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The variations in temperature and rainfall patterns under climate change are threatening crop production systems, and optimizing fertilization practices is a prerequisite for sustainable cereal production. This two-year field study investigated the effects of eight treatments (T1: P60K60; T2: P60K60 + Nmin spring; T3: P60K60 + N40autumn + Nmin spring; T4: P60K60 + N60spring; T5: P60K60 + N100spring; T6: P60K60 + N40autumn + N60spring + Zn; T7: P60K60 + N60autumn + N80spring + Zn; and T8: P60K60 + N160spring + Zn) on the grain yield and quality of four divergent maize cultivars (NS-4023, NS-640, NS-6010 and NS-6030). The observations on climatic data showed substantial variations in monthly and cumulative rainfall only, which was 174 and 226 mm for 2011 and 2012, respectively, and much less than the historical cumulative rainfall of 339 mm. However, temperature during growth years showed little deviation from the historical data. The data showed that treatment and maize cultivar significantly influenced grain yield; however, grain yield remained lower in 2012 than in 2011 for each treatment and cultivar. Applying N as split doses in combination with Zn, resulted in higher grain yields than adding at once. However, the treatments and cultivars affected grain quality variables differently, including oil, thiol SH, phytate, inorganic P, soluble protein, starch, total phenol, protein, total sugars and tryptophan contents. Despite the pronounced difference in grain yields between 2011 and 2012 for each treatment and cultivar, grain quality did not always vary significantly between cultivars. Principal component analysis (PCA) revealed that the relationships between grain yield and grain quality varied significantly during 2011 and 2012. The changes in rainfall patterns at critical growth maize stages seemed to be a more important factor than temperature in regulating the response of maize cultivars in terms of grain yield and quality to various fertilization regimes in this study. [ABSTRACT FROM AUTHOR]

Fusarium wilt (FW) caused by Fusarium oxysporum f. sp. ciceri is a devastating disease of chickpea (Cicer arietinum). To identify promising resistant genotypes and genomic loci for FW resistance, a core set of 179 genotypes of chickpea was tested for FW reactions at the seedling and reproductive stages under field conditions and controlled conditions in the greenhouse. Our results revealed that at the seedling stage, most of the genotypes were resistant, whereas at the reproductive stage, most of the genotypes were susceptible. Genotyping using a 5OK Axiom® CicerSNP Array and trait data of FW together led to the identification of 26 significant (P 5 E-05) marker-trait associations (MTAs) for FW resistance. Among the 26 MTAs, 12 were identified using trait data recorded in the field (three at the seedling and nine at the reproductive stage), and 14 were identified using trait data recorded under controlled conditions in the greenhouse (six at the seedling and eight at the reproductive stage). The phenotypic variation explained by these MTAs varied from 11.75 to 15.86%, with an average of 13.77%. Five MTAs were classified as major, explaining more than 15% of the phenotypic variation for FW, and two were declared stable, being identified in two environments. One of the promising stable and major MTAs (Affx_123280060) detected in field conditions at the reproductive stage was also detected in greenhouse conditions at the seedling and reproductive stages. The stable and major (> 15% PVE) MTAs can be used in chickpea breeding programs. [ABSTRACT FROM AUTHOR]

