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In the face of evolving agricultural practices and climate change, tools towards an integrated biovigilance platform to combat crop diseases, spore sampling, DNA diagnostics and predictive trajectory modelling were optimized. These tools revealed microbial dynamics and were validated by monitoring cereal rust fungal pathogens affecting wheat, oats, barley and rye across four growing seasons (2015–2018) in British Columbia and during the 2018 season in southern Alberta. ITS2 metabarcoding revealed disparity in aeromycobiota diversity and compositional structure across the Canadian Rocky Mountains, suggesting a barrier effect on air flow and pathogen dispersal. A novel bioinformatics classifier and curated cereal rust fungal ITS2 database, corroborated by real‐time PCR, enhanced the precision of cereal rust fungal species identification. Random Forest modelling identified crop and land‐use diversification as well as atmospheric pressure and moisture as key factors in rust distribution. As a valuable addition to explain observed differences and patterns in rust fungus distribution, trajectory HYSPLIT modelling tracked rust fungal urediniospores' northeastward dispersal from the Pacific Northwest towards southern British Columbia and Alberta, indicating multiple potential origins. Our Canadian case study exemplifies the power of an advanced biovigilance toolbox towards developing an early‐warning system for farmers to detect and mitigate impending disease outbreaks. [ABSTRACT FROM AUTHOR]

The carbon cycle of saline–alkali ecosystems will be affected to some extent in the context of future global warming. Therefore, we investigated the net ecosystem exchange (NEE) of three typical crops (wheat, maize and soybean) in the saline–alkaline land of the Yellow River Delta. To further investigate CO2 fluxes, NEE was decomposed into gross primary productivity (GPP) and ecosystem respiration (Re). In terms of seasonal variation, wheat and soybean were carbon sources in the early and late growth periods, and carbon sinks in the rest of the period, whereas maize was a carbon sink in the majority of the period, and maize had good carbon sink potential. The cumulative NEE during the growth periods for wheat, maize, and soybean were 414.86, 258.24 and 228.92 g cm−2, respectively, and the daily variation showed that the peak NEE values for the three crops preceded the peak values of both GPP and ecosystem respiration, occurring approximately at 12:00 a.m. In the correlation analysis, NEE and GPP of the three crops were well correlated with photosynthetic photon flux density and net radiation, whereas Re was significantly correlated with air temperature. Through a comparative analysis of CO2 fluxes within various agricultural ecosystems, our findings indicated that wheat demonstrated moderate carbon sequestration capabilities, whereas maize and soybean exhibited strong carbon sink characteristics. Notably, saline–alkali crops exhibited lower Re, whereas GPP levels remained at a moderate range. Therefore, under the global warming trend, the respiration of saline crops and soils will be affected and may change the original carbon sink into a carbon source. Hence, implementing suitable measures targeting saline–alkali areas, such as the establishment of an effective crop rotation system and the enhance saline–alkali land conditions, can reduce emissions of greenhouse gases, thus reducing the pressure of global warming and maintaining a stable carbon cycle in saline–alkali land. [ABSTRACT FROM AUTHOR]

Food and feed production worldwide heavily relies on wheat (Triticum aestivum). However, current agricultural practices face numerous challenges including a shortage of land for cultivation, a desire to reduce the use of chemical pesticides and fertilizers, and the development of resistance towards employed pesticides and virulence towards host resistance in the most widely grown varieties. In this paper, we demonstrate based on the literature that cultivating wheat variety mixtures generally leads to increased yield and yield stability across years and environments, reduced severity of multiple diseases, and a decreased risk of lodging before harvest compared to the cultivation of pure stands. Moreover, mixtures may delay fungicide resistance development and increase genetic diversity, ultimately prolonging the durability of resistance genes. Furthermore, growing mixtures may lower the risk of crop failure due to more extreme weather events and lead to better utilization of water and nutrients. We discuss a Danish case study advocating the cropping of wheat varieties in mixtures as an example of how variety mixtures can be utilized in integrated pest management strategies. The study shows that if all involved stakeholder groups promote the adoption of variety mixtures, a major uptake by farmers can be reached, potentially reducing the dependency on pesticides in current cropping schemes. [ABSTRACT FROM AUTHOR]

Wheat sharp eyespot is a soil-borne fungal disease commonly found in wheat areas in China, which can occur throughout the entire reproductive period of wheat and has a great impact on the yield and quality of wheat in China. By constructing a domain ontology for wheat sharp eyespot control and modeling the domain knowledge, we aim to integrate and share the knowledge in the field of wheat sharp eyespot control, which can provide important support and guidance for agricultural decision-making and disease control. In this study, the literature in the field of wheat sharp eyespot control was used as a data source, the KeyBERT keyword extraction algorithm was used to mine the core concepts of the ontology, and the hierarchical relationships among the ontology concepts were extracted through clustering. Based on the constructed ontology of wheat sharp eyespot control, the schema of knowledge extraction was formed, and the knowledge extraction model was trained using the ERNIE 3.0 knowledge enhancement pretraining model. This study proposes a model and algorithm to realize knowledge extraction based on domain ontology, describes the construction method and process framework of wheat sharp eyespot control domain ontology, and details the training and reasoning effect of the knowledge extraction model. The knowledge extraction model constructed in this study for wheat sharp eyespot control contains a more complete conceptual system of wheat sharp eyespot. The F1 value of the model reaches 91.26%, which is a 17.86% improvement compared with the baseline model, and it can satisfy the knowledge extraction needs in the field of wheat sharp eyespot control. This study can provide a reference for domain knowledge extraction and provide strong support for knowledge discovery and downstream applications such as intelligent Q&A and intelligent recommendation in the field of wheat sharp eyespot control. [ABSTRACT FROM AUTHOR]

Wheat (Triticum aestivum L.)–cotton (Gossypium hirsutum L.) relay strip intercropping involves cultivating wheat sown in autumn and cotton sown in spring, allowing the two crops to grow together for ∼2 months. Despite its prevalence in cotton‐growing regions globally, this agricultural practice remains untapped in Turkey, where the emphasis on resource use efficiency and the competition between staple and cash crops are paramount. To address this, we conducted a study comparing three cropping systems under both well‐watered and limited water conditions: sole wheat with a row spacing of 13.5 cm, sole cotton with a row spacing of 70 cm, and an intercropping system consisting of four rows of wheat and two rows of cotton, with row spacings of 13.5 cm and 40.5 cm, respectively. In intercropped wheat and cotton, the relative wheat yield was 0.68, while the relative cotton yield was 0.73, resulting in a combined relative yield of 1.41 when compared to monoculture. The land equivalent ratio (1.44) and area time equivalent ratio (1.08) consistently exceeded 1.0, particularly under limited watering conditions and concurrent heat stress observed in the second year of the experiment. Our findings indicate that wheat–cotton relay intercropping holds significant potential as a highly effective approach to enhance the production of both cotton and wheat in Turkey, particularly in stressful conditions such as limited water availability. Core Ideas: The productivity of wheat/cotton intercropping under both well‐watered and drought conditions in Turkey was studied.On average, intercropped wheat and cotton exhibited relative yields of 64% and 75%, respectively.The land equivalent ratio and water equivalent ratio were well above 1, with averages of 1.5 and 1.4, respectively.The advantage of intercropping was slightly increased under conditions of water shortage.Intercropped cotton demonstrated greater resilience to heat stress. [ABSTRACT FROM AUTHOR]

