTRACT FROM AUTHOR]

Dryland agricultural soils are recognized as significant sites of methane (CH4) absorption, making them integral to the global CH4 budget. Nitrogen fertilization is commonly used by growers in these regions to obtain optimal wheat yields, but it is unclear how various methods may affect CH4 absorption. Therefore, we conducted two years of field studies in the rain-fed agricultural experimental station in the semi-arid Loess Plateau in northwest China to test how four fertilization methods altered different crop and soil characteristics. Plots consisted of a popular spring wheat variety treated with either no fertilizer (CK), nitrogen fertilizer (N), organic manure (M), or a combination of nitrogen and organic manure (NM). We analyzed the effects each fertilization methods had on both yield and soil CH4 flux. The results indicated that these soils act as a net sink of CH4. The NM treatment significantly increased wheat yield, while the N treatment significantly reduced CH4 absorption. Furthermore, soil CH4 absorption under each treatment had a clear temporal pattern, which peaked during the flowering stage. Our principal component analysis and linear regression analysis illustrated how CH4 fluxes were significantly positively or negatively correlated with soil total nitrogen, nitrate nitrogen, and temperature (P < 0.05), potentially explaining 40% of the CH4 variability. In conclusion, our results indicate that the co-application of nitrogen and organic manure can both support optimal wheat yield and effectively reduce the risk of CH4 emissions. [ABSTRACT FROM AUTHOR]

The stagnant crop productivity and declining factor productivity especially under rice-wheat system in changing climate scenario demand the adoption of nutrient responsive high yielding climate-resilient varieties. Considering these challenges, the present study was conducted during two consecutive Rabi seasons of 2020-21 and 2021-22 with an aim to improve wheat productivity through appropriate combinations of genotypes, nutrient management and plant growth regulators (PGRs). The experiment was conducted in split-plot design with two nutrient levels {recommended dose of fertilizer (RDF) as 150:60:40 kg N, P2O5 and K2O ha-1, respectively, and 150% RDF + 15 t FYM (farm yard manure) ha-1 + two sprays of PGRs consisting of tank-mix of chlormequat chloride @ 400 g + tebuconazole @ 172 g ha-1 at the first node and flag leaf stage} in main-plots and nine genotypes (DBW187, DBW303, DBW327, DBW332, DBW370, DBW371, DBW372, HD3086 and PBW872) in sub-plots. The plant height significantly reduced while earheads m-2 and grains m-2 improved with PGRs application under high fertility which led to increased (12.6%) mean grain yield over RDF. Among genotypes, maximum yield was observed for DBW370 (67.84 q ha-1) followed by PBW872, DBW371 and DBW372. Nutrient management and genotype interaction revealed that more grains m-2 in DBW370 led to maximum yield (66.2 q ha-1) at RDF while bolder grains in PBW872 made it top yielder (71.16 q ha-1) under high fertility condition. It is concluded that productivity of modern wheat cultivars can be improved through higher fertility and tank-mix application of chlormequat + tebuconazole. [ABSTRACT FROM AUTHOR]

Leaf gas exchange plays a critical role in determining crop final yield, and there is a threshold response of leaf gas exchange to water stress. It is of great significance to quantify crop water stress severity by using the response characteristics of leaf gas exchange to drought. However, it is currently unclear whether leaf gas exchange serve as a reliable indicator for predicting crop final yield in response to drought, which affects the accuracy of monitoring agricultural drought using physiological indicators during the crop growing season. This study determined the response threshold of leaf gas exchange to drought for spring wheat through a serials of soil dry-down experiments and used the threshold characteristics to construct and parameterize a spring wheat growth model. Spring wheat were designed to be irrigated with five treatments (with supplementary irrigation at 230 mm, 165 mm, 115 mm, 50 mm and 0 mm). Crop model were used to simulate and analyze the threshold response characteristics of grain yield to drought and compare them to the thresholds of leaf gas exchange indices for spring wheat. The results showed that the response threshold of stomatal conductance of spring wheat to fraction of transpirable soil water was 0.5, which was greater than that of transpiration rate and net photosynthetic rate, 0.4. The parameterized spring wheat growth model with the response threshold of net photosynthetic rate to fraction of transpirable soil water accurately simulated the aboveground biomass and final yield of spring wheat. The response threshold of spring wheat final yield to fraction of transpirable soil water was significantly smaller than that of leaf gas exchange parameters to fraction of transpirable soil water (0.18 versus 0.4). This indicates that there are certain problems in using physiological indicator such as leaf gas exchange indices during crop growing season to determine the agricultural drought severity and reflect the reduction of final crop yields due to drought. [ABSTRACT FROM AUTHOR]

