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Accurate production estimates, months before the harvest, are crucial for all parts of the food supply chain, from farmers to governments. While methods have been developed to use satellite data to monitor crop development and production, they typically rely on official crop statistics or ground-based data, limiting their application to the regions where they were calibrated. To address this issue, a new method called VeRsatile Crop Yield Estimator (VeRCYe) has been developed to estimate wheat yield at the pixel and field levels using satellite data and process-based crop models. The method uses the Leaf Area Index (LAI) as the linking variable between remotely sensed data and APSIM crop model simulations. In this process, the sowing dates of each field were detected (RMSE = 2.6 days) using PlanetScope imagery, with PlanetScope and Sentinel-2 data fused into a daily 3 m LAI dataset, enabling VeRCYe to overcome the traditional trade-off between satellite data that has either high temporal or high spatial resolution. The method was evaluated using 27 wheat fields across the Australian wheatbelt, covering a wide range of pedo-climatic conditions and farm management practices across three growing seasons. VeRCYe accurately estimated field-scale yield (R2 = 0.88, RMSE = 757 kg/ha) and produced 3 m pixel size yield maps (R2 = 0.32, RMSE = 1213 kg/ha). The method can potentially forecast the final yield (R2 = 0.78–0.88) about 2 months before the harvest. Finally, the harvest dates of each field were detected from space (RMSE = 2.7 days), indicating when and where the estimated yield would be available to be traded in the market. VeRCYe can estimate yield without ground calibration, be applied to other crop types, and used with any remotely sensed LAI information. This model provides insights into yield variability from pixel to regional scales, enriching our understanding of agricultural productivity. [ABSTRACT FROM AUTHOR]

Wheat is an essential crop for food security in North Africa. However, it's productivity is limited by several factors, among them climate change effects. Predicting wheat yield on a large scale is thus important for ensuring food security, as it allows farmers and policymakers to make informed decisions regarding agricultural production and marketing. Machine learning (ML) algorithms have been used in previous studies to predict wheat yield in Africa, but there is still a need for improvement in terms of accuracy and usability. The advantage of using several ML algorithms is that it allows for comparing and selecting the best-performing model. The objective of this study is to develop an accessible and user-friendly web-based application that predicts wheat yield using an ensemble learning model that integrates four feature scaling algorithms (Min-Max, Z- score, MaxAbsScaler, and Robust scaling) and seven ML techniques (LASSO, Extreme Gradient Boosting [XGBoost], Random Forest [RF], Linear Regression [LR], Ridge, Gradient Boosting Regression [GBR], Support Vector Regression [SVR]), based on meteorological data (rainfall and temperature), and agriculture and soil properties (pesticides, fertilizers, and irrigation). Findings show that the GBR algorithm with MaxAbsScaler feature scaling is the best with an R 2 of 97%, demonstrating the developed model's effectiveness. Farmers and farm managers could use the suggested model for better decisions, contributing to food productivity and security in North Africa. [ABSTRACT FROM AUTHOR]

AbstractCurrent agricultural production systems face challenges of poor economic returns, soil fatigue and negative environmental outcomes from excess use of nitrogenous fertilizers, especially in wheat production under middle gangetic plains. To overcome these challenges, the current study was conducted to optimize nitrogen management in different wheat genotypes with precision nitrogen management tools and approaches. The field experiment was laid out in split-plot design, with three genotypes assigned to the main plot and six nitrogen management practices to the sub-plot. The soil of the experimental field was sandy loam in texture, with low levels of organic carbon and available nitrogen, and medium levels of available phosphorus and potassium. Results revealed that the HD-2967 genotype outperformed others in terms of growth, grain yield (4.7 and 4.81 t ha−1), gross return (1417.41 and 1505.48 US$ ha−1), net return (953.43 and 1019.76 US$ ha−1), and B-C ratio (2.04 and 2.08) in 2015-16 and 2016-17, respectively. Among the nitrogen management practices, application of 150 kg N ha−1 in three equal splits demonstrated improved crop growth, grain yield (4.7 and 4.81 t ha−1), and economic returns (gross return, 1500.40 and 1607.65 US$ ha−1, net return, 1025.40 and 1110.38 US$ ha−1 and B: C ratio, 2.17 and 2.23) in 2015-16 and 2016-17, respectively. However, it resulted in higher nitrogen losses. Green seeker guided N application significantly reduced apparent nitrogen losses compared to all other nitrogen applied treatments. These findings provide valuable insights for optimizing wheat production by selecting appropriate genotypes and implementing precision nitrogen management techniques to enhance yield, profitability, and environmental sustainability. [ABSTRACT FROM AUTHOR]

This study explored the efficacy of soil aggregate indices in quantifying soil structural development, utilizing 5‐year field experiment data from the Southeastern United States. The experiment utilized a split‐plot design with cover crops (native vegetation as control, cereal rye (Secale cereale L.), winter wheat (Triticum aestivum), hairy vetch (Vicia villosa), and mustard (Brassica rapa) plus cereal rye as the main factor and fertilizer source (no fertilizer as control, inorganic fertilizer with phosphorus, potassium, and elemental sulfur, and poultry litter) as the secondary factor. Aggregate size fractions were determined using the wet‐sieving method, and aggregate stability index (ASI), mean weight diameter (MWD), geometric mean diameter (GMD), and fractal dimension (FD) were calculated to assess soil structural stability. Main effects results indicated that cereal rye (55.11%) and poultry litter (50.97%) exhibited the highest ASI values. The highest MWD, GMD, and FD were observed under mustard plus cereal rye (1.187 mm), cereal rye (0.462 mm), and hairy vetch (2.573), respectively. Principal component analysis revealed that cover crops significantly improved soil aggregate structure and stability, overcoming limitations of sole fertilization practices. Regression analysis suggested that ASI, MWD, and GWD positively correlated with soil organic carbon, whereas FD negatively correlated with MWD, GMD, and ASI. Principal component analysis exhibited that FD decreased with increasing soil organic carbon, ASI, MWD, and GMD, demonstrating that lower FD values indicate enhanced soil aggregation and structure. Assessed indices, FD included, effectively gauged soil structural stability. These metrics should be prioritized in managerial decisions to support soil productivity and health in agricultural systems. Core Ideas: The application of cereal rye and poultry litter increased the aggregate stability index (ASI).Poultry litter addition was beneficial to improving mean weight diameter (MWD).ASI, MWD, and geometric mean diameter (GMD) positively correlated with soil organic carbon.Fractal dimension (FD) is negatively correlated with MWD, GMD, and ASI.The evaluated indices (ASI, MWD, and GMD) and FD were effective in assessing soil structural stability. [ABSTRACT FROM AUTHOR]

A strongly declining aerosol radiative effect has been observed in China since 2013 after implementing the clean air action, yet its impact on wheat (Triticum aestivum L.) production remains unclear. We use satellite measures and a biophysical crop model to assess the impact of aerosol-induced radiative perturbations on winter wheat production in the agricultural belt of Henan province from 2013 to 2018. After calibrating parameters with the extended Fourier Amplitude Sensitivity Test (EFAST) and the generalized likelihood uncertainty estimation (GLUE) method, the DSSAT CERES-Wheat model was able to simulate crop biomass and yield more accurately. We found that the aerosol negatively impacted wheat biomass by 21.87% and yield by 22.48% from 2006 to 2018, and the biomass effects from planting to anthesis were more significant compared to anthesis to maturity. Due to the strict clean air action, under all-sky conditions, the surface solar shortwave radiation (SSR) in 2018 increased by about 7.08% over 2006-2013 during the wheat growing seasons. As a result of the improvement of crop photosynthesis, winter wheat biomass and yield increased by an average of 5.46% and 2.9%, respectively. Our findings show that crop carbon uptake and yield will benefit from the clean air action in China, helping to ensure national food and health security. [ABSTRACT FROM AUTHOR]