Existing agricultural nitrogen datasets in China are mostly developed using coarse national or provincial statistics. A crop‐specific nitrogen rate dataset based on the finest‐scale agricultural nitrogen statistics at the county level remains lacking. Here, we constructed a new dataset (CN‐N), which provides annual nitrogen rates for rice, wheat and maize in China at a 1‐km spatial resolution from 2004 to 2016. This dataset was developed by harmonizing county‐level and provincial agricultural nitrogen statistics with gridded crop distribution maps, resulting in 13 years of nitrogen rate maps for each crop covering 2004–2016. Validation against farmers' surveys by crop indicates CN‐N reliably quantifies average nitrogen rates and trends for each crop over 2004–2016, demonstrating improved spatial heterogeneity compared to previous datasets rasterized using only provincial statistics. Our study provides a crop‐specific, temporally consistent, gridded nitrogen rate dataset based on the finest‐scale county‐level agricultural nitrogen statistics. This can support future process‐based modelling for sustainable agricultural nitrogen management strategies. [ABSTRACT FROM AUTHOR]

This article discusses the role of the transcription factor TaMYB72 in promoting heading and enhancing grain yield traits in wheat. The researchers used CRISPR/Cas9-based gene editing to create knockout mutants of TaMYB72 and found that these mutants displayed later heading dates and increased grain yield traits compared to the wild-type plants. The study also revealed that TaMYB72 directly activates the expression of TaFT, a gene involved in flowering and spikelet development, to regulate the height and yield traits of wheat. These findings provide valuable insights into the genetic basis of grain yield traits and heading date in wheat, and suggest TaMYB72 as a potential target gene for increasing grain yield in breeding programs. [Extracted from the article]

Feeding the growing world population is a primary concern faced by plant breeders and producers. The world population of 8 billion is expected to reach 9.8 billion by 2050, which will demand a 60% increase in food production. These demands need to be met under changing climatic conditions and already stretched resources by extending the boundaries of agriculture to urban areas, deserts, and fresh and saltwater bodies. Additionally, crops are needed to support deep space explorations. Therefore, plants with desirable stature, organization, better resource use efficiency, and higher yield are required to meet these targets. The food security challenge is not new; from prehistoric times, humans shaped plant architecture to make plants fit their needs. For example, intentional/unintentional selection in different plants led to the development of un-branched maize from branched teosinte, spikes with more to fewer inflorescence branches in barley and wheat, tall vine-like plants into compact bushes in tomato and soybean, and from tall to semidwarf varieties in wheat, barley, rice, and sorghum. However, control of plant architecture is complex, as several phytohormone-signal transduction pathways, besides other genetic and epigenetic factors, determine it. Among the plant hormones, strigolactones are vital in shoot branching and root growth, influencing the plant's architecture. Given the importance of shoot architecture in determining yield, we reviewed different traits defining plant architecture and genetic and physiological factors contributing to these traits with attention to wheat, barley, rice, and Arabidopsis. We hope the information will help develop crops with desired architecture for terrestrial and extraterrestrial farming. [ABSTRACT FROM AUTHOR]

Background: Wheat is staple diet for majority of people of world and requires several nutrients for optimum growth like Nitrogen, Potassium and Zinc etc. These nutrients when added in the form of chemical fertilizers definitely increase production but at the cost of negative impact on soil, air, water and living beings. Nanoformulations can provide a possible solution to this problem. The current study tried to assess the impact of foliar application of Nano-N, K, Zn on morphological and yield related parameters of wheat. Methods: Wheat plants were grown up to harvesting stage for two consecutive years from 2018 to 2020. Pots grown plants were treated with three different concentrations of Nano-N, K, Zn and bulk/chemical N, K, Zn along-with a control setup having no external nutrients supplement. Several morphological and yield related parameters were recorded. Result: Application of Nano-N, K, Zn resulted in statistically significant increase in plant height, seeds per spike, root length, 100 seed weight, yield and biomass accumulation compared to the control and bulk/chemical N, K, Zn. Highest yield per pot of 23.87 g was obtained under nano-N, K, Zn treatment while yield under bulk fertilizers and control setup was only 7.54 g and 4.38 g respectively. Our work presents a novel combination of nitrogen, potassium and zinc nanofertilizers which not only increase quality of wheat produce but also environment friendly too. [ABSTRACT FROM AUTHOR]

Precision agriculture involves the application of advanced technologies to improve agricultural productivity, efficiency, and profitability while minimizing waste and environmental impacts. Deep learning approaches enable automated decision-making for many visual tasks. However, in the agricultural domain, variability in growth stages and environmental conditions, such as weather and lighting, presents significant challenges to developing deep-learning-based techniques that generalize across different conditions. The resource-intensive nature of creating extensive annotated datasets that capture these variabilities further hinders the widespread adoption of these approaches. To tackle these issues, we introduce a semi-self-supervised domain adaptation technique based on deep convolutional neural networks with a probabilistic diffusion process, requiring minimal manual data annotation. Using only three manually annotated images and a selection of video clips from wheat fields, we generated a large-scale computationally annotated dataset of image–mask pairs and a large dataset of unannotated images extracted from video frames. We developed a two-branch convolutional encoder–decoder model architecture that uses both synthesized image–mask pairs and unannotated images, enabling effective adaptation to real images. The proposed model achieved a Dice score of 80.7% on an internal test dataset and a Dice score of 64.8% on an external test set composed of images from five countries and spanning 18 domains, indicating its potential to develop generalizable solutions that could encourage the wider adoption of advanced technologies in agriculture. [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]

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]

BACKGROUND: Wild relatives of wheat (Triticum spp.) harbor beneficial alleles for potential improvement and de novo domestication of selected genotypes with advantageous traits. We analyzed the nutrient composition in wild diploid and tetraploid wheats and their domesticated diploid, tetraploid and hexaploid relatives under field conditions in Germany and compared them with modern Triticum aestivum and Triticum durum cultivars. Grain iron (Fe) and zinc (Zn) concentrations, phytate:mineral molar ratios, grain protein content (GPC) and antioxidant activity were analyzed across 125 genotypes. RESULTS: Grain Fe and Zn concentrations in wild wheats were 72 mg kg−1 and 59 mg kg−1, respectively, with improved bioavailability indicated by Phytate:Fe and Phytate:Zn molar ratios (11.7 and 16.9, respectively) and GPC (231 g kg−1). By comparison, grain Fe and Zn concentrations in landrace taxa were 54 mg kg−1 and 55 mg kg−1, respectively, with lower Phytate:Fe and Phytate:Zn molar ratios (15.1 and 17.5, respectively) and GPC (178 g kg−1). Average grain Fe accumulation in Triticum araraticum was 73 mg kg−1, reaching 116 mg kg−1, with high Fe bioavailability (Phyt:Fe: 11.7; minimum: 7.2). Wild wheats, landraces and modern cultivars showed no differences in antioxidant activity. Triticum zhukovskyi stood out with high grain micronutrient concentrations and favorable molar ratios. It was also the only taxon with elevated antioxidant activity. CONCLUSION: Our results indicate alteration of grain quality during domestication. T. araraticum has promising genotypes with advantageous grain quality characteristics that could be selected for de novo domestication. Favorable nutritional traits in the GGAA wheat lineage (T. araraticum and T. zhukovskyi) hold promise for improving grain quality traits. © 2024 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry. [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]

Wheat landraces are traditional varieties that have evolved over generations in response to local environments and farming practices and therefore exhibit remarkable adaptability to challenging climatic conditions and low-input farming systems. While the suitability of Mediterranean landraces to non-optimal climatic conditions during anthesis and grain ripening stage have been previously assessed, the role of photosynthesis efficiency and stomatal control on this resilience remains unexplored. This study aims to evaluate the relationship between grain yield and the post-anthesis flag leaf gas exchanges of Sicilian wheat landraces under irrigated and rainfed conditions and to compare these traits to modern durum (Triticum turgidum subsp. durum) and bread wheat (T. aestivum) varieties. Results indicate that wheat landraces respond to water availability similarly to modern varieties, reducing stomatal conductance by 26.8% and net photosynthesis by 18.1% under rainfed conditions, resulting in 10.6% lower grain yield compared to irrigated conditions. However, some landraces demonstrate comparable or even higher flag leaf net photosynthesis rates and lower transpiration levels, leading to higher yields in both rainfed and irrigated conditions, confirming their value as a source of gene pool for wheat breeding programs in drought-prone Mediterranean regions. [ABSTRACT FROM AUTHOR]