High-throughput phenotyping (HTP) approaches are potentially useful for designing indirect selection strategies, which consists in the selection of a primary target trait X based on secondary trait Y. Usually, the secondary trait Y is correlated to the target trait X and is easier, faster and cheaper to measure. In this context, the use of secondary traits (such as vegetation indices derived from HTP platforms) could potentially lead to a fast, non-invasive, accurate and efficient selection of superior genotypes. Considering the lack of information in the literature regarding high-throughput phenotyping approaches in tropical wheat breeding, this study aimed to (i) determine the best stages to carry out image acquisition for applying multi-spectral vegetation indices for genotype evaluation and selection; (ii) evaluate the heritability and accuracy of multi-spectral vegetation indices; (iii) understand the relationships between vegetation indices and target agronomic traits; and (iv) evaluate the efficiency of indirect selection via UAV-based high-throughput phenotyping. A diversity panel of 49 tropical wheat cultivars was evaluated during the 2022 winter season. Weekly flight campaigns were performed to further build the dataset with multi-spectral vegetation indices, which were then analyzed together with four target agronomic traits. Statistical analysis based on Mixed Effect Model was performed to estimate genetic parameters and predict genetic values, which were subjected to correlation analysis. Additionally, factor analysis was applied, and the factorial scores were used in an indirect selection strategy (indirect via HTP). This strategy was compared to three alternative strategies: direct via grain yield, direct via days to heading, and the multi-trait genotype-ideotype distance index. The results indicate that vegetation indices are suitable for indirect selection strategies and highly efficient for the indirect selection of grain yield and cycle. These findings will help in the decision making regarding the adoption of remote or proximal sensing-based approaches in Brazilian public wheat breeding programs. [ABSTRACT FROM AUTHOR]

Common wheat (Triticum aestivum L.) is one of the most important species of crops. It is the most common cereal grown on all continents. Every year the yield of wheat on plantations all over the world is hugely reduced by yellow rust caused by the Puccinia striformis f. sp. tritici fungus. Apart from the yield potential and grain quality, resistance to diseases has become an important breeding goal. The identification and use of new sources of resistance is essential to improve the resistance of wheat plants to yellow rust. In this study, we performed a genome wide association study (GWAS) for the derived mapping population. The aim of this study was to find the silicoDArT and SNP markers coupled with the genes determining resistance to Puccinia striformis f. sp. tritici, which could be used to select yellow rust-resistant cultivars. Long-term observations resulted in the identification of a cultivar (Tobak) with very high resistance to infestation with yellow rust. This cultivar was crossed with a yellow rust-susceptible cultivar and a mapping population was derived and subjected to next-generation sequencing (NGS). As a result of the DArTseq analysis, 10,586 silicoDArT markers and 8,423 SNP markers were obtained. The obtained genotyping data was used for association mapping, which was performed using the GWAS method. The largest number of sequences similar to the sequences of the silicoDArT and SNP markers determined in the GWAS analysis were located on chromosome 2B. Further analyses resulted in the identification of region 36838943-536815801 on chromosome 2B, which contained three sequences related with resistance to diseases. Disease resistance genes involved in the plant defense system, such as the disease resistance proteins RAG1, RAG2 and RPP8, have been identified. [ABSTRACT FROM AUTHOR]