Copyright of Anbar Journal of Agricultural Sciences is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Anbar Journal of Agricultural Sciences is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Wheat (Triticum aestivum L.) is one of the most important strategic crops to overcome food security problems in the world including Ethiopia. This can be achieved through genetic improvement of the crop and its production practices. In this connection, information on the mutual association of traits is important for effective selection in wheat‐breeding programs. In 2021/2022 production year, a field experiment was undertaken to estimate the extent of genetic variability, path analysis, and association of yield and yield‐related characteristics for the selection of desirable wheat genotypes. A total of 64 bread wheat genotypes, including yellow rust‐resistant Boru (resistant), Hachalu (moderately resistant), and Madda‐Walabu (susceptible) as control, were used for the field experiment at Sinana and Agarfa Agricultural Research Centers. The experiment was laid out in a simple alpha lattice design. The mean analysis of variances showed highly significant differences (p < 0.001) for all traits among the tested genotypes. The value of the phenotypic coefficient of variance was higher than the genotypic coefficient of variance for all studied traits, indicating the presences of higher genetic variability among the tested genotypes. Grain yield had a significant positive correlation with days to maturity, grain‐filling period, plant height, kernels spike−1, thousand seed weight, and biological yield at both genotypic and phenotypic levels including spike length at phenotypic levels at both locations and with plant height, thousand seed weight, and biological yield at both locations at genotypic and phenotypic levels. Similarly, days to maturity and grain‐filling period also showed a significant positive phenotypic correlation with grain yield. The analyzed path coefficients at both genotypic and phenotypic levels also indicated how grain yield is influenced directly and indirectly by other yield and yield‐related traits. The result also showed the existence of good heritability values along with high genetic advance, higher phenotypic coefficient of variation and genotypic coefficient of variation for grain yield, biological yield, and grain‐filling period. This implies the true relationship among these traits and grain yield; therefore, due attention should be paid to such traits during selection for further improvement. Hence, the present study indicated the importance of the direct and indirect effects of the studied traits on yield and yield components which makes selection desirable for improving the grain yield of wheat and its genetic resistance against yellow rust in the study area. Core Ideas: Wheat (Triticum aestivum L.) is one of the most important strategic crops to overcome food security.Wheat yield can be increased through genetic improvement of the crop and its production practices.Genetic variability, path analysis, and association of yield and yield‐related characteristics are desirable.Higher values of the phenotypic coefficient of variance were obtained for all the studied traits.The presence of additive gene action was observed that makes selection a good breeding strategy. [ABSTRACT FROM AUTHOR]

The assessment of soil health through a robust index system having a sufficient number of indicators is an important step toward sustainable crop production. The present study aimed at establishing a minimum data set (MDS) from soil functional and nutritional attributes using a dual index system to evaluate the soil health of farmlands under wheat (Triticum aestivum)–maize (Zea mays) crop rotation in Yanting County, Sichuan, China. Farms from 10 villages in the study area were selected, out of which three sites were considered healthy/ideal sites and used as a reference for the remaining seven targeted sites, and soil samples were collected at depth of 20 cm from these farms. The MDS indicators were selected by using principal component analysis (PCA) followed by Pearson's correlation on 25 attributes. Based on significant values, eight attributes were retained in the final MDS, including the sucrase level, pH, wilting coefficient, water holding capacity, organic matter, NK ratio, total potassium, and available phosphorus. Based on the results, most of the farmland soils in Yanting County were in a healthy condition, accounting for 61.71% of the surveyed samples, followed by sub-healthy, degraded, and weak soils, accounting for 19.64%, 9.71%, and 8.93%, respectively. The values of most of the indicators at the targeted sites were significantly lower than those at ideal sites. Thus, specific steps should be taken by adding soil organic matter, combined with other fertilizers, to enhance the microbial biomass, enzymatic activities, and other biological activities in the soil. [ABSTRACT FROM AUTHOR]

Feeding the world's ever‐increasing population requires continuous development of high‐yielding and disease‐resistant cultivars of food crops such as wheat (Triticum aestivum L.). Speed breeding, which utilizes longer photoperiod times and higher temperatures, is a technique that accelerates plant development and is rapidly being adopted by wheat breeders across the globe to fast‐track cultivar development. Plant diseases are a major threat to crop production, and breeding for disease resistance is a major goal of crop breeders. Fusarium head blight (FHB), caused by Fusarium graminearum, is a major disease of small grain cereals, affecting their yield and quality. The aim of present work was to assess if speed breeding conditions can be used to accelerate reliable assessment of FHB severity and mycotoxin deoxynivalenol (DON) accumulation in wheat varieties. We screened a set of six spring wheat genotypes with different levels of genetic resistance (two moderately susceptible, two highly susceptible, one moderately resistant, and one resistant) for their response to FHB at 14 days after inoculation (dai) and 21 dai and DON accumulation under normal versus speed breeding conditions. FHB severity and DON accumulation were found to be highly correlated at all time points under normal and speed breeding conditions. Robust differentiation between resistant and susceptible genotypes could be achieved at 14 dai rather than the normal period of 21 dai, saving at least a week in phenotyping. Combined with the accelerated growth, flowering, and maturity under these conditions, efficient FHB screening and DON evaluation under speed breeding conditions will fast‐track development of resistant wheat varieties. Core Ideas: Speed breeding is increasingly being adopted by crop breeding programs.We evaluated spring wheat genotypes with different levels of genetic resistance for Fusarium head blight (FHB) and deoxynivalenol (DON) levels under speed breeding versus regular conditions.Reliable distinction could be made in FHB severity at 14 days after inoculation (dai) under speed breeding as compared to 21 dai under normal growth conditions.Growing and testing the plants under speed breeding conditions saved a total of 21–23 days as compared to regular conditions. [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]

Crop residues are the main organic source of nutrients in agricultural soils. The active pool of soil organic carbon plays a dominant role in crop production and soil health. Rice and wheat residues were used in 90 days incubation study under controlled conditions (25°C temperature and maximum water-holding capacity) to estimate the release of carbon dioxide and water-soluble carbon in an Indo-Gangetic alluvial soil (Inceptisols) of Varanasi. The experiment was laid out in a factorial completely randomized design with three replications. The rice and wheat residues showed a wide variation in the content of their total carbon (TC), total nitrogen (TN), total phosphorus (TP) and total sulfur (TS). Out of the two crop residues added to the soil, rice residue had higher carbon dioxide-carbon (CO2-C) release than that of the wheat residue over control. Results revealed that conjunctive application of rice residue along with urea (20 kg N ha−1) and Trichoderma viride (10 kg ha−1) had resulted in a higher content of CO2-C (7.44 mg per 100 g per day) at 90 days of the incubation period. The amount of CO2 (mg) released, increases with a combination of crop residues with urea (20 kg N ha−1) and Trichoderma viride (10 kg ha−1) up to 90 days over control. The highest release of CO2 (204.70 mg) was recorded with rice residue treated with urea (20 kg N ha−1) and Trichoderma viride (10 kg ha−1). The study also revealed that the release of water-soluble carbon decreases with an increase in the incubation period irrespective of treatment. At 90 days of the incubation period, the control without any crop residue addition has the highest water-soluble carbon content (459.75 µg/g). The present study indicates that the incorporation of rice and wheat residues along with urea and supplemental decomposers (Trichoderma viride) has the potential to release adequately active organic carbon pool parameters such as CO2 and water-soluble carbon in an Inceptisols of Varanasi region of India. [ABSTRACT FROM AUTHOR]

Drought stress constricts crop production around the world. Employing high-yielding cultivars with drought tolerance might be the ideal professional approach to coping with its detrimental outcomes. As a result, the current study was performed to investigate the sensitivity and tolerance of nine wheat genotypes to drought stress. In a randomized block design experiment, nine wheat genotypes were subjected to four water treatments: 100%, 85%, 70%, and 55% of the available water (AW). Four water regimes in two growing seasons were counted as eight environmental zones. The leaf's water relations and photosynthetic pigment were estimated, as well as growth and yield parameters. Univariate and multivariate statistical approaches, including the new method of multi-trait genotype–ideotype distance (MGIDI), were used for evaluation. The analysis of variance revealed that genotype, environment, and their interactions had a highly significant effect on all traits. The same trend was shown by the additive main effects and multiplicative interaction (AMMI) analysis of variance for grain yield across the environments. The AMMI biplot study indicated that the G8 genotype is the most stable in terms of water stress. The G7 genotype can withstand droughts up to 55% of the available water, while the G8 and G3 genotypes can withstand droughts up to 70% of the available water. Based on all examined traits, this index was used to identify the stable genotypes G7, G8, and G3, which can therefore be suggested for cultivation during drought conditions. Furthermore, we found a positive correlation between the MGIDI, ANOVA, and tolerance index results, indicating that the same desirable genotypes of G7 and G8 were identified by these procedures as being highly tolerant and stable across a range of soil moisture conditions. Based on MGIDI analysis, we can recommend that the G7 genotype exhibits higher grain yield and yield-related traits with the best drought-tolerant indices. [ABSTRACT FROM AUTHOR]