Background: The rice-wheat cropping system is the prevailing agricultural method in the North-Western states of India, namely in the Indo-Gangetic plains. The practice of open burning of rice residue is frequently employed for expedient land preparation, but it has significant adverse impacts on both the environment and human health. These include the emission of greenhouse gases, loss of nutrients, elevated concentrations of particulate matter (PM), and disruption of the biological cycle. This research aims to investigate the implementation of effective management strategies in the rice-wheat cropping system, namely via the use of tillage-based crop cultivation techniques, stubble retention, and integration approaches. The objective is to enhance soil health features in order to augment crop yield and improve its attributes. Results: The research was carried out using a split plot experimental design, consisting of three replications. The main plot consisted of four different cultivation methods, while the subplot included three genotypes of both rice and wheat. The research demonstrates the enhanced efficacy of residue application is significantly augmenting soil nutrient concentrations compared to standard tillage practices (P < 0.05). This was accomplished by an analysis of soil nutrient levels, namely nitrogen (N), phosphorus (P), potassium (K), and organic carbon (OC), at a depth of 0–15 cm. The implementation of natural farming, zero tillage, and reduced tillage practices resulted in decreases in rice grain yields of 34.0%, 16.1%, and 10.8%, respectively, as compared to conventional tillage methods. Similarly, the implementation of natural farming, zero tillage, and reduced tillage resulted in reductions in wheat grain yields of 59.4%, 10.9%, and 4.6% respectively, in comparison to conventional tillage practices. Conclusion: Regarding the individual crop genotypes investigated, it was continuously observed that Him Palam Lal Dhan 1 and HPW 368 displayed considerably greater grain yields for both rice and wheat during the two-year experimental period. Furthermore, when considering different cultivation methods, conventional tillage emerged as the most effective approach for obtaining higher productivity in both rice and wheat. Additionally, Him Palam Lal Dhan 1 and HPW 368 exhibited superior performance in terms of various crucial yield components for rice (such as panicle density, grains per panicle, panicle weight, and test weight) and wheat (including effective tiller density, grains per spike, spike weight, and 1000-grain weight). [ABSTRACT FROM AUTHOR]

Background: Agropyron cristatum (L.) is a valuable genetic resource for expanding the genetic diversity of common wheat. Pubing3228, a novel wheat-A. cristatum hybrid germplasm, exhibits several desirable agricultural traits, including high grain number per spike (GNS). Understanding the genetic architecture of GNS in Pubing3228 is crucial for enhancing wheat yield. This study aims to analyze the specific genetic regions and alleles associated with high GNS in Pubing3228. Methods: The study employed a recombination inbred line (RIL) population derived from a cross between Pubing3228 and Jing4839 to investigate the genetic regions and alleles linked to high GNS. Quantitative Trait Loci (QTL) analysis and candidate gene investigation were utilized to explore these traits. Results: A total of 40 QTLs associated with GNS were identified across 16 chromosomes, accounting for 4.25–17.17% of the total phenotypic variation. Five QTLs (QGns.wa-1D, QGns.wa-5 A, QGns.wa-7Da.1, QGns.wa-7Da.2 and QGns.wa-7Da.3) accounter for over 10% of the phenotypic variation in at least two environments. Furthermore, 94.67% of the GNS QTL with positive effects originated from Pubing3228. Candidate gene analysis of stable QTLs identified 11 candidate genes for GNS, including a senescence-associated protein gene (TraesCS7D01G148000) linked to the most significant SNP (AX-108,748,734) on chromosome 7D, potentially involved in reallocating nutrients from senescing tissues to developing seeds. Conclusion: This study provides new insights into the genetic mechanisms underlying high GNS in Pubing3228, offering valuable resources for marker-assisted selection in wheat breeding to enhance yield. [ABSTRACT FROM AUTHOR]

Agricultural areas worldwide suffer immensely due to the rapid depletion of irrigation water. Applying the proper nutrients can alleviate the harmful effects of water stress. This field study transpired to evaluate the influence of both titanium-dioxide (TiO2) and zinc-oxide (ZnO) nanoparticles on two wheat (Triticum aestivum L.) cultivars (Gimeza-12 and Sids-13) under water irrigation requirements (WIR) of 100% and 75% WIR. Water stress reduced yield attributes and mineral contents but increased protein, gluten, Zeleny sedimentation index, flavonoids, antioxidant activities, and WP. All used concentrations of TiO2-NPs and ZnO-NPs induced positive responses for all tested parameters compared with non-treated corresponding controls under well-watered and drought-stress conditions. Treatment with 10 mg L-1 of ZnO-NPs followed by 10 mg L-1 TiO2-NPs gave the highest values of all studied yield parameters in plants subjected to 75% WIR for both cultivars compared to other controls. The results showed that the Gimeza-12 cultivar, which had the highest grain yield, was more tolerant to drought than the Sids-13 cultivar. [ABSTRACT FROM AUTHOR]

The intensive agriculture that is used in many countries has led to a reduction in biodiversity and the deterioration of the environment. Therefore, it is important to increase the adoption of cropping systems with high biodiversity. The objectives of the present study were the following: 1. assess the performance and sustainability of novel highly diversified production systems compared to the current traditional system and 2. provide quantitative economic and ecosystem service information for farmers, extension workers, and policy makers in order to support the development of sustainable and resilient high species cultivar/landrace diversification (HSD) production systems. The rotation of wheat–pea–barley was a system with low energy inputs and high outputs, significantly increasing the energy efficiency. Also, the same system demonstrated better economic and environmental indices, making it a suitable cropping system for Mediterranean areas. [ABSTRACT FROM AUTHOR]

Over the course of two winter periods, researchers at the Agricultural Experiment Unit, College of Agricultural Engineering Sciences, University of Baghdad, studied the effects of covering wheat (the Al-Furat variety) and “vitamins B9” (“folic acid”) and E “(tocopherol)” on a number of growth traits. Three independent trials were conducted utilizing a factorial design within a Randomized Complete Block Design. The first component was folic acid at 0, 250, and 500 mg L-1 ; the second component was vitamin E at 0, 1, and 2 ml L-1 . At the start of the tillering and flowering stages, both vitamins were applied. All measured characteristics (plant height, flag leaf area, total tiller count, plant dry weight at booting and 100% blooming phases, and “vitamin B9” 500 mg L-1 ) were found exceeded at this dosage. Aside from that, total chlorophyll, chlorophyll a and b content in leaves, and the pace of crop growth.Since the focus of 2 ml L-1 was higher than most of the attributes, applying vitamin E influenced the growth characteristics. The number of tillers, plant dry weight, crop growth rate, total chlorophyll, biological yield, chlorophyll a and b in leaves. [ABSTRACT FROM AUTHOR]

Plant-growth-promoting bacteria are an important economic and environmental resource as biofertilizers that can stimulate plant growth and improve agricultural yields. In this study, potential plant growth-promoting bacteria were isolated from soil samples collected in Russia. Strains that manifested active growth on a nitrogen-free medium, the Pikovskaya medium (with insoluble phosphates) and CAS (Chrome Azurol S) agar, were selected for the study. All bacterial isolates were identified by 16S rRNA gene sequencing analysis. Seventeen bacterial isolates of different species were purified and quantified for their ability to grow on nitrogen-free media; dissolve phosphate; and produce ammonium, indole-3-acetic acid, siderophores, and antifungal activity. Principal component analysis identified three groups of strains: one with the maximum signs of providing "plant nutrition"; one with signs of "antimicrobial activity"; and a group "without outstanding signs". All 17 strains were involved in experiments involving growing inoculated wheat seeds (Triticum aestivum) in pots under natural environmental conditions, and were assessed by their effect on the wheat growth and yield as well as on the chemical composition of the soil. For the "plant nutrition" group, regression analysis revealed a connection between indicators of plant growth, ear length, and ammonium accumulation in the soil. However, in other groups, there were also strains showing a positive effect on plant growth, which suggests the necessity of involving additional factors to predict the ability of strains to affect plants when screened in the laboratory. [ABSTRACT FROM AUTHOR]