The objective of this study was to characterize the effects of barley powdery mildew infection on wheat via the evolution and dynamics of chloroplasts and oxidative processes based on in vivo measurements of ultra-weak photon emission, parallel measurement of chlorophyll and ascorbic acid content, and molecular identification of the pathogen. The results showed the temporal dynamics of the evolution of ultra-weak photon emission signals that were evidently different for healthy and powdery mildew-infested wheat leaves. In the dark, the ceasing of delayed fluorescence signal made it possible to visualize the ultra-weak luminescence signal as well. Both delayed fluorescence and ultra-weak luminescence signals were characteristic of stress symptoms induced by powdery mildew that was further strengthened by the changes of chlorophyll and ascorbic acid content as typical stress analytical parameters. The presented data and parameterization enabled the identification of stress induction due to powdery mildew infestation in wheat, which should be investigated in detail in the future for fine-tuning our measurements, even by using other species and increasing the length of the measurement in order to increase its specificity. The changes in R2 values are suitable for monitoring the changes of plant stress response. The measurement of fluorescence and luminescence leads to a greater comprehension of the underlying photon emission-related processes, both in general and in the case of powdery mildew infestation. [ABSTRACT FROM AUTHOR]

Global gridded crop models (GGCMs) have been broadly applied to assess the impacts of climate and environmental change and adaptation on agricultural production. China is a major grain producing country, but thus far only a few studies have assessed the performance of GGCMs in China, and these studies mainly focused on the average and interannual variability of national and regional yields. Here, a systematic national- and provincial-scale evaluation of the simulations by 13 GGCMs [12 from the GGCM Intercomparison (GGCMI) project, phase 1, and CLM5-crop] of the yields of four crops (wheat, maize, rice, and soybean) in China during 1980–2009 was carried out through comparison with crop yield statistics collected from the National Bureau of Statistics of China. Results showed that GGCMI models generally underestimate the national yield of rice but overestimate it for the other three crops, while CLM5-crop can reproduce the national yields of wheat, maize, and rice well. Most GGCMs struggle to simulate the spatial patterns of crop yields. In terms of temporal variability, GGCMI models generally fail to capture the observed significant increases, but some can skillfully simulate the interannual variability. Conversely, CLM5-crop can represent the increases in wheat, maize, and rice, but works less well in simulating the interannual variability. At least one model can skillfully reproduce the temporal variability of yields in the top-10 producing provinces in China, albeit with a few exceptions. This study, for the first time, provides a complete picture of GGCM performance in China, which is important for GGCM development and understanding the reliability and uncertainty of national- and provincial-scale crop yield prediction in China. [ABSTRACT FROM AUTHOR]

Terminal irrigation drought stress is one of the most drastic abiotic stress to diminish the wheat crop development and grains yield in arid regions of the world. The use of moringa leaf extract (MLE30) via seed priming technique is investigated as an organic and sustainable approach for the mitigation of drought stress along with curtailed seed rate in wheat crop. The study investigated the interaction of organic seed priming: control (dry seeds), hydro-priming, MLE30-priming, seed rate: recommended @ 125 kg ha−1, curtailed @ 25 kg ha−1, and terminal irrigation drought (TID): normal irrigation, mild-TID, severe-TID in wheat crop at agronomic research station, Bahawalpur, Pakistan during the wheat winter season of 2021–2022 and 2022–2023. The application of organic MLE30-priming with curtailed seed rate enhanced antioxidant enzyme activity especially total soluble proteins by 15%, superoxide dismutase by 68%, peroxidase by 16%, catalase by 70%, ascorbic acid by 17% and total protein contents by 91% under severe-TID. Yield and yield-related morphological attributes performed better in MLE30-priming as compared to hydro-priming. An effective trend was observed in the plant's chlorophyll contents, K+, and water use efficiency after being treated with MLE30-priming followed by hydro-priming under curtailed seed rate. The higher benefit–cost ratio and net income return were observed with the application of MLE30-priming with curtailed seed rate under mild-TID and severe-TID. So, it is suggested to adopt the MLE30-priming technique along with a curtailed seed rate for improving the crop establishment, stress regulation, and economic return under limited availability of irrigation water. The project findings recommended that the application of exogenous application of organic MLE30-seed priming favored and compensated the maximum wheat grains production under curtailed seed rate @ 25 kg ha−1 and induced terminal drought stress at flowering and milking conditions. [ABSTRACT FROM AUTHOR]