Drought stress is the prime obstacle for worldwide agricultural production and necessitates innovative strategies for enhancing crop resilience. This study explores the efficacy of plant growth-promoting rhizobacteria (PGPR) and biochar (BC) as sustainable amendments for mitigating the effects of drought on wheat growth. Multiple experiments were carried out on isolated strains to assess their drought tolerance potential and multiple plant growth-promoting attributes. Experiments in the laboratory and natural environment were conducted to assess the impact of plant growth-promoting rhizobacteria, biochar, and their synergistic application on various growth parameters of wheat. The results revealed that the drought-tolerant PGPR strains (Bacillus subtilis and Bacillus tequilensis), alongside biochar (rice husk), alleviated the phytotoxic impact of drought by increasing the root length from 17.0% to 70.0% and shoot length from 30.0% to 82.0% as compared to un-inoculated stressed controls. The total chlorophyll and carotenoid contents of the plants were substantially increased to 477% and 423%, respectively, when biochar and PGPR were applied synergistically. Significant enhancements in membrane stability index, relative water content, proline, and sugar level were achieved by combining biochar and bacterial strains, resulting in increases of 19.5%, 37.9%, 219%, and 300%, respectively. The yield of wheat in terms of plant height, spike length, number of spikelets per spike, and number of grains per spike was enhanced from 26.7% to 44.6%, 23.5% to 62.7%, 91.5% to 154%, and 137% to 182%, respectively. It was concluded that the biochar-based application of PGPR induced drought tolerance in wheat under water deficit conditions, ultimately improving the production and yield of wheat. [ABSTRACT FROM AUTHOR]

Fusarium head blight (FHB) is a major threat to wheat crop production and food security worldwide. The creation of resistant wheat cultivars is an essential component of an integrated strategy against Fusarium graminearum, the primary aetiological agent that causes FHB. The results of this study show that the deployment of proto-cooperative interactions between wheat genotypes and mycoparasitic biocontrol agents (BCAs) can improve crop yield and plant resistance in controlling the devastating effects of FHB on wheat agronomic traits. A Fusarium-specific mycoparasite, Sphaerodes mycoparasitica, was found to be compatible with common and durum wheat hosts, thus allowing the efficient control of F. graminearum infection in plants. Four genotypes of wheat, two common wheat, and two durum wheat cultivars with varying FHB resistance levels were used in this greenhouse study. The BCA treatments decreased FHB symptoms in all four cultivars and improved the agronomic traits such as spike number, spike weight, seed weight, plant biomass, and plant height which are vital to grain yield. Conversely, the F. graminearum 3ADON chemotype treatment decreased the agronomic trait values by up to 44% across cultivars. Spike number, spike weight, and seed weight were the most improved traits by the BCA. A more measurable improvement in agronomic traits was observed in durum wheat cultivars compared to common wheat. [ABSTRACT FROM AUTHOR]

Our aim was to characterize the changes in N% by organs of Tr. aestivum L. varieties, grown in transition to organic production (TOP) and conventional production (CP) during the period 2018-2020. The varieties - Dragana, Rada, Pchelina, Kocara and Kalina were grown after predecessors - winter oil rape, spring peas, sunflower and maize for grain. At CP, fertilization was on a PK background of P60 K60 and after peas 0, 30, 60 and 90 kg N/ha, and after the others - 0, 60, 120 and 180 kg N/ha. In TOP, the leaves N% is influenced to the maximum extent by the type of the predecessor. In CP however, mineral fertilization has a determining role for the dynamics of N% in leaves, stems and grain, while that in the non-grain part of the spike - the conditions of the year. Cultivation after a maize predecessor results in higher N% remaining in the organs of the noneconomic part of the crop. At CP, wheat forms a grain with the highest protein content after winter oil rape. As with TOP, the varieties Pchelina and Rada are distinguished by a higher protein content compared to the others. Nitrogen concentration in the organs of wheat grown under CP is higher than the same under TOP. Significant dynamics by year was found in the N% in the leaves, where the excess was respectively 87.85% (2018), 78.89% (2019) and 18.47 (2020). For grain, these values are respectively - 38.15%, 25.40% and 9.03%. [ABSTRACT FROM AUTHOR]

Hypoxia is one of the common abiotic stresses that negatively affects the development and productivity of agricultural crops. Quercetin is used to protect plants from oxidative stress when exposed to environmental stressors. O2 deficiency leads to impaired development and morphometric parameters in wheat varieties Orenburgskaya 22 (Triticum aestivum L.) and varieties Zolotaya (Triticum durum Desf.). Cytological analysis revealed various types of changes in the cytoplasm under conditions of hypoxia and treatment with quercetin. The most critical changes in the cytoplasm occur in the Zolotaya variety during pretreatment with quercetin followed by hypoxia, and in the Orenburgskaya 22 variety during hypoxia. Quercetin has a protective effect only on the Orenburgskaya 22 variety, and also promotes a more effective recovery after exposure to low O2 content. Hypoxia causes an increase in reactive oxygen species and activates the antioxidant system. It has been shown that the most active components of the antioxidant system in the Orenburgskaya 22 variety are MnSOD and Cu/ZnSOD, and in the Zolotaya variety GSH. We have shown that quercetin provides resistance only to the wheat genotype Orenburgskaya 22, as a protective agent against abiotic stress, which indicates the need for a comprehensive study of the effects of exogenous protectors before use in agriculture. [ABSTRACT FROM AUTHOR]

Drought is a major global challenge in agriculture that decreases crop production. 1-Aminobutyric acid (GABA) interfaces with drought stress in plants; however, a mechanistic understanding of the interaction between GABA accumulation and drought response remains to be established. Here we showed the potassium/proton exchanger TaNHX2 functions as a positive regulator in drought resistance in wheat by mediating cross-talk between the stomatal aperture and GABA accumulation. TaNHX2 interacted with glutamate decarboxylase TaGAD1, a key enzyme that synthesizes GABA from glutamate. Furthermore, TaNHX2 targeted the C-terminal auto-inhibitory domain of TaGAD1, enhanced its activity, and promoted GABA accumulation under drought stress. Consistent with this, the tanhx2 and tagad1 mutants showed reduced drought tolerance, and transgenic wheat with enhanced TaNHX2 expression had a yield advantage under water deficit without growth penalty. These results shed light on the plant stomatal movement mechanism under drought stress and the TaNHX2-TaGAD1 module may be harnessed for amelioration of negative environmental effects in wheat as well as other crops. [ABSTRACT FROM AUTHOR]

Whole-crop wheat (Triticum aestivum, WCW) has a high nutritional value and digestibility. No-tillage (NT) can reduces energy and labor inputs in the agricultural production process, thus decreasing production costs. There are many studies on planting techniques of WCW at present, few being on no-tillage planting. This study aimed to compare the effects of different tillage methods and maturity stages on the yield, nutritive value, and silage fermentation quality of WCW. The experiment included two tillage methods (NT; conventional tillage, CT), two maturity stages (flowering stage; milk stage), and three years (2016-2017; 2017-2018; 2018-2019). Years had a strong influence on the yield and nutritional composition of WCW. This was mainly related to the amount of rainfall, as it affects the seedling emergence rate of wheat. Although tillage methods showed no significant effects on the yield, plant height, and stem number per plant of WCW (P > 0.05), compared to CT, the dry matter (DM) and crude protein (CP) yields of NT decreased by 0.74 t/ha and 0.13 t/ha. Tillage methods showed no significant effects on the nutritive composition of WCW (P > 0.05). The WCW at the milk stage had greater DM (5.25 t/ha) and CP (0.60 t/ha) yields than that at the flowering stage (3.19 t/ha and 0.39 t/ha) (P< 0.05). The acid detergent fiber concentration of WCW decreased by 34.5% from the flowering to the milk stage, whereas water-soluble carbohydrates concentration increased by 50.6%. The CP concentration at the milk stage was lower than that at the flowering stage (P< 0.05). The lactic acid concentration of NT (17.1 g/kg DM) silage was lower than that of CT (26.6 g/kg DM) silage (P< 0.05). The WCW silage at the milk stage had a lower NH3-N concentration (125 g/kg TN) than that at the flowering stage (169 g/kg TN) (P< 0.05). Wheat sown by NT and CT was of similar yield and nutritional value, irrespective of harvest stages. WCW harvested at the milk stage had greater yield and better nutritional composition and silage fermentation quality than that at the flowering stage. Based upon the results of the membership function analysis, no-tillage sowing of wheat was feasible and harvesting at milk stage was recommended. [ABSTRACT FROM AUTHOR]