Black-grass (Alopecurus myosuroides) is one of the most problematic agricultural weeds of Western Europe, causing significant yield losses in winter wheat (Triticum aestivum) and other crops through competition for space and resources. Previous studies link black-grass patches to water-retaining soils, yet its specific adaptations to these conditions remain unclear. We designed pot-based waterlogging experiments to compare 13 biotypes of black-grass and six cultivars of wheat. These showed that wheat roots induced aerenchyma when waterlogged whereas aerenchyma-like structures were constitutively present in black-grass. Aerial biomass of waterlogged wheat was smaller, whereas waterlogged black-grass was similar or larger. Variability in waterlogging responses within and between these species was correlated with transcriptomic and metabolomic changes in leaves of control or waterlogged plants. In wheat, transcripts associated with regulation and utilisation of phosphate compounds were upregulated and sugars and amino acids concentrations were increased. Black-grass biotypes showed limited molecular responses to waterlogging. Some black-grass amino acids were decreased and one transcript commonly upregulated was previously identified in screens for genes underpinning metabolism-based resistance to herbicides. Our findings provide insights into the different waterlogging tolerances of these species and may help to explain the previously observed patchiness of this weed's distribution in wheat fields. Black-grass is a problematic weed of winter wheat. To better understand if waterlogging tolerance increases its weediness, we conducted controlled waterlogging studies comparing the physiology and molecular responses of black-grass and wheat. These revealed differences in roots and aerial tissues within and between species. Molecular analyses showed that wheat mounts a significant molecular response, altering gene expression and metabolites with waterlogging, whereas black-grass showed minimal responses to waterlogging despite its apparent tolerance. This article belongs to the Collection Flooding Stress and Hypoxic Responses in Plants. [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]

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]

Background: Wheat (Triticum aestivum L.) is one of the most widely grown and vital cereal crops, containing a high percentage of basic nutrients such as carbohydrates and proteins. Drought stress is one of the most significant limitations on wheat productivity. Due to climate change influences plant development and growth, physiological processes, grain quality, and yield. Drought stress has elicited a wide range of plant responses, namely physiological and molecular adaptations. Biopriming is one of the recent attempts to combat drought stress. Mitigating the harmful impact of abiotic stresses on crops by deploying extreme-habitat-adapted symbiotic microbes. The purpose of this study was to see how biopriming Triticum aestivum grains affected the effects of inoculating endophytic fungi Aspergillus fumigatus ON307213 isolated from stressed wheat plants in four model agricultural plants (Gemmiza-7, Sids-1, Sakha8, and Giza 168). And its viability in reducing drought stress through the use of phenotypic parameters such as root and shoot fresh and dry weight, shoot and root length, and so on. On a biochemical and physiological level, enzymatic parameters such as catalase and superoxidase dismutase are used. Total phenolics, flavonoids, and photosynthetic pigments are non-enzymatic parameters. Making use of molecular techniques such as reverse transcriptase polymerase chain reaction (RT-PCR). Results: It has been found that using Aspergillus fumigatus as a biological biopriming tool can positively impact wheat plants experiencing drought stress. The total biomass of stressed wheat plants that had been bio-primed rose by more than 40% as compared to wheat plants that had not been bio-primed. A. fumigatus biopriming either increased or decreased the amount of enzymatic and non-enzymatic substances on biochemical scales, aside from the noticeable increase in photosynthetic pigment that occurs in plants that have been bio-primed and stressed. Drought-resistant genes show a biopriming influence in gene expression. Conclusions: This is the first paper to describe the practicality of a. fumigatus biopriming and its effect on minimizing the degrading effects of drought through water limitation. It suggests the potential applications of arid habitat-adapted endophytes in agricultural systems. [ABSTRACT FROM AUTHOR]

The Dzungar Basin of northern Xinjiang has previously been considered a marginal environment with little evidence for the development of prehistoric agriculture. Recent archaeobotanical studies have indicated the region as being a route for the transmission of domesticated plants, technologies and ideas between East and West Eurasia during prehistory, as early as 5000 BP. These interactions are still poorly understood and most evidence for early plant food production and consumption in the region comes from limited mortuary contexts. In this study we present plant macrofossil analysis from the settlement site of Luanzagangzi on the southern side of the Dzungar Basin. From ca. 3130 BP an agricultural package of east and west Asian cereals and chaff is present, comprising wheat, barley, foxtail millet, broomcorn millet, and significantly a single grain of japonica type rice. AMS dating indicates this is the oldest directly dated rice in Xinjiang and the broader region, ranging 3069–2881 cal. BP. Cereal morphometrics and material culture from the site further indicate a connection with the Gansu region to the east. The spread of agriculture into the site environment may be linked to the onset of wetter conditions relating to strengthened westerly systems across arid Central Asia in the Late-Holocene. A declining abundance of West Asian cultivars over the period of the site's occupation possibly reflect a shift away from intensive agriculture to low-level management of millets. [ABSTRACT FROM AUTHOR]

Soil erosion poses a significant threat to agricultural production worldwide, with a still-debated impact on the current increase in atmospheric CO2. Whether erosion acts as a net carbon (C) source or sink also depends on how it influences greenhouse gas (GHG) emissions via its impact on crop yield and nutrient loss. These effects on the environmental impacts of crops remain to be considered. To fill this gap, we combined watershed-scale erosion modeling with life cycle assessment to evaluate the influence of soil erosion on environmental impacts of wheat production in the Ebro River basin in Spain. This study is the very first to address the full GHG balance of erosion including its impact on soil fertility and its feedback on crop yields. Two scenarios were simulated from 1860 to 2005: an eroded basin involving conventional agricultural practices, and a non-eroded basin involving conservation practices such as no-till. Life cycle assessment followed a cradle-to-farm-gate approach with a focus on recent decades (1985–2005). The mean simulated soil erosion of the eroded basin was 2.6 t ha−1 year−1 compared to the non-eroded basin. Simulated soils in both eroded and non-eroded basins lost organic C over time, with the former emitting an additional 55 kg CO2 ha−1 year−1. This net C source represented only 3% of the overall life cycle GHG emissions of wheat grain, while the emissions related to the increase of fertilizer inputs to compensate for N and P losses contributed a similar percentage. Wheat yield was the most influential parameter, being up to 61% higher when implementing conservation practices. Even at the basin scale, erosion did not emerge as a net C sink and increased GHG emissions of wheat by 7–70%. Nonetheless, controlling erosion through soil conservation practices is strongly recommended to preserve soils, increase crop yields, and mitigate GHG emissions. [ABSTRACT FROM AUTHOR]