Due to the increase in greenhouse gases from burning fossil fuels, there is increased attention on renewable energy sources from specialized crops. These crops should not compete with food security, and it is important to select plant resources which can produce methane-rich biogas efficiently. The most commonly used energy crops are planted and managed intensively with high inputs in productive land, and this negatively affects land use and sustainable use of resources. The main purposes of this study are to: (a) determine the best cropping system for optimal biogas and methane production from sole crops of winter pea, triticale and out and their mixtures at two different maturity stages (first stage: full-flowering stage of winter pea and beginning of milky stage of cereals; second stage: emergence of firsts pods for pea and milky/waxy stage of cereals); and (b) to develop and use a surface model to determine the best combinations of various mixtures that result in highest biogas and methane. The used pure or mixtures of pea, oat and triticale in two seed weight ratios (50%:50% and 75%:25%) produced different green mass, dry matter, solids, biogas and methane yields. The experiments showed that maximum green mass was produced by the mixture of pea and oat at the seed ratio 75%:25% and when crop was harvested at the full-flowering stage of winter pea and beginning of the milky stage of cereals. After quadratic model analyses, the combination ratios of the oat and triticale were, respectively, 30% and 8%, with a maximum green biomass yield of 61.48 t ha−1, while the corresponding values were 28% and 38%, with maximum solids yields of 25.64 t ha−1. As the model was set at 100 for all three independent variables (oat, triticale and pea), the pea should be at 62% (100-30-8) and 34% (100-28-38), respectively, for green mass and organic solids yields. The results of surface analysis and multivariate analysis of variance showed that the mixture of oat and triticale had great potentiality for biogas and methane yields. The optimal mixture of oat with triticale was 27~35% with 73~65% for producing biogas and (or) methane. [ABSTRACT FROM AUTHOR]

High-temperature stress (HT) over crop productivity is an important environmental factor demanding more attention as recent global warming trends are alarming and pose a potential threat to crop production. According to the Sixth IPCC report, future years will have longer warm seasons and frequent heat waves. Thus, the need arises to develop HT-tolerant genotypes that can be used to breed high-yielding crops. Several physiological, biochemical, and molecular alterations are orchestrated in providing HT tolerance to a genotype. One mechanism to counter HT is overcoming high-temperature-induced membrane superfluidity and structural disorganizations. Several HT lipidomic studies on different genotypes have indicated the potential involvement of membrane lipid remodelling in providing HT tolerance. Advances in high-throughput analytical techniques such as tandem mass spectrometry have paved the way for large-scale identification and quantification of the enormously diverse lipid molecules in a single run. Physiological trait-based breeding has been employed so far to identify and select HT tolerant genotypes but has several disadvantages, such as the genotype-phenotype gap affecting the efficiency of identifying the underlying genetic association. Tolerant genotypes maintain a high photosynthetic rate, stable membranes, and membrane-associated mechanisms. In this context, studying the HT-induced membrane lipid remodelling, resultant of several up-/down-regulations of genes and post-translational modifications, will aid in identifying potential lipid biomarkers for HT tolerance/susceptibility. The identified lipid biomarkers (LIPIDOTYPE) can thus be considered an intermediate phenotype, bridging the gap between genotype–phenotype (genotype–LIPIDOTYPE–phenotype). Recent works integrating metabolomics with quantitative genetic studies such as GWAS (mGWAS) have provided close associations between genotype, metabolites, and stress-tolerant phenotypes. This review has been sculpted to provide a potential workflow that combines MS-based lipidomics and the robust GWAS (lipidomics assisted GWAS-lGWAS) to identify membrane lipid remodelling related genes and associations which can be used to develop HS tolerant genotypes with enhanced membrane thermostability (MTS) and heat stable photosynthesis (HP). [ABSTRACT FROM AUTHOR]

Crop rotation is known as an eco-friendlier approach, as provides diversification in crop management systems, modifies intensive pressure on the agricultural ecosystem, utilizes various soil horizons, and prevents the establishment of specific pests and weeds. We set out here a study on the farms that have been managed over 50 years of specific continuous crop management programs. The experimental treatments were in a different management system: monoculture of maize, winter wheat, and soybean, 2-year crop rotation (winter wheat–maize) with and without chemical fertilizer, and 3-year crop rotation (winter wheat–soybean–maize) with and without chemical fertilizer and manure. We took soil samples six times from 2014 to 2017 prior to sowing and after harvesting each year. Weed seeds were extracted from soils and identified and counted by species. We, upon the data of a long term experiment of crop rotation, could conclude that crop rotations with more crops in the sequence are significantly effective in maintaining weed populations, a low-input crop production could reach a constant low population below an important damaging density, and therefore will be a more sustainable crop production while chemical fertilizers would change the soil's chemical and structure and imbalance the plant population diversity and manures with high weed seed infestations have the potential to totally eradicate crop rotation effects, Therefore, clean manures or compost are highly recommended. [ABSTRACT FROM AUTHOR]