Background: Wheat is a cereal crop that is widely farmed across the world and ranks first in global crop production. Wheat cultivation is the world's most important food crop. The assessment of genetic divergence existing in the germplasm collections is very important to select genetically divergent parents for hybridization in a transgressive breeding programme for development of high yielding wheat varieties coupled with quality, multiple resistance and wider adaptability. Methods: The experiment on 21genotypes including two checks viz., HD 2967 and PBW 824 was conducted to work out the genetic variability, heritability, genetic advance and divergence analysis for yield and yield contributing traits in wheat (Triticum aestivum L.). The experiment was laid out in randomised block design (RBD) during Rabi, 2021-2022 at Lovely Professional University, Phagwara, Punjab. Result: The analysis of variance revealed mean sum of square due to genotypes were significant for all the characters indicating sufficient genetic variability among the genotypes. The magnitude of PCV and GCV were moderate for grain yield per plant and harvesting index, which suggests greater phenotypic and genotypic variance among the genotypes and responsiveness of the attributes for making further improvement by selection and indicating limited scope for improvement. High heritability coupled with high genetic advance observed for harvest-index thus these characters show additive gene action in their expression. In divergence analysis, maximum intra-cluster distance exhibited by cluster 2 followed by cluster 1among the different genotypes. The maximum inter-cluster distance between cluster 2 and 3 followed by cluster 2 and 7 and the minimum inter cluster distance was recorded between cluster 5 and 6 followed by cluster 1 and 3. It indicated that for crop improvement in wheat diversified genotypes may be selected from cluster 2 and cluster 3 to received maximum transgressive recombinants from segregating generations. [ABSTRACT FROM AUTHOR]

The intermittent ozone (O3) exposure of crops to alternating high and low concentrations is common in fields, but its impact on crop production has not been thoroughly investigated. In this study, two widely planted and O3-sensitive crops, winter wheat and soybean, were intermittently exposed to elevated O3 concentrations in open-top chambers. The results showed that the winter wheat and soybean yields significantly decreased with O3 exposure (AOT40, cumulative hourly O3 concentration above 40 ppb) (p < 0.001). The relative yield losses were 0.99% per AOT40 for winter wheat and 1.2% per AOT40 for soybean, respectively. The responses of the crop biomasses to elevated O3 concentrations were lower than that of crop yield. Although the O3-induced crop yield and biomass losses under continuous O3 exposure were greater than those under intermittent O3 exposure, the differences were not statistically significant. Therefore, we can conclude that the effects of elevated O3 concentrations on crops are closely related to the exposure dose but not significantly related to the temporal distribution of elevated O3 concentrations. This study improves our understanding of how crop production responds to intermittent O3 exposure. [ABSTRACT FROM AUTHOR]

One of the crucial research areas in agricultural decision-making processes is crop yield prediction. This study leverages the advantages of hybrid models to address the complex interplay of genetic, environmental, and management factors to achieve more accurate crop yield forecasts. Therefore, this study used the data of wheat growth environment, crop management, and historical yield in experimental fields in Anding District, Dingxi City, Gansu Province from 1984 to 2021 to construct eight machine learning models and ensemble models. Furthermore, Agricultural Production Systems sIMulator (APSIM), machine learning (ML), and APSIM combined with machine learning (APSIM-ML) were employed to predict wheat yields in 2012, 2016, and 2021. The results show that the APSIM-ML weighted ensemble prediction model, optimized to minimize the MSE, performed the best. Compared to the optimized ML and APSIM models, the average improvements in the RMSE, RRMSE, and MBE for the test years were 43.54 kg/ha, 3.55%, and 15.54 kg/ha, and 93.96 kg/ha, 7.55%, and 104.21 kg/ha, respectively. At the same time, we found that the dynamic flow of water and nitrogen between the soil and crops had the greatest impact on wheat yield prediction. This study improved the accuracy of dryland wheat yield prediction in Gansu Province and provides technical support for the intelligent production of dryland wheat in the loess hilly area. [ABSTRACT FROM AUTHOR]

Crop models can provide insights into the impacts of climate and management on crop growth and yield, but most currently are limited by overly simplistic assumptions about phenological development and response to water stress. We assessed winter wheat growth and yield performance of three crop models with lineage to the EPIC crop submodel. SWAT adopted the EPIC approach with few modifications, WEPS added new biomass accumulation, partitioning, and canopy approaches linked to key phenological development stages, and UPGM added to WEPS a detailed phenology component simulating responses to water-deficit stress. The models were evaluated with default parameters and compared to experimental data for winter wheat (Triticum aestivum L.) from two sites and a range of water-stress conditions for yield, aboveground biomass, biomass partitioning, canopy height, harvest index, and leaf area index. All models simulated yield very well (index of agreement [d] ≥ 0.93), but differences in model performance were increasingly evident for biomass (d = 0.91 [WEPS] to 0.86 [SWAT]), final canopy height (d = 0.68 [UPGM] to 0.44 [SWAT]), and harvest index (d = 0.61 [WEPS] to 0.43 [SWAT]). Errors in biomass simulation were most evident in the grain-filling period late in the growing season. Both WEPS and UPGM exhibited improved simulation of biomass and other response variables by including more explicit simulation of phenological response to water stress. The consistent improvement in winter wheat growth and yield simulation achieved with detailed phenology simulation provides an incentive to develop and test detailed phenology simulation components for other crops: currently 11 crops are simulated in UPGM, although the phenological parameters are uncalibrated. Better modeling linkages of water-stressed phenological development with other physiological processes will be critical to inform crop production where water stress and irrigation limitation are concerns. [ABSTRACT FROM AUTHOR]

The aim of this study was to determine the impact of different crop production systems (organic, integrated, and conventional) on the yields of several spring wheat (Triticum aestivum L.) cultivars. A field experiment was carried out at the Agricultural Experimental Station of the Institute of Soil Science and Plant Cultivation in Osiny (Poland) in three consecutive growing seasons (2014, 2015, and 2016). Two factors were included in the experiment: the crop production system (organic, integrated, and conventional) and spring wheat cultivars (Kandela, Izera, Ostka Smolicka, and Waluta). The crop production system significantly differentiated the yield, health, and weed infestation of the spring wheat. Wheat yield in the conventional system (6.12 t·ha−1) was higher than in the organic system (3.68 t·ha−1) by 67%, whereas, in the integrated system (7.61 t·ha−1), it was greater than in the organic system by 109%. The lower yields in the organic system were mainly due to fewer ears per m2 and a smaller 1000-grain weight. In the organic system, we also observed a higher infestation of wheat by foliar fungal pathogens and weeds compared with the conventional and integrated systems. The spring wheat cultivars differed in yield structure and resistance to infestation by fungal pathogens. The Waluta and Izera cultivars performed well in all systems but yielded the best in the integrated and conventional ones. The Kandela cultivar was the most suitable for the organic system, as it achieved the highest yield (4.16 t·ha−1). This was mainly due to its ability to form a compact canopy with relatively high ear density, a large 1000-grain weight, and the highest resistance to fungal pathogens. The results for cultivars' performance in the organic system may be useful for farmers in decreasing yield gaps in relation to integrated and conventional systems. [ABSTRACT FROM AUTHOR]

The proper fallowing of soil maintains or even improves its yield potential. The aim of this research was to compare five methods of soil protection with high production potential on the yield and quality of strategic plants. The tested methods consisted of five variants: bare fallow—BF; natural fallow—NF; fodder galega (Galega orientalis Lam.)—FG; a mixture of fodder galega (Galega orientalis Lam.) with smooth brome (Bromus inermis)—FG+SB; and smooth brome (Bromus inermis)—SB. The soil had been set aside for 9 years, after which time the fallows were terminated and the fields were cropped with winter oilseed rape, winter wheat, and spring wheat in three consecutive years. After the end of fallowing, the content of Nog. and Ctot., pH, and forms of available macro- and microelements in the soil were determined. The influence of each type of fallow on the yield of seeds/grain, straw, total protein, crude fat, and the content of macronutrients in the seeds/grain and straw of the grown crops was determined. Regarding the yields of the crops, the best solution was long-term soil protection via sowing fodder galega or a mixture of fodder galega and smooth brome. A field previously maintained as a fallow with these plants (singly or in combination) could produce over twice-as-high yields of wheat and oilseed rape as those harvested from a field established on bare fallow. The yields of the cereals and oilseed rape obtained in this study prove that food security and environmental protection issues can be reconciled. The methods for protecting farmland temporarily excluded from agricultural production presented in this paper correspond perfectly to the framework of the Green Deal for Europe. Arable land excluded from cultivation can be used to overcome new challenges facing modern agriculture. [ABSTRACT FROM AUTHOR]