The processes coupled with carbon and water exchange are linked to crop assimilation, water consumption, controlling crop growth and development, and ultimately determining crop yield. Therefore, studying the characteristics of crop water constraints and their controlling factors at multiple scales is of great significance for regional and global food production stability and food security. Employing field observations and a comprehensive literature review, this study investigates the maximum water-use efficiency of wheat and its governing factors at both leaf and canopy (ecosystem) scales. The results demonstrate remarkable consistency and well-defined boundaries in maximum water-use efficiency across diverse climate regions and wheat varieties, both at the leaf and agricultural ecosystem scales. At the leaf scale, the maximum water-use efficiency of wheat was 4.5 μg C mg−1 H2O, while for wheat agricultural ecosystems, on a daily scale, the maximum water-use efficiency was 4.5 g C kg−1 H2O. Meanwhile, the maximum water-use efficiency of wheat agricultural ecosystems decreased continuously with increasing time scales, with values of 6.5, 4.5, 3.5, and 2 g C kg−1 H2O for instantaneous, daily, weekly, and monthly scales, respectively. Environmental factors, primarily vapor pressure deficit, light, and soil water content, exert significant control over leaf-level water-use efficiency. Similarly, the maximum water-use efficiency of agricultural ecosystems fluctuates in response to daily variations in meteorological elements. C3 crops like wheat exhibit remarkable resilience in their carbon–water exchange patterns across diverse environmental conditions. The findings in the current research can serve as a reference for improving crop water-use efficiency. [ABSTRACT FROM AUTHOR]

Wheat production is under pressure due to climate change, increasing input production and higher demand for grain. Successful production depends on certain factors such as agroecological conditions, technical management and genotype, i.e., variety. The main goal was to determine yield, yield components and other morphological and agronomic characteristics of different wheat varieties and to analyze weather conditions during the 2020/2021 vegetative season. The research was conducted on agricultural holding in eastern Croatia according to RCB design in three replications. In general, the weather during 2020/2021 did not deviate too much compared to the observed long-term mean, but significant deviations in distribution were recorded during individual months. The precipitation deviation ranged from -99.7 % (June) to + 51.0 % (December), while air temperature oscillations were even more pronounced. The implemented agrotechnics were in accordance with the profession's recommendations for adequate plant protection and mineral fertilization. The analysis of variance revealed significance for five out of nine properties studied (number of grains per ear, 1000 grain mass, hectolitre mass, plant height and ear length). The average yield of all five varieties in this survey was 9.36 t ha-1. Each variety had certain advantages in terms of one and/or more characteristics, as the yield differences were not statistically justified. By sowing high yield varieties of different seed companies, it is possible to achieve higher and more stable yields, which is the goal of every production. Choosing the right varieties of wheat for a particular area is also important due to the increasingly pronounced climate changes. [ABSTRACT FROM AUTHOR]

Millets have been the staple food in many parts of the world, but in recent times they have been losing ground because of the increased use of processed foods and grains, such as wheat and rice. India has been the granary of millets due to the largest production and export of Indian millets globally. The very nature of millets being drought-resistant, small seeded grass, which can be grown in arid conditions, with less water and less farming intensive, makes it a great choice for ecological agriculture and sustainable source of food for combating hunger in the rapidly changing global climate and constructing climate-resistant agri-food systems. The various health benefits of millets make them an excellent choice for patients with celiac disease, type 2 diabetes mellitus, ischemic heart disease, dyslipidemia, obesity, etc. [ABSTRACT FROM AUTHOR]

Estimating wheat yield accurately is crucial for efficient agricultural management. While canopy spectral information is widely used for this purpose, the incorporation of canopy volumetric features (CVFs) remains underexplored. This study bridges this gap by utilizing unmanned aerial vehicle (UAV) multispectral imaging to capture images and elevation data of wheat at key developmental stages—gestation and flowering stages. We innovatively leveraged the elevation differences between these stages to calculate canopy height, develop a novel CVF, and refine the wheat yield prediction model across various wheat varieties, nitrogen fertilizer levels, and planting densities. The integration of canopy volume information significantly enhanced the accuracy of our yield prediction model, as evidenced by an R2 of 0.8380, an RMSE of 313.3 kg/ha, and an nRMSE of 11.33%. This approach not only yielded more precise estimates than models relying solely on spectral data but also introduced a novel dimension to wheat yield estimation methodologies. Our findings suggest that incorporating canopy volume characteristics can substantially optimize wheat yield prediction models, presenting a groundbreaking perspective for agricultural yield estimation. [ABSTRACT FROM AUTHOR]

Geostatistics is a crucial tool for data analysis in the field of precision agriculture, allowing the characterization of spatial variability magnitude, optimizing profitability and yield in agricultural areas. In this context, the present study aimed to evaluate the spatial dependence of the variables yield, Normalized Difference Vegetation Index (NDVI), and surface temperature in winter wheat plants. This was achieved through fitting semivariograms with different statistical models and interpolating the study variables using Ordinary kriging. The experiment was conducted at Fazenda Santa Helena, located in the municipality of Lavras in the state of Minas Gerais, Brazil, with a 12-hectare winter wheat crop of the TBIO Calibre variety. Data were collected using a grid sampling method at different stages of wheat plant growth (tillering and elongation). The analyzed variables included yield, NDVI, and surface temperature. Statistical analyses were performed using the R software. Initially, the spatial dependence of the study variables was analyzed by fitting semivariograms using the Restricted Maximum Likelihood (REML) method and considering spherical, exponential, and gaussian models. The evaluation of errors was carried out through cross-validation, and subsequently, the data interpolation was performed using ordinary kriging with the best-fitted semivariogram model. The results demonstrated a proper fit of semivariograms for the study models, with the spherical model standing out for surface temperature variables (elongation and tillering), NDVI (tillering), and the exponential model for NDVI (elongation) and yield. Therefore, the use of geostatistics is emphasized as an important tool to assist in precision agriculture management in winter wheat crops. [ABSTRACT FROM AUTHOR]

Crop diversification has been proposed as a promising strategy for transitioning towards sustainable agricultural systems. The Hetao Irrigation District faces multiple challenges in ensuring food security and farmer livelihood. A diversified green manure inclusive cropping system was designed to evaluate the influences of hairy vetch (Vicia villosa Roth) incorporation on soil nutrients, yield, and economic benefit compared to the existing wheat–maize–sunflower rotation system in the Hetao Irrigation District. The specific method was as follows: spring wheat (Triticum-durum L.)–vetch rotation in the first year, maize (Zea mays L.)/vetch intercropping in the second year, and sunflower (Helianthus annuus L.)/vetch relay intercropping in the third year. Over a 6-year experimental observation, green manure incorporation significantly increased soil alkaline hydrolyzed nitrogen and exchangeable potassium levels. Although the effect of green manure incorporation on the yield of rotated spring wheat and intercropped maize was not prominent, it improved sunflower yield in the second rotation cycle by 11%. Consequently, only the sunflower led to an increase in income of 235 CNY ha−1 in the second rotation cycle. This indicates that the soil-property-building and yield-enhancing effects of green manure incorporation require time to accumulate. However, the benefits derived from increased yield were not sufficient to offset the production costs associated with green manure cultivation, resulting in less-than-desirable economic returns. [ABSTRACT FROM AUTHOR]

Salt stress affects the growth and global production of wheat (Triticum aestivum L.). Plant growth-promoting microbes can enhance plant resistance to abiotic stresses. In this study, we aimed to assess the inoculation of soil with Streptomyces sp. HU2014 to improve wheat tolerance to salt stress from multiple perspectives, including the interaction of the strain, the addition of NaCl, the condition of the wheat, and rhizosphere microbial communities. The results showed that the strain promoted wheat growth under NaCl stress by increasing biomass by 19.8%, total chlorophyll content by 72.1%, proline content by 152.0%, and malondialdehyde content by 106.9%, and by decreasing catalase by 39.0%, peroxidase by 1.4%, and soluble sugar by 61.6% when compared to the control. With HU2014 soil inoculation, total nitrogen, nitrate nitrogen, total phosphorus, and Olsen phosphorus increased, whereas ammonium nitrogen and pH decreased. HU2014 inoculation and/or the addition of NaCl affected the diversity of rhizosphere bacteria, but not fungi. The structure of the microbial community differed after HU2014 inoculation, with Proteobacteria, Acidobacteriota, Bacteroidota, and unclassified fungi being the dominant phyla, and these taxa correlated with the above-mentioned soil parameters. Thus, this study provided a promising way to enhance wheat tolerance to salt stress and improve the agricultural ecological environment by using plant growth-promoting microbes. [ABSTRACT FROM AUTHOR]