Global climate changes can dramatically impact wheat production in Brazil's Cerrado biome, considered a new wheat farming frontier. Therefore, new approaches are needed to better understand the G×E interaction in environments that are highly dissimilar in terms of climate variables. Here, we integrate envirotyping, adaptability, and stability techniques to better understand the G × E interaction and provide new insights for the recommendation of tropical wheat genotypes that can perform well in hotter and drier environments. Thirty-six wheat genotypes were evaluated for grain yield in eight field trials in 2018, 2019, and 2020 in the Brazilian tropical region. There is strong evidence that even in irrigated conditions, temperatures > 30 °C during the booting and heading/flowering stages dramatically reduce the grain yield. Two lines, VI14774 (GY = 3800 kg ha−1), and VI14980 (GY = 4093 kg ha−1) had better performance in the hotter environment (~ 22% and ~ 32% higher than the grand mean) and are potential germplasm sources for warmer environments at the boosting and heading/flowering stages. In this study, the REML/BLUP and GGE Biplot methods highly correlate in terms of genotype classification for selection and recommendation purposes. The genotypes VI 14127, VI 14197, VI 14026, and BRS 264 are the closest to a hypothetical ideal genotype. Overall, this study provides new insights on how the environment typing can be useful to better understand the genotype-by-environment interaction and help to breed new climate-resilient wheat cultivars for the Brazilian tropical region. [ABSTRACT FROM AUTHOR]

Grain dormancy of wheat is closely associated with grain color: red-grained lines show higher dormancy than white-grained lines. The production of red pigments is regulated by R-1, Tamyb10 gene. However, the relation between grain color and dormancy remains unknown. For this study, we generated transgenic lines which were introduced a DNA fragment containing Tamyb10-D1 gene and its a 2 kb promoter including the 5′ untranslated region into white-grained wheat. Transgenic lines showed red-grained and higher dormant traits. Contents of plant hormones and gene expression of embryos at 30 days after pollination were examined in a wild type and a transgenic line. No differences were observed in the contents of plant hormones, but several genes are differentially expressed between these lines. One differentially expressed gene, TaLTP2.128, is a member of non-specific lipid transfer proteins. It was expressed higher in white grains than in red grains. A putative amino acid sequence showed similarity to that of OsHyPRP5, which is identified as QTL controlling low-temperature germinability in rice. Expression of TaLTP2.128 was increased by grain imbibition. The increasing levels were higher not only in other white-grained lines, but also in non-dormant red-grained lines. TaLTP2.128 was expressed at a quite early stage of germination. These study findings indicate that Tamyb10 regulates dormancy release by the modification of TaLTP2.128 acting as trigger of germination. [ABSTRACT FROM AUTHOR]

Grain, flour and bread quality parameters were investigated in one Polish and three Ukrainian triticale cultivars, selected as the most suitable for production of bread. The studies revealed large differences in some bread-making parameters. The farinographic parameters of the Ukrainian triticale cultivars were not worse than those of wheat, but the bread loaf volume was lower. The best triticale bread was obtained from the Polish cultivar Panteon, loaf volume and crumb porosity were the highest, in spite of weak results of the farinographic test. Reliability of parameters used for prediction of wheat bread quality in application to triticale is discussed. The laboratory baking is recommended for bakers, breeders and for cultivar testing as the safest method of the evaluation. [ABSTRACT FROM AUTHOR]