Due to the essential role of nano-fertilizers in crop production, studies have yet to be conducted to evaluate nano-molybdenum (Mo) application on winter wheat (Triticum aestivum L.). The present study assessed the efficacy of nano-Mo on the Mo-uptake, plant growth, and winter wheat yield. Wheat was grown in the pot experiment using four experimental groups (deionized water: C, nano potassium molybdate: NMoK, potassium molybdate: MoK, and ammonium molybdate: MoA), each with six replicate samples applied-foliar three times in a 30-day interval. The results revealed that NMoK improved Mo accumulation in grains, stomatal conductance, root dry weight, yield, and the number of spikes per pot of wheat compared with MoK. Additionally, NMoK treatment significantly increased wheat grain yield by 46.29%, 13.94%, and 17.70% compared with C, MoK, and MoA treatments, respectively. These results demonstrated that the nano-Mo application may enhance Mo-inefficient wheat growth, thus, increasing its productivity under acidic soil conditions. The principal component analysis (PCA) elucidates that all variables reside within the positively correlated variable domain. This encompasses parameters related to yield, photosynthetic machinery, and Mo uptake by various plant organs. Through cluster analysis, the nano-Mo group exhibited a more pronounced influence on the variables than the without-Mo and non-nano-Mo groups. Based on our findings, nano-Mo could be a suitable alternative to non-nano molybdenum fertilizers. This recommendation is particularly relevant for enhancing the growth of winter wheat crops cultivated in acidic soil conditions. [ABSTRACT FROM AUTHOR]

Background: One of the current challenges is to secure wheat crop production to meet the increasing global food demand and to face the increase in its purchasing power. Therefore, the current study aimed to exploit a new synthesized nanocomposite to enhance wheat growth under both normal and drought regime. The effectiveness of this nanocomposite in improving the microbiological quality of irrigation water and inhibiting the snail's growth was also assessed. Results: Upon the employed one-step synthesis process, a spherical Fe/Cu/P nanocomposite was obtained with a mean particle size of 4.35 ± 1.524 nm. Cu2+, Fe2+, and P4+ were detected in the dried nanocomposite at 14.533 ± 0.176, 5.200 ± 0.208, and 34.167 ± 0.203 mg/ml concentration, respectively. This nanocomposite was found to exert antibacterial activity against Escherichia coli and Salmonella typhi. It caused good inhibition percent against Fusarium oxysporum (43.5 ± 1.47%) and reduced both its germination rate and germination efficiency. The lethal concentration 50 (LC50) of this nanocomposite against Lanistes carinatus snails was 76 ppm. The treated snails showed disturbance in their feeding habit and reached the prevention state. Significant histological changes were observed in snail digestive tract and male and female gonads. Drought stress on wheat's growth was mitigated in response to 100 and 300 ppm treatments. An increase in all assessed growth parameters was reported, mainly in the case of 100 ppm treatment under both standard and drought regimes. Compared to control plants, this stimulative effect was accompanied by a 2.12-fold rise in mitotic index and a 3.2-fold increase in total chromosomal abnormalities. Conclusion: The finding of the current study could be employed to mitigate the effect of drought stress on wheat growth and to enhance the microbiological quality of irrigation water. This is due to the increased efficacy of the newly synthesized Fe/Cu/P nanocomposite against bacteria, fungi, and snails. This methodology exhibits potential for promoting sustainable wheat growth and water resource conservation. [ABSTRACT FROM AUTHOR]

Plant diseases are a significant threat to global food security since they directly affect the quality of crops, leading to a decline in agricultural productivity. Several researchers have employed crop-specific deep learning models based on convolutional neural networks (CNN) to identify plant diseases with better accuracy and faster implementation. However, the use of crop-specific models is unreasonable considering the resource-constrained devices and digital literacy rate of farmers. This work proposes a single light-weight CNN model for disease identification in three major crops, namely, Corn, Rice, and Wheat. The proposed model uses convolution layers of variable sizes at the same level to accurately detect the diseases with various sizes of the infected area. The experimentation results reveal that the proposed model outperforms several benchmark CNN models, namely, VGG16, VGG19, ResNet50, ResNet152, ResNet50V2, ResNet152V2, MobileNetV2, DenseNet121, DenseNet201, InceptionV3, and Xception, to achieve an accuracy of 84.4% while using just 387,340 parameters. Moreover, the proposed model validates its efficacy as a multi-functional tool by classifying healthy and infected categories of each crop individually, obtaining accuracies of 99.74%, 82.67%, and 97.5% for Corn, Rice, and Wheat, respectively. The better performance values and light-weight nature of the proposed model make it a viable choice for real-time crop disease detection, even in resource-constrained environments. [ABSTRACT FROM AUTHOR]

Context. Computer-based crop simulation models are important tools for agricultural research and management. APSIM (Agricultural Production Systems sIMulator) is commonly used around the world but has not been widely validated in North America. Aims. The objective of this work was to evaluate the reliability of APSIM for simulating wheat production in California, with the aim of providing guidance for future field research aimed at model calibration and validation. Methods. Environmental and management data from state-wide wheat variety trials of common wheat (Triticum aestivum L.) were used to parameterise the APSIM-Wheat module (ver. 7.10 r4220). Simulated yield and protein data were compared with observed field trial results to test the reliability of APSIM simulations. Key results. The most reliable simulation of grain yield had a root-mean-square error of 1040 kg/ha and normalised root-mean-square error of 16% relative to actual field data. Preliminary calibration of the model for Californian wheat varieties did not improve simulation accuracy or precision. Conclusions. The accuracy or precision of the simulations was comparable to that of other tests of the APSIM-Wheat module in environments where it has not been previously calibrated but was considered too low to be reliable. The lack of reliability was due to the poor representation of local Californian wheat genotypes by existing APSIM cultivars, as well as possible lack of precision and accuracy of field data. Implications. APSIM could be a valuable tool for wheat research and management in California; however, further research is needed to generate suitable field data for model calibration and validation. [ABSTRACT FROM AUTHOR]

The effectiveness of mineral fertilization on wheat productivity was determined in a field experiment on Alluvial-meadow soil (Fluvisol, FAO 2015) at the experimental field of Tsalapitsa village, Plovdiv region, during 2019-2020. Four increasing rates of nitrogen fertilization along with a constant background of phosphorus fertilization were tested in the following variants: N40P100; N80P100; N120P100; N160P100, and N0P0 (control) - without any fertilization. The influence of these variants on yield and the content of basic macro and microelements in wheat's dry biomass were assessed. Plant samples were collected at the full maturity phase of wheat, with each variant sampled in triplicate, to determine the concentrations of N, P, K, Ca, Mg, Cu, Zn, Mn, and Fe. Correlation analysis and analysis of variance (ANOVA) were employed to identify dependencies between observed variables. Significant differences between the variants for N% content in grain, chaff and straw of wheat were established. The highest nitrogen values were observed in the grain of the N160P100 and N120P100 variants, at 2.10% and 2.02%, respectively. The applied fertilization had a significant positive effect on the accumulation of potassium, calcium, copper, manganese and iron in wheat biomass. This finding was supported by the correlation coefficients between fertilizer rates and N (R = 0.948), Ca (R = 0.854), Cu (R = 0.681), Mn (R = 0.735), and Fe (R = 0.769) in the wheat grain. Significant yield differences were observed among the variants, with the highest yield recorded for N120P100 (7123.0 kg/ha), more than tripling that of the control variant. The uptake of nitrogen, phosphorus and potassium by the total biomass of wheat increased depending on the fertilization rates and it was the highest in the N120P100 variant. [ABSTRACT FROM AUTHOR]

In crop production, one important limiting factor is the availability of nitrogen (N) and N derivatives, as they are of much significance in plant metabolism and growth. Various nitrate transporter genes including GS2a, TaNRT2.1, TaNRT2.2, TaNRT1, ASN1, cysteine protease, GST1, and TaAMT2.1 mediate the uptake, transport, and remobilization of N in the plants. However, their role is not quite understood with respect to the importance of grain-filling stages and the plant's overall yield. Herein, the expression levels of a number of genes and enzymes involved in N uptake and metabolism were measured over the course of anthesis and under N-treatet and N-deficit conditions in two genotypes of wheat, namely Morvarid and Gonbad. The samples were taken 10, 15, and 20 days after anthesis (DAA), which is a critical stage in grain filling, and the relation between gene expression, enzyme activity, and DAA was demonstrated. It was observed that N-related gene expression significantly increases under N-deficit conditions and over the course of anthesis, suggesting the significance of the N-related genes and enzymes in maintaining the metabolism and growth of the plants under Ndeficit conditions. The results of this study also showed that the amount of nitrogen in the plant can increase the amount of seed protein, leaf chlorophyll content, the size and volume of cell protoplasm, and also affect the leaf surface and photosynthetic activity, so it is important to use modified cultivars with high expression of transgenic nitrogen genes. [ABSTRACT FROM AUTHOR]