Pesticide treatment leads to a significant increase in wheat yield and enhances pest resistance. However, pesticides, particularly the insecticide cypermethrin, which is used for wheat Triticum aestivum L. field and grain storage treatment, are toxic xenobiotics. To reduce their toxicity, it is possible to pre-treat seeds with plant growth-promoting rhizobacteria (PGPR), which can enhance plant resistance to adverse environmental factors. In this study, we used a previously unused as PGPR representative of the genus Azospirillum, A. thiophilum BV-ST, isolated in Russia, which makes it interesting for agricultural use in the same climatic zone. We optimized the detection method of A. thiophilum using PCR. Then, we demonstrated that this bacterium successfully inoculates to wheat roots. We showed that cypermethrin treatment of one- and two-week-old wheat seedlings caused an increase in mtDNA damage, and in one-week-old seedlings, it induced a decrease in chlorophyll levels. However, three- and four-week-old seedlings were more resistant to damage, possibly due to their approximately 5-fold higher expression of NDOR-1 and GST genes, which play an important role in xenobiotic detoxification. Pre-treatment of wheat seeds with A. thiophilum contributed to the upregulation of NDOR-1 and GST gene expression in one- and two-week-old seedlings, resulting in the protection of mtDNA from cypermethrin-induced damage and prevented the decrease in chlorophyll levels. [ABSTRACT FROM AUTHOR]

Farmers around the world time the planting of their crops to optimize growing season conditions and choose varieties that grow slowly enough to take advantage of the entire growing season while minimizing the risk of late-season kill. As climate changes, these strategies will be an important component of agricultural adaptation. Thus, it is critical that the global models used to project crop productivity under future conditions are able to realistically simulate growing season timing. This is especially important for climate- and hydrosphere-coupled crop models, where the intra-annual timing of crop growth and management affects regional weather and water availability. We have improved the crop module of the Community Land Model (CLM) to allow the use of externally specified crop planting dates and maturity requirements. In this way, CLM can use alternative algorithms for future crop calendars that are potentially more accurate and/or flexible than the built-in methods. Using observation-derived planting and maturity inputs reduces bias in the mean simulated global yield of sugarcane and cotton but increases bias for corn, spring wheat, and especially rice. These inputs also reduce simulated global irrigation demand by 15 %, much of which is associated with particular regions of corn and rice cultivation. Finally, we discuss how our results suggest areas for improvement in CLM and, potentially, similar crop models. [ABSTRACT FROM AUTHOR]

Cereals are the most broadly produced crops and represent the primary source of food worldwide. Nitrogen (N) is a critical mineral nutrient for plant growth and high yield, and the quality of cereal crops greatly depends on a suitable N supply. In the last decades, a massive use of N fertilizers has been achieved in the desire to have high yields of cereal crops, leading to damaging effects for the environment, ecosystems, and human health. To ensure agricultural sustainability and the required food source, many attempts have been made towards developing cereal crops with a more effective nitrogen use efficiency (NUE). NUE depends on N uptake, utilization, and lastly, combining the capability to assimilate N into carbon skeletons and remobilize the N assimilated. The glutamine synthetase (GS)/glutamate synthase (GOGAT) cycle represents a crucial metabolic step of N assimilation, regulating crop yield. In this review, the physiological and genetic studies on GS and GOGAT of the main cereal crops will be examined, giving emphasis on their implications in NUE. [ABSTRACT FROM AUTHOR]

Background: Seed is the starting point of agriculture and dictates ultimate productivity of other inputs. Quality seed of improved varieties is an important basic unit for enhancing productivity of any crop species. As the quality deteriorates during subsequent generations, the old must be replaced with fresh lots of quality seeds. The present study was an attempt to analyze the source, SRR and management of wheat seed in Amritsar district of Punjab. Methods: The current study was conducted on primary data collected from 120 farmers during the agricultural year 2019-20. The data was analyzed using simple tabular analysis and other suitable statistical techniques. Result: The study found that the most preferred source of seed was institutional sources from which 45.83 per cent of the seed was procured from these agencies. The second most preferred source was self-retained by the farmers as 43.70 per cent farmer's preferred self-retained seeds. Only small farmers and medium farmers procured wheat seed from fellow farmers, relatives and friends. This source was preferred by small and medium farmers as seed is available free of cost and no immediate cash payment was charged by fellow farmers or relatives. Seed replacement rate was found to be 49.94 per cent for wheat crop in Amritsar district of Punjab. The study found that minimum attention was paid at post storage of wheat seed (2.50 per cent) whereas maximum attention was paid in the field (48.83 per cent) during wheat seed production. The main determinants of purity and quality of wheat seed were past experience of the farmer, repute of the institution, tag of certification agency and advice of known person. Seed replacement rate (SSR) for wheat was less for small farmers in the study area which can be increased by giving incentives to farmers for using certified seeds. These incentives can be in the form of higher price of produce to the small farmers. Maximum farmers used self-retained seed foe the next season and they paid minimum attention to the storage of seed which lead to deterioration in the quality of seed. Farmers should be educated to use scientific methods in the storage of seeds. [ABSTRACT FROM AUTHOR]

Breeding has dramatically changed the plant architecture of wheat (Triticum aestivum), resulting in the development of high-yielding varieties adapted to modern farming systems. However, how wheat breeding shaped the genomic architecture of this crop remains poorly understood. Here, we performed a comprehensive comparative analysis of a whole-genome resequencing panel of 355 common wheat accessions (representing diverse landraces and modern cultivars from China and the United States) at the phenotypic and genomic levels. The genetic diversity of modern wheat cultivars was clearly reduced compared to landraces. Consistent with these genetic changes, most phenotypes of cultivars from China and the United States were significantly altered. Of the 21 agronomic traits investigated, 8 showed convergent changes between the 2 countries. Moreover, of the 207 loci associated with these 21 traits, more than half overlapped with genomic regions that showed evidence of selection. The distribution of selected loci between the Chinese and American cultivars suggests that breeding for increased productivity in these 2 regions was accomplished by pyramiding both shared and region-specific variants. This work provides a framework to understand the genetic architecture of the adaptation of wheat to diverse agricultural production environments, as well as guidelines for optimizing breeding strategies to design better wheat varieties. Genetic changes during breeding enable wheat to adapt to diverse agricultural regions and elucidate ways to optimize breeding strategies for better wheat varieties. [ABSTRACT FROM AUTHOR]

Background: Agricultural activities in 2020 have resulted in 5.5 billion tons of CO2 equivalent globally, which is expected to rise because the food system would have to grow 70% more food for the population in 2050. Research suggests that agricultural productivity in South Asian countries, will increase food security; however, the role of their food crops and livestock products in environmental imprints is uncertain. This review aimed to assess the environmental impacts resulting from pre‐ and post‐production agricultural activities related to edible food crops and livestock products consumed in eight South Asian countries. Methods: Studies were retrieved using three databases (PubMed, Google Scholar and Science Direct) from 2011 to 2022. The protocol for this scoping review was not registered. Results: Twenty‐seven studies met the inclusion criteria. Most studies were conducted in India. Twenty‐four articles assessed greenhouse gases (GHG) emissions, followed by water footprints (n = 5), nitrogen and phosphorus (N&P) emissions (n = 4), and land requirements (n = 4). The production of rice and wheat was identified as a significant contributor to GHG emissions. In India, Bangladesh and Sri Lanka, the production of livestock (meat/bovine/shrimp and milk) was reported to be harmful to the environment. Inconclusive data were retrieved for other environment variables. Conclusions: Diversification in food production and cultivating additional coarse cereals (millets) offer opportunities for GHG reduction. Nevertheless, more comprehensive and longitudinal studies for South Asian countries are essential to make precise conclusions and validate the present review. Key points: The present study explored the role of South Asian food crops and livestock in environmental degradation.Most studies assessed green house gas (GHG) emissions.Production of wheat, rice and livestock products contributed significantly to GHG emissions.Diversification in food production, cultivating coarse cereals such as millets is desirable. [ABSTRACT FROM AUTHOR]