In the Indo-Gangetic Plains (IGP), rice–wheat cropping system (RWCS) predominates, producing large quantity of crop residue and its management is major concern. Farmers usually burn the residue to clear the field for succeding crop, and burning damages soil microbes, resulted in loss of soil organic matter. Hence, current study was conducted to assess the impact of different Happy seeder based residue management options on changes in microbial dynamics, enzyme activities and soil organic matter content and also to know that alternative method for attaining sustainable wheat productivity in sandy loam soils of Haryana, India. Results revealed that Zero tillage wheat (ZTW) with partial and full residue retention treatments sown with Happy seeder (after using chopper and spreader), and ZTW with anchored stubbles significantly enhanced soil microbial count by 47.9–60.4%, diazotropic count by 59.0–73.1% and actinomycetes count by 47.3–55.2%, grain yield by 9.8–11.3% and biomass yield by 7.4–9.6% over conventional tilled (CT) residue burning and residue removal plots. ZTW sown with surface retention of rice crop residue increased the organic carbon by 0.36–0.42% and the soil moisture content by 13.4–23.6% over CTW without residue load. Similarly, ZTW sown with Happy seeder with full residue enhanced alkaline phosphatase activity from 95.3 µg TPF g−1 soil 24 h−1 in 2018–2019 to 98.6 µg TPF g−1 soil 24 h−1 in 2019–2020 over control plots. Likely, microbial population and enzymatic activity showed strong positive correlation under variable residue retention practices. However, increased microbial population reduced the soil pH from 7.49 to 7.27 under ZTW with residue retention plots. The wheat yield enhanced by 9.8–11.3% during 2018–2019 and 2019–2020 under ZTW with Happy seeder with full residue load over residue burning and residue removal plots. ZTW sown with Happy seeder under full residue retention, achieved maximum net return 43.16–57.08 × 103 ₹ ha−1) and B-C ratio (1.52 to 1.70) over CTW without residue. Therefore, rice residue needs to be managed by planting wheat using appropriate machinery under ZT for sustaining higher productivity in RWCS and improve soil health and environment under IGP regions. [ABSTRACT FROM AUTHOR]

Root system architecture (RSA) plays a fundamental role in nutrient uptake, including zinc (Zn). Wheat grains are inheritably low in Zn. As Zn is an essential nutrient for plants, improving its uptake will not only improve their growth and yield but also the nutritional quality of staple grains. A rhizobox study followed by a pot study was conducted to evaluate Zn variability with respect to RSA and its impact on grain Zn concentration. The grain Zn content of one hundred wheat varieties was determined and grown in rhizoboxes with differential Zn (no Zn and 0.05 mg L−1 ZnSO4). Seedlings were harvested 12 days after sowing, and root images were taken and analyzed by SmartRoot software. Using principal component analysis, twelve varieties were screened out based on vigorous and weaker RSA with high and low grain Zn content. The screened varieties were grown in pots with (11 mg ZnSO4 kg−1 soil) and without Zn application to the soil. Zinc translocation, localization, and agronomic parameters were recorded after harvesting at maturity. In the rhizobox experiment, 4% and 8% varieties showed higher grain Zn content with vigorous and weaker RSA, respectively, while 45% and 43% varieties had lower grain Zn content with vigorous and weaker RSA. However, the pot experiment revealed that varieties with vigorous root system led to higher grain yield, though the grain Zn concentration were variable, while all varieties with weaker root system had lower yield as well as grain Zn concentration. Zincol-16 revealed the highest Zn concentration (28.07 mg kg−1) and grain weight (47.9 g). Comparatively higher level of Zn was localized in the aleurone layer than in the embryonic region and endosperm. It is concluded that genetic variability exists among wheat varieties for RSA and grain Zn content, with a significant correlation. Therefore, RSA attributes are promising targets for the Zn biofortification breeding program. However, Zn localization in endosperm needs to be further investigated to achieve the goal of reducing Zn malnutrition. [ABSTRACT FROM AUTHOR]