As an important macro element for all living cells, phosphorus is essential in agricultural production systems and is required in large quantities by elite varieties of crops to maintain yields. Approximately 70% of the worldwide cultivated land suffers from phosphorous deficiency, and it has recently been estimated that the worldwide phosphorous resources will be shattered by the end of this century, thereby increasing the need to develop phosphorus-efficient crops. A greater understanding of how plants can maintain yield with lower phosphorous availability is highly desirable to both breeders and farmers. For this research, we focused on the phosphorusstarvation tolerance 1 (PSTOL1) gene, which is known to be involved in enhancing early root growth, thereby enabling plants to acquire more phosphorus and other nutrients and enhancing grain yield in phosphorus-deficient soil. As there is no reported structure and function of the PSTOL1 gene, this project involves a distinct set of opportunities and challenges and requires different approaches to model the interaction between PSTOL1 and the gene phosphorous uptake 1 (PUP1). This article covers the modeling, docking, and simulation of PSTOL1 to check the protein stability and its behavior over time. The physiochemical properties were ascertained, a phylogenetic tree was constructed to find the evolutionary relationship, and the conserved domains were analyzed for functional annotation. This study reports that the advancement of the PSTOL1-mediated phosphorous uptake 1 (PUP1) signaling cascade using structural bioinformatics is a potent biological mechanism against phosphorous starvation in wheat. [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]

To investigate the responses of crop production and soil profile nutrient status to biochar (BC) application, we conducted a soil column experiment considering two BC addition rates (0.5 and 1.5 wt% of the weight of 0–20 cm topsoil) combined with two nitrogen (N) input levels (low N: 144 kg ha−1, LN; high N: 240 kg ha−1, HN). The results showed that BC application increased the soil pH. The soil pH of the 0–10 cm profile under LN and the 20–40 cm profile under HN were both significantly increased by 0.1–0.2 units after BC addition. Under LN, BC addition significantly increased NH4+-N (17.8–46.9%), total N (15.4–38.4%), and soil organic carbon (19.9–24.0%) in the 0–10 cm profile, but decreased NH4+-N in the 20–30 cm soil profile and NO3−-N in the 10–30 cm profile by 13.8–28.5% and 13.0–34.9%, respectively. BC had an increasing effect on the available phosphorus, the contents of which in the 10–20 and 30–40 cm soil profiles under LN and 20–30 cm profile under HN were significantly elevated by 14.1%, 24.0%, and 23.27%, respectively. However, BC exerted no effect on the available potassium in the soil profile. BC had a strong improving effect (15.3%) on the wheat yield, especially the N144 + BC0.5% treatment, which could be compared to the HN treatment, but there was no yield-increasing effect when high N fertilizer was supplied. In summary, BC improved the fertility of agriculture soil (0–20 cm) with wheat. In particular, low N inputs together with an appropriate rate of BC (0.5 wt%) could not only achieve the low inputs but also the high outputs in wheat production. In future study, we will compare the effects of multiple doses of N and BC on soil fertility and crop production. [ABSTRACT FROM AUTHOR]

Plant growth regulators (PGRs) play an important role in increasing crop yield, and quality, and enhancing crop stress resistance in agricultural production, especially for important crops. PGRs can affect the transport and distribution of assimilates by changing the content and distribution of endogenous hormones in plants. Numerous empirical research results have proven that PGRs have an important impact on the growth, development, and yield composition of wheat. Taking wheat plants as an example, this study reviews the application of PGRs in wheat production and explores their impact on wheat growth and yield. Furthermore, residues and microbial degradation of PGRs are summarized in detail. Finally, future research directions on PGR application in wheat production are proposed. This summary is of great significance for understanding the role of PGRs in wheat production. [ABSTRACT FROM AUTHOR]

Introduction: In the face of climate changes and limited water availability for irrigated crop production, enhanced drought tolerance and adaptation is vital to improve wheat productivity. The objective of this study was to determine the responses of newly bred and advanced mutant lines of wheat based on agronomic traits and biomass allocation under drought-stressed and nonstressed environments for production and breeding. Methods: Fifty-three mutant lines, including the parental check and six check varieties, were evaluated under non-stressed (NS) and drought stressed (DS) conditions in the field and controlled environments using a 20 x 3 alpha lattice design with two replicates. The following agronomic data were collected: days to 50% heading (DTH), days to maturity (DTM), plant height (PH), number of productive tillers (PTN), shoot biomass (SB), root biomass (RB), total biomass (TB), root: shoot ratio (RSR), spike length (SL), thousand seeds weight (TSW) and grain yield (GY). Data were analyzed and summarized using various statistical procedures and drought tolerance indices were computed based on grain yield under NS and DS conditions. Results: Significant (P < 0.05) differences were recorded among the mutant lines for most assessed traits under NS and DS conditions. Grain yield positively and significantly (p < 0.001) correlated with PTN (r = 0.85), RB (r = 0.75), SB (r = 0.80), SL (r =0.73), TB (r = 0.65), and TSW (r = 0.67) under DS condition. Principal component analysis revealed three components contributing to 78.55% and 77.21% of the total variability for the assessed agronomic traits under DS and NS conditions, respectively. The following traits: GY, RB, SB, and PTN explained most of the variation with high loading scores under DS condition. Geometric mean productivity (GMP), mean productivity (MP), harmonic mean (HM), and stress tolerance index (STI) were identified as the best drought tolerance indices for the identification of tolerant lines with positive correlations with GY under NS and DS conditions. Discussion: Among the advanced lines tested, LMA16, LMA37, LMA47, LMA2, and LMA42 were selected as the superior lines with high performance and drought tolerance. The selected lines are recommended for multi-environment trails and release for production in water-limited environments in South Africa. [ABSTRACT FROM AUTHOR]

This research aimed at evaluation of a given land resource suitable for selected rain fed crops production (malt barley, wheat and teff) in Ambesh watershed. It also quantified suitable land and classified into the land mapping units (LMUs), and presents a land suitability map. Land suitability assessment (LSA) made using climatic condition, topography, soil physical and chemical properties as a major factor integrated with a multi criteria decision making (MCDM) analysis in Ambesh watershed. Fourteen composite soil samples were taken by categorizing the watershed into different land mapping units (LMUs) and analyzed in a soil laboratory. Climatic data, rainfall was obtained from two meteorological stations nearby to the study area. Temperature data derived from Landsat 8 satellite thermal bands data. Data obtained from the soil laboratory and others were finally analyzed using ArcGIS environment and priority estimation tool (PriEsT) software's. Weighted Sum Overlay was implemented to investigate the final LSA map of the watershed. Results revealed that LMUs, VRe–LPq and LPK.Pq–FLc LMUs has higher overall suitability for all the selected rain fed crops. However, LMUs (VRe–NTu and NTu–VRe) has lower overall suitability values particularly for S1 suitability class (0.05% and 10.6%, respectively). The least suitable LMU is VRe–NTu with 0.05% S1 suitability class and above 99% of the land laid under the suitability classes of moderately suitable, marginally suitable and not suitable for the selected land utilization types. Moreover, about 219.06 ha (17.76%), 217.6 ha (17.64%), 168.9 ha (13.7%), of land are highly suitable for malt barley, teff and wheat crop production, respectively. In conclusion, during MCDM, classifying the land into closer homogeneities (LMU) an important application of LSA integrated with remote sensing and GIS for a better decision making. Meanwhile, majority (above two third's) of the land in the watershed is under moderate and marginally suitable, it needs intensive land management activities to increase the land qualities and obtain high yields. LSA recommended before land utilization decision has to be made. It is also important to classifying the land into LMUs to make it more homogeneous for sample taking and reducing the prestigious soil laboratory analysis costs. [ABSTRACT FROM AUTHOR]

Context. Crop production is one of the agricultural sectors most vulnerable to climate change. In order to minimise risks, innovative technologies and management strategies are continually being developed. Early sowing is a strategy used in wheat production; however, with irregular rainfall patterns, false breaks can occur. Aims. We sought to determine the optimal volume of autumn-break rainfall for the start of season, and whether formation of a larger rhizosheath (i.e. the thick layer of soil adhering to roots) can buffer wheat seedlings fromfalse-break conditions, thereby keeping plants alive until the next rainfall. Methods. In glasshouse experiments, six varieties of common wheat (Triticum aestivumL.), two with contrasting rhizosheath-forming ability and the other four untested, were grown on two soil types (Kandosol and Vertosol) under simulated autumn-break rainfall and false-break durations. Rhizosheath size and plant establishment traits were measured. Key results. The ability to form large rhizosheaths explained ~80% of the variability in crop establishment under various scenarios of false-break conditions. Comparative growth performance of the cultivars forming the largest (cv. Flanker) and smallest (cv. Westonia) rhizosheaths showed that they were largely similar for the first 28 days of drought but differed significantly thereafter. Flanker was progressively better able to establish as false-break duration increased and showed significantly greater tiller and leaf production than Westonia. Conclusions. We demonstrate that genotype selection for formation of large rhizosheaths can help to reduce plant seedling death under false-break conditions. Implications. Although the amount of starting rainfall is critical, cultivars differ significantly with regard to how far they can develop without follow-up rain. Future research is suggested for a field-scale study of the potential for selection for larger rhizosheaths to improve wheat crop establishment under harsh conditions. [ABSTRACT FROM AUTHOR]