Root traits can be exploited to increase the physiological efficiency of crop water use under drought. Root length, root hairs, root branching, root diameter, and root proliferation rate are genetically defined traits that can help to improve the water productivity potential of crops. Recently, high-throughput phenotyping techniques/platforms have been used to screen the germplasm of major cool-season grain legumes for root traits and their impact on different physiological processes, including nutrient uptake and yield potential. Advances in omics approaches have led to the dissection of genomic, proteomic, and metabolomic structures of these traits. This knowledge facilitates breeders to improve the water productivity and nutrient uptake of cultivars under limited soil moisture conditions in major cool-season grain legumes that usually face terminal drought. This review discusses the advances in root traits and their potential for developing drought-tolerant cultivars in cool-season grain legumes. [ABSTRACT FROM AUTHOR]

The adverse effects of mounting environmental challenges, including extreme temperatures, threaten the global food supply due to their impact on plant growth and productivity. Temperature extremes disrupt plant genetics, leading to significant growth issues and eventually damaging phenotypes. Plants have developed complex signaling networks to respond and tolerate temperature stimuli, including genetic, physiological, biochemical, and molecular adaptations. In recent decades, omics tools and other molecular strategies have rapidly advanced, offering crucial insights and a wealth of information about how plants respond and adapt to stress. This review explores the potential of an integrated omics‐driven approach to understanding how plants adapt and tolerate extreme temperatures. By leveraging cutting‐edge omics methods, including genomics, transcriptomics, proteomics, metabolomics, miRNAomics, epigenomics, phenomics, and ionomics, alongside the power of machine learning and speed breeding data, we can revolutionize plant breeding practices. These advanced techniques offer a promising pathway to developing climate‐proof plant varieties that can withstand temperature fluctuations, addressing the increasing global demand for high‐quality food in the face of a changing climate. [ABSTRACT FROM AUTHOR]

Background: Yellow or stripe rust, caused by the fungus Puccinia striiformis f. sp. tritici (Pst) is an important disease of wheat that threatens wheat production. Since developing resistant cultivars offers a viable solution for disease management, it is essential to understand the genetic basis of stripe rust resistance. In recent years, meta-QTL analysis of identified QTLs has gained popularity as a way to dissect the genetic architecture underpinning quantitative traits, including disease resistance. Results: Systematic meta-QTL analysis involving 505 QTLs from 101 linkage-based interval mapping studies was conducted for stripe rust resistance in wheat. For this purpose, publicly available high-quality genetic maps were used to create a consensus linkage map involving 138,574 markers. This map was used to project the QTLs and conduct meta-QTL analysis. A total of 67 important meta-QTLs (MQTLs) were identified which were refined to 29 high-confidence MQTLs. The confidence interval (CI) of MQTLs ranged from 0 to 11.68 cM with a mean of 1.97 cM. The mean physical CI of MQTLs was 24.01 Mb, ranging from 0.0749 to 216.23 Mb per MQTL. As many as 44 MQTLs colocalized with marker–trait associations or SNP peaks associated with stripe rust resistance in wheat. Some MQTLs also included the following major genes- Yr5, Yr7, Yr16, Yr26, Yr30, Yr43, Yr44, Yr64, YrCH52, and YrH52. Candidate gene mining in high-confidence MQTLs identified 1,562 gene models. Examining these gene models for differential expressions yielded 123 differentially expressed genes, including the 59 most promising CGs. We also studied how these genes were expressed in wheat tissues at different phases of development. Conclusion: The most promising MQTLs identified in this study may facilitate marker-assisted breeding for stripe rust resistance in wheat. Information on markers flanking the MQTLs can be utilized in genomic selection models to increase the prediction accuracy for stripe rust resistance. The candidate genes identified can also be utilized for enhancing the wheat resistance against stripe rust after in vivo confirmation/validation using one or more of the following methods: gene cloning, reverse genetic methods, and omics approaches. [ABSTRACT FROM AUTHOR]