In the Indo-Gangetic Plains (IGP), rice–wheat cropping system (RWCS) predominates, producing large quantity of crop residue and its management is major concern. Farmers usually burn the residue to clear the field for succeding crop, and burning damages soil microbes, resulted in loss of soil organic matter. Hence, current study was conducted to assess the impact of different Happy seeder based residue management options on changes in microbial dynamics, enzyme activities and soil organic matter content and also to know that alternative method for attaining sustainable wheat productivity in sandy loam soils of Haryana, India. Results revealed that Zero tillage wheat (ZTW) with partial and full residue retention treatments sown with Happy seeder (after using chopper and spreader), and ZTW with anchored stubbles significantly enhanced soil microbial count by 47.9–60.4%, diazotropic count by 59.0–73.1% and actinomycetes count by 47.3–55.2%, grain yield by 9.8–11.3% and biomass yield by 7.4–9.6% over conventional tilled (CT) residue burning and residue removal plots. ZTW sown with surface retention of rice crop residue increased the organic carbon by 0.36–0.42% and the soil moisture content by 13.4–23.6% over CTW without residue load. Similarly, ZTW sown with Happy seeder with full residue enhanced alkaline phosphatase activity from 95.3 µg TPF g−1 soil 24 h−1 in 2018–2019 to 98.6 µg TPF g−1 soil 24 h−1 in 2019–2020 over control plots. Likely, microbial population and enzymatic activity showed strong positive correlation under variable residue retention practices. However, increased microbial population reduced the soil pH from 7.49 to 7.27 under ZTW with residue retention plots. The wheat yield enhanced by 9.8–11.3% during 2018–2019 and 2019–2020 under ZTW with Happy seeder with full residue load over residue burning and residue removal plots. ZTW sown with Happy seeder under full residue retention, achieved maximum net return 43.16–57.08 × 103 ₹ ha−1) and B-C ratio (1.52 to 1.70) over CTW without residue. Therefore, rice residue needs to be managed by planting wheat using appropriate machinery under ZT for sustaining higher productivity in RWCS and improve soil health and environment under IGP regions. [ABSTRACT FROM AUTHOR]

In the context of degradation of soil health, environmental pollution, and yield stagnation in the rice–wheat system in the Indo-Gangetic Plains of South Asia, an experiment was established in split plot design to assess the long-term effect of crop residue management on productivity and phosphorus requirement of wheat in rice–wheat system. The experiment comprised of six crop residue management practices as the main treatment factor with three levels (0, 30 and 60 kg P2O5 ha–1) of phosphorus fertilizer as sub-treatments. Significant improvement in soil aggregation, bulk density, and infiltration rate was observed under residue management (retention/incorporation) treatments compared to residue removal or residue burning. Soil organic carbon (SOC), available nutrient content (N, P, and K), microbial count, and enzyme activities were also significantly higher in conservation tillage and residue-treated plots than without residue/burning treatments. The residue derived from both crops when was either retained/incorporated improved the soil organic carbon (0.80%) and resulted in a significant increase in SOC (73.9%) in the topsoil layer as compared to the conventional practice. The mean effect studies revealed that crop residue management practices and phosphorus levels significantly influenced wheat yield attributes and productivity. The higher grain yield of wheat was recorded in two treatments, i.e. the basal application of 60 kg P2O5 ha–1 without residue incorporation and the other with half the P-fertilizer (30 kg P2O5 ha–1) with rice residue only. The grain yield of wheat where the rice and wheat residue were either retained/incorporated without phosphorus application was at par with 30 and 60 kg P2O5ha–1. Phosphorus levels also significantly affected wheat productivity and available P content in the soil. Therefore, results suggested that crop residue retention following the conservation tillage approach improved the yield of wheat cultivated in the rice–wheat cropping system. [ABSTRACT FROM AUTHOR]