Maintaining or even increasing crop yields while reducing nitrous oxide (N2O) emissions is necessary to reconcile food security and climate change, while the metric of yield‐scaled N2O emission (i.e., N2O emissions per unit of crop yield) is at present poorly understood. Here we conducted a global meta‐analysis with more than 6000 observations to explore the variation patterns and controlling factors of yield‐scaled N2O emissions for maize, wheat and rice and associated potential mitigation options. Our results showed that the average yield‐scaled N2O emissions across all available data followed the order wheat (322 g N Mg−1, with the 95% confidence interval [CI]: 301–346) > maize (211 g N Mg−1, CI: 198–225) > rice (153 g N Mg−1, CI: 144–163). Yield‐scaled N2O emissions for individual crops were generally higher in tropical or subtropical zones than in temperate zones, and also showed a trend towards lower intensities from low to high latitudes. This global variation was better explained by climatic and edaphic factors than by N fertilizer management, while their combined effect predicted more than 70% of the variance. Furthermore, our analysis showed a significant decrease in yield‐scaled N2O emissions with increasing N use efficiency or in N2O emissions for production systems with cereal yields >10 Mg ha−1 (maize), 6.6 Mg ha−1 (wheat) or 6.8 Mg ha−1 (rice), respectively. This highlights that N use efficiency indicators can be used as valuable proxies for reconciling trade‐offs between crop production and N2O mitigation. For all three major staple crops, reducing N fertilization by up to 30%, optimizing the timing and placement of fertilizer application or using enhanced‐efficiency N fertilizers significantly reduced yield‐scaled N2O emissions at similar or even higher cereal yields. Our data‐driven assessment provides some key guidance for developing effective and targeted mitigation and adaptation strategies for the sustainable intensification of cereal production. [ABSTRACT FROM AUTHOR]

Nitrogen (N), an important element for crop growth, has a great impact on dry matter weight and yield. Currently, improving N fertilizer use rate is an urgent problem to be solved in agricultural production in the world. In this field experiment, a self-developed water-soluble polymer material (PPM) with water retention and slow-release characteristics was combined with different doses of N fertilizer (N300 (100% N), PN300 (PPM + 100% N), PN240 (PPM + 80% N), PN180 (PPM + 60% N), CK (no N and PPM)) to analyze the impacts on N uptake and use efficiency of wheat plants. The results showed that the combined application of PPM and N fertilizer significantly improved yield, plant height, biomass, and N uptake and use efficiency of drip irrigated wheat, and the PN240 group had the highest N use rate. In addition, the PN300 group had the highest yield. N use efficiency in the PN240 group was 40.23% higher than that in the N300 group. Therefore, the combined application of PPM and N fertilizer, especially PN240, can reduce the N fertilizer application rate by increasing N use efficiency. This study provides technical reference for improving the N use efficiency of drip-irrigated wheat in arid areas. [ABSTRACT FROM AUTHOR]

It is of great significance to study the plant morphological structure for improving crop yield and achieving efficient use of resources. Three dimensional (3D) information can more accurately describe the morphological and structural characteristics of crop plants. Automatic acquisition of 3D information is one of the key steps in plant morphological structure research. Taking wheat as the research object, we propose a point cloud data-driven 3D reconstruction method that achieves 3D structure reconstruction and plant morphology parameterization at the phytomer scale. Specifically, we use the MVS-Pheno platform to reconstruct the point cloud of wheat plants and segment organs through the deep learning algorithm. On this basis, we automatically reconstructed the 3D structure of leaves and tillers and extracted the morphological parameters of wheat. The results show that the semantic segmentation accuracy of organs is 95.2%, and the instance segmentation accuracy AP50 is 0.665. The R 2 values for extracted leaf length, leaf width, leaf attachment height, stem leaf angle, tiller length, and spike length were 0.97, 0.80, 1.00, 0.95, 0.99, and 0.95, respectively. This method can significantly improve the accuracy and efficiency of 3D morphological analysis of wheat plants, providing strong technical support for research in fields such as agricultural production optimization and genetic breeding. [ABSTRACT FROM AUTHOR]

BACKGROUND: The present work estimates the area and corresponding wheat crop production in the study area, which comprises the Etah region of Uttar Pradesh, India. For this purpose, multispectral images of multiple sensors, namely Sentinel‐2, Landsat‐8 and Landsat‐9 during the preharvest period, i.e. March for the years 2021 and 2022, were used. A multispectral information fusion approach was proposed, involving image classification as well as vegetation index‐based information extraction. For imposing information fusion, appropriate image bands were identified with the help of separability analysis followed by land cover classification for wheat crop class extraction. Support vector machine (SVM), artificial neural network (ANN) and maximum likelihood (ML) were used for classification, whereas normalized difference vegetation index (NDVI) and fractional vegetation cover (FVC) were used for index‐based crop area extraction. RESULTS: A maximum accuracy of 98.34% was achieved for Sentinel‐2 data using ANN, whereas a minimum accuracy of 80.21% was achieved for Landsat‐9 using the ML classifier. The estimated area for Sentinel‐2 data for the year 2021 was 260 540 ha using ANN and 203 240 ha using ML, which is close to the reference data, i.e. 238 600 ha. SVM also showed good performance and calculated least error in estimated crop area for the year 2022 on Sentinel‐2 data. It calculated 8 408 490 tons of wheat for the same year. CONCLUSION: The proposed method utilizes a single image per year for extraction of information supported by the ground truth data, which makes it a novel approach to information extraction for crop production monitoring. © 2023 Society of Chemical Industry. [ABSTRACT FROM AUTHOR]

Now a days automation and monitoring of crop irrigation is required for quality production of the crop. In this paper wheat, tomato and rice are considered for the study. A PLC based system is developed for monitoring and automation of these crops at various stages of growth. For the simulation of the system TwinCatTM software is used. For wheat crop temperature is monitored at germination, growth, and grain filling stages. Also, for wheat irrigation schedule is simulated. For tomato temperature is monitored at various growth stages. For rice crop temperature, soil moisture and humidity content are considered. The monitoring system helps the farmers to maintain the desired conditions for the respective crop. [ABSTRACT FROM AUTHOR]

The Upper Cheliff plain (North of Algeria) experienced substantial impacts from climate variability, particularly notable as the majority of cereal cultivation areas rely on rainfed practices, devoid of irrigation. Certainly, the insufficient rainfall during the critical phases of the crop's life cycle in 2020-2021 resulted in cereal production in this region dropping to 51500 kg, which is less than half of the yield from the 2019-2020 agricultural season (124300 kg). The study aimed to assess the influence of climate change on cereal crop yields in the Upper Cheliff Plain by analyzing trends in rainfall, temperature, and humidity time series over 30 years, from 1981 to 2020. This was established with mathematical formulas and statistical assessments of cereal production. The study revealed three distinct periods: 1981-1987, 1988-2004, and 2005-2020. Annual rainfall decreased by 11% between 1988-2004, while temperatures increased by 0.1°C in recent decades, leading in lower humidity. In 2017/2018, with a rainfall of 634 mm, the average yields of bread wheat (Triticum aestivum L), durum wheat (Triticum durum L) and barley (Hordeum vulgare L) were respectively 2800, 3100 and 2100 kg ha-1. In 1996/1997, when rainfall was less than 246 mm, yields of the same species did not exceed 600, 700, and 700 kg ha-1. It can be explained by the vulnerability of cereals to water stress. The results illustrate the strong link between selected climatic parameters and agricultural production in the semi-arid climate such as the Upper Cheliff Plain. [ABSTRACT FROM AUTHOR]