Salinity is one of the major abiotic factors that limit the growth and productivity of plants. Foliar application of plant growth regulators (PGRs) may help plants ameliorate the negative impacts of salinity. Thus, a field experiment was conducted at the Botanical Garden University of Balochistan, Quetta, to explore the potential role of PGRs, i.e., moringa leaf extract (MLE; 10%), proline (PRO; 1 µM), salicylic acid (SA; 250 µM), and thiourea (TU; 10 mM) in ameliorating the impacts of salinity (120 mM) on Plantago ovata, an important medicinal plant. Salinity hampered plant photosynthetic pigments and metabolites but elevated oxidative parameters. However, foliar application of PGRs enhanced photosynthetic pigments, including Chl b (21.11%), carotenoids (57.87%) except Chl a, activated the defense mechanisms by restoring and enhancing the metabolites, i.e., soluble sugars (49.68%), soluble phenolics (33.34%), and proline (31.47%), significantly under salinity stress. Furthermore, foliar supplementation of PGRs under salt stress led to a decrease of about 43.02% and 43.27% in hydrogen peroxide and malondialdehyde content, respectively. Thus, PGRs can be recommended for improved photosynthetic efficiency and metabolite content that can help to get better yield under salt stress, with the best and most effective treatments being those of PRO and MLE to predominately ameliorate the harsh impacts of salinity. [ABSTRACT FROM AUTHOR]

Domestication of orphan crops could be explored by editing their genomes. Genome editing has a lot of promise for enhancing agricultural output, and there is a lot of interest in furthering breeding in orphan crops, which are sometimes plagued with unwanted traits that resemble wild cousins. Consequently, applying model crop knowledge to orphan crops allows for the rapid generation of targeted allelic diversity and innovative breeding germplasm. We explain how plant breeders could employ genome editing as a novel platform to accelerate the domestication of semi-domesticated or wild plants, resulting in a more diversified base for future food and fodder supplies. This review emphasizes both the practicality of the strategy and the need to invest in research that advances our understanding of plant genomes, genes, and cellular systems. Planting more of these abandoned orphan crops could help alleviate food scarcities in the challenge of future climate crises. [ABSTRACT FROM AUTHOR]

Crop nitrogen (N) fertilization diagnoses via the N nutrition index (NNI)-yield relationship have been tested for several crop species, but a cross-species comparison of that relationship has not been performed yet. This study aimed to perform a cross-species comparison of the relationship between NNI and yield with emphasis on the yield sensitivity to N deficiency, slope of the models. Additionally, we conducted an evaluation to determine the best NNI sampling moment to predict relative yield, with focus on major grain crops. Based on a recently published global dataset to parametrize critical dilution curves , we calculated integrated NNI, instantaneous NNI, relative yield, and relative shoot biomass for annual ryegrass, tall fescue, maize, potato, rice, and wheat. We obtained 238 observations to fit integrated NNI-relative yield linear mixed-effects models and 1606 observations to fit instantaneous NNI-relative yield models. Subsequently, we performed a sensitivity analysis to determine the best NNI sampling moment to predict relative yield, with focus on major grain crops (maize, rice, and wheat). Our results show that there was low inter-species variation of sensitivity to N deficiency, i.e., the slope of the relationship between relative yield and integrated NNI. For grain crops, instantaneous NNI around anthesis demonstrated a better predictive capability for relative yield, outperforming other vegetative stages. This finding contributed to improving the understanding of the association between relative yield and NNI with implications for breeding programs, nutrient management practices, and crop modelling. Most importantly, this study is a contribution to improving the N nutrition diagnosis for several crop species, by using an integral, comparative approach. • The relationship between relative yield and integrated NNI was similar across species. • The slope of relative yield-integrated NNI shown limited variation across species. • The relative yield-integrated NNI slopes of maize and potato were the highest. • For grain crops, NNI around anthesis was the strongest predictor of relative yield. [ABSTRACT FROM AUTHOR]