Nickel (Ni) is known as a plant micronutrient and serves as a component of many significant enzymes, however, it can be extremely toxic to plants when present in excess concentration. Scientists are looking for natural compounds that can influence the development processes of plants. Therefore, it was decided to use proline as a protective agent against Ni toxicity. Proline (Pro) is a popularly known osmoprotectant to regulate the biomass and developmental processes of plants under a variety of environmental stresses, but its role in the modulation of Ni-induced toxicity in wheat is very little explored. This investigation indicated the role of exogenously applied proline (10 mM) on two wheat varieties (V1 = Punjab-11, V2 = Ghazi-11) exposed to Ni (100 mg/kg) stress. Proline mediated a positive rejoinder on morphological, photosynthetic indices, antioxidant enzymes, oxidative stress markers, ion uptake were analyzed with and without Ni stress. Proline alone and in combination with Ni improved the growth, photosynthetic performance, and antioxidant capacity of wheat plants. However, Ni application alone exhibited strong oxidative damage through increased H2O2 (V1 = 28.96, V2 = 55.20) accumulation, lipid peroxidation (V1 = 26.09, V2 = 38.26%), and reduced translocation of macronutrients from root to shoot. Application of Pro to Ni-stressed wheat plants enhanced actions of catalase (CAT), peroxidase (POD), superoxide dismutase (SOD), and total soluble protein (TSP) contents by 45.70, 44.06, 43.40, and 25.11% in V1, and 39.32, 46.46, 42.22, 55.29% in V2, compared to control plants. The upregulation of antioxidant enzymes, proline accumulation, and uptake of essential mineral ions has maintained the equilibrium of Ni in both wheat cultivars, indicating Ni detoxification. This trial insight into an awareness that foliar application of proline can be utilized as a potent biochemical method in mitigating Ni-induced stress and might serve as a strong remedial technique for the decontamination of polluted soil particularly with metals. [ABSTRACT FROM AUTHOR]

Wheat is one of the most produced and consumed grain products worldwide. Wheat is the main grain product in developed and underdeveloped countries. Flour obtained from wheat is used in the production of bread, the most basic food product, and in the production of cakes used to celebrate the most special days. Therefore, knowing the pure bread wheat varieties is important both for production and for those who use wheat as flour. However, since wheat varieties are very similar to each other, it is difficult to distinguish them. To solve this problem, a pre-trained hybrid model based on convolutional neural network (CNN) is proposed in this study to classify bread wheat varieties. Images of five different registered bread wheat varieties were captured and a bread wheat image data set was created by separating them with image processing techniques to be used in deep learning. Then, the obtained images were classified using transfer learning with fine-tuning on the Xception model, one of the pre-trained CNN models. To increase the classification success, Xception CNN model and BiLSTM (Bidirectional Long Short-Term Memory) algorithms hybrid (Xception + BiLSTM) models were obtained. As a result of classifications, the highest classification success was obtained from the Xception + BiLSTM model with 97.73%. The results revealed that the proposed methods can be used in systems used for classification of bread wheat varieties and to obtain pure wheat varieties automatically. [ABSTRACT FROM AUTHOR]