A laboratory experimentation was done in the Department of Plant Physiology, Institute of Agricultural Sciences, Banaras Hindu University to evaluate elevated night temperature effect in wheat (Triticum aestivum L.) to see the response in some antioxidant and biochemical parameters in two wheat cultivars viz. HUW-234 (comparatively tolerant to heat stress) and sonalika (comparatively susceptible to heat stress). A significance difference was recorded in the parameters pertaining to antioxidant system includes catalase, SOD and APX activity were found to increase substantially when the plants kept under stress conditions (250C/240C day and night temperature) than the plants kept under controlled condition (250C/150C day and night temperature). The percent increase in the antioxidant enzyme activity was found to be more in the tolerant genotype (HUW-234) than in the susceptible genotype (Sonalika). There was 23.52 % increase was reported in the catalase activity by tolerant genotype when kept under stress conditions than those kept under control. Significant reductions were reported in most of the photosynthetic and membrane parameters viz., chlorophyll ‘a’, chlorophyll ‘b’ and membrane thermostability index. Similar percent reduction was reported with respect to biochemical parameters (total protein content, starch content and soluble sugar content) in the susceptible variety kept under high night temperature regime. Based on the pooled data of two-year experimentation it can be concluded that variety HUW-234 was found to be more tolerant than variety sonalika to HNT stress. [ABSTRACT FROM AUTHOR]

Conservation agriculture (CA) is a promising management practice adopted by spring wheat growers in the Indo-Gangetic plains (IGPs) of India, particularly in areas where residue burning is prominent. Effective nitrogen management is essential to achieve maximum profitable wheat yield under CA to promote agricultural sustainability. A field experiment conducted during the winter seasons of 2020–21 and 2021–22 comprising seven treatments with varying nitrogen doses from 0 to 250 kg/ha was used to find the best nitrogen management strategy. Instrument-based physiological indices, including the chlorophyll content index (CCI), normalized difference vegetation index (NDVI), Dualex meter-based values, and flavonoids, were used to investigate the relation between these indices and growth stages. Increasing nitrogen levels from 0 to 250 kg/ha resulted in increased growth and physiological indices. However, the increase beyond 150 with or without CA was non-significant in case of many indices. The enriched treatment (250 kg N/ha) recorded a lower grain yield (5123 kg/ha) compared to 100 kg N/ha treatments (5595 kg/ha). The thousand-grain weight was also found to be reduced by 21.2% in 250 kg N/ha compared to the 150 kg N/ha treatment. The application of 200 kg N/ha under CA produced a significant increase (9.6%) in grain yield (6673 kg/ha) as compared to the farmer's practice of 150 kg N/ha. Applying 150 kg N/ha under CA increased grain yield by 231 kg/ha over the same N level without CA, although the difference was non-significant. The application of 200 kg N/ha under CA yielded the highest gross return (2271.8 $/ha), net return (1545.0 $/ha), and B:C (3.1) due to the reduced cost of cultivation in CA and maximum grain yield. Additionally, if this technology is adapted to 13.7 m ha rice–wheat area in South Asia then additional net return from 200 kg N/ha application under CA over farmers practice will be $3.32 billion annually, which is huge amount. Therefore, using 200 kg N/ha under CA can further increase grain yield, productivity, and profitability per unit area. However, for resource-limited growers in rice–wheat growing areas, 150 kg N/ha under CA can still be a viable and economically sound option. [ABSTRACT FROM AUTHOR]

Increasing phosphorus (P) fertiliser use efficiency (PUE) is essential for addressing global nutrition security, food production costs, and environmental pollution. However, a myriad of soil × climate × crop × management interactions control PUE and adaptive tools are needed to put this complexity into context at the field scale. We conducted a Morris global sensitivity analysis on an evaluated agricultural system model (APSIM) across 132 years of climate data to identify important drivers of PUE in a subtropical dryland cropping system. We selected soil, crop, and management parameters to understand their influence on yield, biomass, and grain P export as measures of PUE in a subtropical wheat crop. We then examined three P fertility scenarios ranging from low to high (10, 40, 70 mg available P kg−1 at 0–10 cm, with subsoils to 180 cm at 9–10 mg available P kg−1) resulting in 1,782,000 simulations. In scenarios with medium or high P fertility and higher in-crop rainfall (> 200 mm), nitrogen (N) fertiliser was the most important driver for increasing yield and associated PUE. At low P fertility and lower in-crop rainfall (< 200 mm), P fertiliser and P sorption isotherm parameters were the most important drivers. This highlighted potential constraints to PUE analysis in the region if rainfall data is not available, and to modelling activities if P isotherm data is not available. Our study is the first to use a Morris global sensitivity analysis method for defining the influence of N and P fertiliser, and in-crop rainfall, as short-term (year–year) drivers of PUE. This method may be adapted to investigate emerging challenges in increasing PUE in other agricultural systems, but future research should include interactions with deep P banding, the effects of climate change, and demonstrate drivers over the longer-term (5–10 years). [ABSTRACT FROM AUTHOR]

This study aims to evaluate the impact of training on the use of modern agricultural inputs in comparison to the recommended amount for wheat and maize production in Gozamin and Machakil Woredas in Northwest Ethiopia. The study employs a mixed-methods research design. The propensity score matching and thematic methods of analysis were used to analyze the quantitative and qualitative data, respectively. The study finds that trainees reduced the excess application of wheat seed by 11.66% to 15% ha-1. In Machakil, they tended to reduce excess NPSB application by 21% and increase urea by 52.17% for wheat. But, the NPSB rate was found to increase by 100.4% above the recommended rate in Gozamin. For maize, the trainees increased urea by 12.42% ha-1 in both Woredas. The study recommends the provision of consecutive practical training and demonstrations till farmers get convinced that applying the recommended rates of inputs significantly enhances crop productivity. [ABSTRACT FROM AUTHOR]

The provision of precise and dependable information regarding the extent and distribution of cropland is imperative for the evaluation of food security, agricultural planning, and resource management. Cropland is an important component of land cover type and is offered in multiple existing global/regional land cover products. However, global-scale accuracy evaluation may not be representative of class-specific or local-area accuracy, such as in Northeast China, which is an important grain-producing region of China and has various types of cultivated land (e.g., wheat, rice) and diverse terrains. It poses a great challenge in generating precise cropland classification by automated mapping. Thus, it is indispensable to evaluate the accuracy and reliability of these various land cover datasets before using them. In this study, we collected thirteen sets of global or national-scale land cover datasets. Through the visual interpretation of high-resolution images, ground "truth" samples were collected to evaluate the data accuracy across Northeast China. The overall accuracy (OA) evaluation results in Phase-2020 show that CLCD has the highest value with 0.914, followed by GlobeLand30 (0.906), GLC_FCS30 (0.902), and Esri (0.896) for cropland classification in Northeast China. CGLS-LC100 has the lowest OA (0.710). For the commission and omission errors of six datasets in Phase-2020, CGLS-LC100 has an obvious overestimation (larger commission error), while the two national-scale datasets (CLCD and CLUDs) perform relatively better. In terms of spatial consistency, high spatial agreement among the nine Phase-2015 datasets or in the six Phase-2020 datasets could be discovered in traditional agricultural regions like the Sanjiang–Songnen–Liaohe Plain, and low agreement is found in the transition areas of mountains (hills) and plains with the mixed landscape of forest (grassland) and farmland. In the aspect of comparison pairwise data, CLCD is in good agreement with GLC_FCS30, GlobeLand30, and Esri, while CGLS-LC100 is in the poorest agreement with any other dataset. The comparison and evaluation results are expected to provide a reference on which aspects and to what extent these land cover products may be consistent and guide the cropland data product selection for Northeast China. [ABSTRACT FROM AUTHOR]