The foliar application of zinc (Zn) has been regarded as a practical and economical way to reduce grain cadmium (Cd) accumulation and enhance grain quality in crops. Herein, a two-year field experiment was carried out to examine the efficacy of different application rates of the foliar Zn fertilizer in Cd reduction and microelement biofortification in wheat (Triticum aestivum L.) grains. The results show that the T4 and T5 treatments, 500 and 250-fold dilution of the foliar Zn fertilizer, respectively, increased the grain yield to varying degrees in the two years. When compared with controls and based on the average of the two years' results, spraying with the foliar Zn fertilizer remarkably decreased grain Cd concentrations (44.5%), Cd translocation from stem to grain (TFStem/Grain) (4.92%), the H R I values of Cd (45.5%), PA/Ca (27.8%), PA/Fe (21.4%) and PA/Mn (5.81%) under the T2 treatment (1000-fold dilution). Furthermore, the T2 treatment significantly increased the Zn (37.8%), Ca (48.9%), Fe (37.6%), Mn (14.8%) and total protein (7.92%) contents and the estimated Zn bioavailability (28.9%) in wheat grains after two years. All these findings suggest that the foliar Zn fertilizer holds considerable promise as a safe crop production technique and a means of mitigating "hidden hunger" in developing countries. [ABSTRACT FROM AUTHOR]

Climate-induced extreme events with fluctuations in climatic indicators like temperature and precipitation highly influence crop productivity. This study deals with quantitative analysis of climatic variability and crop production (1990–2018) using panel data regression analysis. The focus is on variability of three crops, i.e., paddy, maize, and wheat in the Rangit river basin of Sikkim Himalaya, India. Meterological data were acquired from the Indian Meteorological Department, agricultural data from the state agricultural department and a field survey were also conducted with the farmers, using a structured questionnaire, focused group discussion, and key informant observations. The acquired data was analyzed with the help of correlation and multiple linear regression analysis to analyze the relationship between climatic variability and crop production. The result of the study shows that all three crops are dependent on rainfall; however, paddy was the most sensitive to climatic variability. It was found that the overall grain production had an inverse relation to temperature, but it had a positive correlation with rainfall. It was observed that there was a continuous decline in the overall production of paddy and wheat. During deficiency years, it was found that when − 11.33% rainfall was deficient, paddy yield declined by − 1.52%. Further, a deviation of − 13.48% led to a decline of − 54.78% in wheat. The study advocates that timely policy interventions and strategies shall reduce climatic shocks and improve productivity. This would strengthen the livelihood security of the local communities, overcome the challenges of food security, and ensure long-term sustainability of Rangit River basin. [ABSTRACT FROM AUTHOR]

Wheat is one of the primary crop productions for half of the global production. It is the most exported cereal, which reached up to 40% according to the records of the Food and Agriculture Organization of the United Nations (FAO) in 2020. The relationship between the crop parameters and remote sensing tools has become essential for the temporal monitoring and estimations of crop growth. In this study, we investigate the relationship between crop height and Synthetic Aperture Radar (SAR) backscatter. Plant height was collected twice, in the early (13 April 2023) and late stages (21 June 2023) of wheat, for a total of 70 samples. Sentinel-1 SAR data was also attempted to be synchronized with ground measurements. For this purpose, 8 images were obtained, 4 in both ascending (8 and 15 April, 16 and 26 June) and descending (9 and 14 April, 20 and 25 June) directions. The basic steps of image pre-processing, calibration, filtering, and topography correction, were applied to each image. By evaluating the correlation coefficients between plant height and images, data with low correlations were excluded and the first three data, dated 8 April and 19 June, were used for plant height estimation. For prediction purposes, Linear Regression (LR) and Random Forest (RF) methods were evaluated with three different training data sets. The highest correlation and minimum error value were achieved by VH polarization with random forest (r = 0.868, RMSE = 5.377 cm) in the early stage and LR (r = 0.616, RMSE = 14.451 cm) in the late stage. In general, higher training (80%) and lower test data (20%) produced better results. [ABSTRACT FROM AUTHOR]

Exploring the intensive planting scheme to improve the agricultural productivity of coastal salinized farmland, the field positioning trial conducted in Kenli district, Shandong province was carried out since 2015, and 4 treatments were set up by considering fertilizer application amount, fertilizer application period, planting density, soil amendment and other measures including farmer's practice (FP), improved soil management (ISM), improved crops management (ICM), integrated soil crop management (ISCM). Track the population dynamic changes in the key growth period of wheat, analyzed the dry matter accumulation and nitrogen, phosphorus and potassium nutrient absorption of wheat and maize during harvest, investigated the changes of wheat and maize yield and yield components, and compared the net income of crop production, soil sodium removal rate and sodium adsorption ratio in the 0--20 cm soil layer after harvest. The results showed that compared with FP treatment, ISM significantly increased the number of ears during wheat and maize harvest, resulting in a 25.2% and 10.0% increase in yield, and a 7.8% increase in net income, respectively. In addition, the soil sodium removal rate of ISM treatment reached 78.6%. The ICM treatment significantly increased the dry matter accumulation of wheat and maize, with a yield increase of 17.8% and 10.7%, respectively, compared to the FP treatment, and the net income increase of 19.3% . The ISCM treatment obtained the highest wheat yield of 11.96 and 10.83 t · hm-2, respectively, the net income increased by 20.8% compared to the FP treatment, and the soil sodium removal rate reached 82.9%. The ISM treatment could significantly reduce the sodium ion content of salinized soil, improve the nutrient absorption capacity of wheat and maize, and increase yield. Although the yield increase effect of ICM treatment was lower than that of ISM treatment, lower input cost could obtain higher net benefit. On the whole, the ISCM treatment could simultaneously achieve soil quality improvement, crop yield increase and economic benefits, which was the optimal management practice scheme under the conditions of this study. This research result could provide technical and theoretical support and demonstration models for improving the production capacity of medium to low yield fields in the region. [ABSTRACT FROM AUTHOR]

In a rice–wheat rotation system, biochar (BC) applied in different crop seasons undergoes contrast property changes in the soil. However, it is unclear how aged BC affects the production and quality of wheat and the nutrent status in a soil profile. In the present soil column experiment, the effects of no nitrogen (N) fertilizer and BC addition (control), N fertilizer (N420) and BC (5 t ha−1) applied at rice [N420 + BC(R)], or wheat [N420 + BC(W)] seasons at a same rate of N fertilizer (420 kg ha−1 yr−1) on yield and quality of wheat as well as the nutrient contents of soil profiles (0–5, 5–10, 10–20, 20–30, 30–40, and 40–50 cm) were observed. The results showed that N420 + BC(W) significantly reduced NH4+-N content in 5–10 and 10–20 cm soils by 62.1% and 36.2%, respectively, compared with N420. In addition, N420 + BC(W) significantly reduced NO3−-N contents by 17.8% and 40.4% in 0–5 and 20–30 cm profiles, respectively, but N420 + BC(R) slightly increased them. The BC applied in wheat season significantly increased the 0–5 and 40–50 cm soil total N contents (24.0% and 48.1%), and enhanced the 30–40 and 40–50 cm soil-available phosphorus contents (48.2 and 35.75%) as well as improved the 10–20 and 20–30 cm soil-available potassium content (38.1% and 57.5%). Overall, our results suggest that N420 + BC(W) had stronger improving effects on soil fertility than N420 + BC(R). Compared to N420, there was a significant 5.9% increase in wheat grain yield, but no change in total amino acids in wheat kernels in N420 + BC(W). Considering the responses of soil profile nutrient contents as well as wheat yield and quality to BC application in different crop seasons, it is more appropriate to apply BC in wheat season. Our results could provide a scientific basis for the ideal time to amend BC into the rice–wheat rotation system, in order to achieve more benefits of BC on crop production and soil fertility. [ABSTRACT FROM AUTHOR]

Osmotic stress is a significant concern in agricultural crop production as it can harm crop growth, development, and productivity. Agriculture crops are particularly vulnerable to osmotic stress due to their reliance on water availability for various physiological processes. Organic amendments like activated carbon biochar and growth hormone gibberellic acid (GA3) can play a vital role. However, the time needed is to modify the established amendment to achieve better results. That's why the current study used potassium-enriched biochar (KBC = 0.75%) with and without GA3 (15 mg/L) as amendments under no osmotic stress and osmotic stress in wheat. Results showed that GA3 + KBC caused significant enhancement in germination (9.44%), shoot length (29.30%), root length (21.85%), shoot fresh weight (13.56%), shoot dry weight (68.38), root fresh weight (32.68%) and root dry weight (28.79%) of wheat over control under osmotic stress (OS). A significant enhancement in chlorophyll a, chlorophyll b and total chlorophyll, while the decline in electrolyte leakage of wheat, also validated the effectiveness of GA3 + KBC over control in OS. In conclusion, GA3 + KBC is the most effective among all applied treatments for improving wheat growth attributes under no osmotic and osmotic stress. Further research is needed at the field level, focusing on various cereal crops, to establish GA3 + KBC as the optimal treatment for effectively mitigating the impacts of osmotic stress. [ABSTRACT FROM AUTHOR]