Wheat is unquestionably the primary source of sustenance in human dietary intake. The cultivation areas and production capacity of wheat worldwide have been observed to increase in parallel with the growth of the global population. Wheat grains from different varieties, when mixed with durum wheat, result in a reduction in the protein content. Various types of wheat grains also exhibit the same characteristic. In this particular scenario, the significance of accurately categorizing wheat becomes more pronounced. In recent years, there has been a proliferation of studies aimed at categorizing agricultural products through the application of deep learning and machine learning methodologies. In the present study, a novel approach was introduced to simultaneously analyze deep features and image patches. This was achieved by utilizing a dataset consisting of a comprehensive collection of 8354 images, encompassing various bread wheat varieties. The classification of wheat types was carried out by employing feature extraction using three distinct methods. MobileNetV2, EfficientNetV2B0, GLCM, and Color-Space algorithms were employed to extract features from the images. Lastly, the Support Vector Machine (SVM), Random Subspace ensemble with k-Nearest Neighbors (RSeslibKnn), Artificial Neural Network (ANN), and Random Forest algorithms were employed to develop models for the classification of bread wheat images. The evaluation of the experimental performances was conducted based on the criteria of accuracy, precision, recall, F-score, and mean absolute error (MAE). In general, the obtained accuracies ranged from 91.50 to 98.65%, which demonstrates the models' proficiency in accurately classifying the samples. When examining different algorithms, Support Vector Machines (SVM) consistently demonstrate robust performance by achieving high levels of accuracy, precision, recall, and F-scores across various feature combinations. [ABSTRACT FROM AUTHOR]

Changes in yield components and spike traits are associated with wheat grain yield genetic progress. The aim of this study was to determine variation in yield components, spike and individual grain traits, and their role in winter wheat grain yield genetic improvement under conditions of the Pannonian Plain. Therefore, two-year field trials were conducted in a southern Pannonian location (Novi Sad, Serbia) with ten winter wheat cultivars released between 1931 and 2015. The grain yield had a significant positive linear relationship with the year of cultivar release, showing the improvement rate of 46.4 kg ha−1 yr−1. Grain yield increase has been positively related to the improvement of spike grain weight. Spike grain weight improvement with a rate of 0.25 g yr−1 was followed by simultaneous rise of the individual grain number and grain weight at different positions within a spikelet. Compared to other grains at different positions within a spikelet, G3 grains showed the highest rate of grain weight and the grain number improvement with the year of cultivar release. On the other hand, there was a significant decrease trend of grain protein content in individual grains at different positions. Therefore, wheat breeders should be more focused on grain number and weight improvement of distal grains in order to regain higher grain yield genetic gain under conditions of the Pannonian Plain. [ABSTRACT FROM AUTHOR]

The majority of farmers (85%) in Asia operate on small plots (< 2 ha) under low-input conditions to support their livelihoods. Wheat production in India faces challenges due to water scarcity and suboptimal nitrogen (N) management practices. To address this problem, a multi-location (9) field experiment comprising of 9 treatments by including nano and prilled urea alone or in combination was conducted under restricted irrigation conditions (only two irrigations i.e., first at crown root initiation stage and 2nd at flag leaf stage) during 2021–2022 and 2022–2023 in randomised block design with three replications in three agro-climatic regions (NWPZ- North Western Plains Zone, NEPZ- North Eastern Plains Zone and CZ- Central Zone) of India. Results indicated that combining recommended nitrogen (RDN) i.e., 90 kg/ha with two sprays of 5% urea increased grain yield by 4.1% and 41.9% in NWPZ and NEPZ, respectively, over RDN alone. Two sprays of nano urea at tillering and jointing stages significantly outperformed the control (Zero N), increasing grain yield by 14.5%, 34.0%, and 19.2% in NWPZ, NEPZ, and CZ, respectively. Moreover, RDN with two sprays of nano urea increased the grain yield and agronomic efficiency by 12.1% and 12.0% in CZ and 25.2% and 24.6% in NEPZ over RDN alone, respectively. From a net benefit perspective, RDN with two sprays of 5% urea was 6.7 and 70.4% higher in NWPZ and NEPZ over RDN under restricted irrigation. In CZ, applying RDN with two sprays of nano urea provided 15.5% higher net benefit over RDN. The recommendation for wheat cultivation in small-scale farming systems in India under restricted irrigation conditions suggests adopting a nitrogen management approach combining RDN with two sprays of 5% urea in NWPZ and NEPZ or with two sprays of nano urea in NEPZ and CZ improved the productivity, profitability and agronomic efficiency. [ABSTRACT FROM AUTHOR]