During 2018 - 2020, in the infection field of Dobrudzha Agricultural Institute - General Toshevo, Bulgaria, 34 common winter wheat and 5 durum wheat cultivars were tested for resistance to leaf rust (P. triticina). The response of the common wheat cultivars to the P. triticina pathotypes predominant in this period was studied under controlled conditions, at seedling stage. The full set of pathotypes from the pathogen population identified during the respective year of study was taken out to the infection field to achieve a maximum rate of infection accumulation on the standard susceptible cultivar Michigan amber. The field parameters final disease severity (FSD), average coefficient of infection (ACI) and resistance rate were estimated. The type of resistance of the studied cultivars was determined. The results showed that at seedling stage most of the cultivars had compatible, susceptible reaction to the P. triticina pathotypes used in the study. Under the conditions of the infection field, 7.7 % of the cultivars exhibited high level of resistance (VR). Cultivar Zhana responded with stable resistance (R), and the cultivars with this type of resistance constituted 2.6%. Moderate resistance (MR) was registered in 5.1% of the tested cultivars. With very resistant to resistant reaction (VR - R) responded 18% of the cultivars. Resistant to moderately resistant (R - MR) was the reaction of 43.6% of the investigated cultivars, and 12.8% reacted within the range of high to moderate resistance (VR - MR). Some cultivars demonstrated variation of resistance within a wider range. The cultivars, which were within the range of highly resistant to moderately susceptible (VR - MS) constituted 5.1%, as well as those within the range moderately resistant to moderately susceptible (MR-MS). In some cultivars, such as Merilin, the level of resistance remained the same as in the previous years, regardless of the variations in the pathogen population, while in other cultivars, such as Karina, Enola and Lazarka, the resistance varied over years. All cultivars with stable resistance under the conditions of the infection field (from high to moderate), can be used in the breeding programs as parental components for the development of varieties resistant to leaf rust. [ABSTRACT FROM AUTHOR]

Crop domestication has led to the development of distinct trait syndromes, a series of constrained plant trait trade‐offs to maximize yield in high‐input agricultural environments, and potentially constrained trait plasticity. Yet, with the ongoing transition to organic and diversified agroecosystems, which create more heterogeneous nutrient availability, this constrained plasticity, especially in root functional traits, may be undesirable for nutrient acquisition. Such agricultural systems require a nuanced understanding of the soil‐crop continuum under organic amendments and with intercropping, and the role crop genetic resources play in governing nutrient management and design. In this study, we use a functional traits lens to determine if crops with a range of domestication histories express different functional trait plasticity and how this expression changes with soil amendments and intercropping. We utilize a common garden experiment including five wheat (Triticum aestivum) varietals with a range of domestication histories planted in a factorial combination with amendment type (organic and inorganic) and cropping design (monoculture or intercropped with soybean). We use bivariate, multivariate and trait space analyses to quantify trait variation and plasticity in five leaf and five root functional traits. Almost all leaf and root traits varied among varieties. Yet, amendment type was nearly inconsequential for explaining trait expression across varieties. However, intercropping was linked to significant differences in root acquisitive strategies, regardless of the varietals' distinct history. Our findings show substantial leaf and root trait plasticity, with roots expressing greater trait space occupation with domestication, but also the strong role of management in crop trait expression. We underscore the utility of a functional trait‐based approach to understand plant–soil dynamics with organic amendments, as well as the role of crop genetic histories in the successful transition to low‐input and diversified agroecosystems. [ABSTRACT FROM AUTHOR]

In a field experiment, composted coffee waste (CW) was used as soil amendment at three different rates (2%, 4%, and 8%) in plots cultivated with wheat; the effects on the soil nematode community and plant growth were studied. By sampling twice, i.e., three and six months after the application of treatments (3MAA and 6MAA), the duration of these effects was also evaluated. Treatment using composted coffee waste (CW) led to an increased abundance of all soil nematodes, especially of bacterivores and fungivores, probably via a bottom-up effect of CW on the soil community. The most-affected genera were the enrichment opportunists Panagrolaimus and Rhabditis, which increased after CW addition in a dosage-dependent way at 3MAA, while at 6MAA they were replaced by general opportunists, mainly bacterivorous and fungivorous genera; a nematotoxic effect of CW was also observed in the 6MAA condition. The nematode indices and the metabolic footprint indicated an enriched and vigorous soil three months after CW addition and a lower enrichment status of the soil together with a higher fungal participation in the decomposition pathway six months after treatments. However, in the 6 MAA condition, the soil nutrient values were higher in the CW-treated plots. None of our treatments inhibited or enhanced plant growth. [ABSTRACT FROM AUTHOR]

Wheat (Triticum aestivum L.) is a vital cereal crop for food security in Pakistan. In Zn-deficient soils, its productivity and quality suffer, affecting grain yield, Zn bioavailability, and nutrition, which can lead to malnutrition. Field experiments were conducted using factorial randomized block design at the Agricultural Research Institute (ARI) Tarnab, Peshawar, Pakistan to evaluate the impact of wheat genotypes (G1-TRB-72-311 synthetic hexaploid, G2-TRB-89-348 advanced line, and G3-Pirsabak-19-approved variety), Zn application methods (AM1: no Zn application, AM2: seed priming with 0.5% Zn, AM3: soil application of 10 kg ha−1 Zn, and AM4: foliar application of 0.5% Zn), and the experiment also explored the use of ZSB (BF1: with bacteria, BF0: without bacteria) to cope with Zn deficiency. The study revealed significant impacts on wheat's Zn content, uptake, and nutrient efficiency, arising from genotypes variance, Zn application approaches, and ZSB. TRB-72-311 synthetic hexaploid genotype with 0.5% foliar Zn and ZSB excelled, enhancing grain (17.8%) and straw Zn (23.1%), increasing total Zn uptake (55.0%), reducing grain phytic acid (11.7%), and boosting Zn-related efficiencies in wheat. These results prompt further discussion regarding the potential implications for agricultural practices. In conclusion, utilizing the TRB-72-311 genotype with 0.5% foliar Zn application and ZSB enhances wheat's Zn content, uptake, grain quality, and addresses malnutrition. [ABSTRACT FROM AUTHOR]

Accurate estimation and regular monitoring of soil moisture is very important for many agricultural, hydrological, or climatological applications. Our objective was to evaluate potential contributions of polarimetry to soil moisture estimation during crop growing cycles using RADARSAT-2 C-band images. The research focused on wheat field data collected during Soil Moisture Active Passive Validation Experiment (SMAPVEX12) conducted in 2012 in Manitoba (Canada). A sensitivity analysis was performed to select the most relevant non-polarimetric and polarimetric variables extracted from RADARSAT-2, and statistical models were developed to estimate soil moisture. In fine, three models were developed and validated: a non-polarimetric model based on cross-polarized backscattering coefficient σ H V 0 ; a polarimetric mixed model using six polarimetric and non-polarimetric retained variables after the sensitivity analysis; and a simplified polarimetric mixed model considering only the phase difference ( ϕ H H − V V ) and the co-polarized backscattering coefficient σ H H 0 . The validation reveals significant positive contributions of polarimetry. It shows that the non-polarimetric model has a much larger error (RMSE = 0.098 m3/m3) and explains only 19% of observed soil moisture variation compared to the polarimetric mixed model, which has an error of 0.087 m3/m3, with an explained variance of 44%. The simplified model has the lowest error (0.074 m3/m3) and explains 53.5% of soil moisture variation. [ABSTRACT FROM AUTHOR]