Background and aims: The production of maize (Zea mays L.) is restricted by various edaphic stresses, including drought and low-fertility soil. Searching for genotypes with optimal root traits is a promising practice when breeding for improved adaptation to abiotic stress and resource-use efficiency. Methods: Using an established semi-hydroponic phenotyping technique, we assessed root trait variability across 174 maize genotypes including 113 cultivars and 11 breeding lines from northern China and 50 Serbian hybrids. Results: Large variation in root architecture traits was observed among the tested genotypes 28 days after transplanting. Sixteen of the characterized traits had coefficients of variation greater than 0.25, especially local root traits. Root traits including total root length, root length at various depths, total shoot mass and nodal root angle, should be considered in maize breeding programs. Genotype ranking data based on a composite score was used to assist in the selection of genotypes with contrasting root architecture traits for future studies. Conclusion: This study identified genotypic variation in root architecture traits in a diverse genotypes of maize. The outcomes of this study could form a basis for maize breeding programs aimed at producing maize cultivars for improved adaptation to target environments. [ABSTRACT FROM AUTHOR]

The aim of this study was to assess the changes in soil organic carbon (SOC) stock in relation to the carbon (C) input from nine wheat-based cropping systems and untilled grass. The SOC pool ranged from 32.1 to 49.4 Mg ha−1at 0–20 cm and from 94 to 171 Mg ha−1at 0–100 cm for the arable soil, while in untilled grassland, it was higher (54 and 185 Mg C ha−1, respectively). SOC stock was observed to be lower at the unfertilized 2-year rotation and higher at the 4-year rotation with manure and mineral fertilization. The study showed a winter wheat yield decrease of 176.8 kg ha−1for a 1- Mg ha−1SOC stock change in the 0–20-cm soil depth. The estimated C input for SOC stock maintenance was from 266 to 340 g C m−2 year−1for winter wheat and rotations, respectively. Additional C input did not increase the SOC pool, suggesting that arable plots had a limited ability to increase SOC. These results provide guidance for the selection of management practices to improve C sequestration. [ABSTRACT FROM PUBLISHER]

Cool season grain legumes occupy an important place among the agricultural crops and essentially provide multiple benefits including food supply, nutrition security, soil fertility improvement and revenue for farmers all over the world. However, owing to climate change, the average temperature is steadily rising, which negatively affects crop performance and limits their yield. Terminal heat stress that mainly occurred during grain development phases severely harms grain quality and weight in legumes adapted to the cool season, such as lentils, faba beans, chickpeas, field peas, etc. Although, traditional breeding approaches with advanced screening procedures have been employed to identify heat tolerant legume cultivars. Unfortunately, traditional breeding pipelines alone are no longer enough to meet global demands. Genomics-assisted interventions including new-generation sequencing technologies and genotyping platforms have facilitated the development of high-resolution molecular maps, QTL/gene discovery and marker-assisted introgression, thereby improving the efficiency in legumes breeding to develop stress-resilient varieties. Based on the current scenario, we attempted to review the intervention of genomics to decipher different components of tolerance to heat stress and future possibilities of using newly developed genomics-based interventions in cool season adapted grain legumes. [ABSTRACT FROM AUTHOR]

The topic of N wheat nutrition was prevalent during the last decades of the 20th century for many reasons such as energy crises, profitability of small grain production, and ecosystem protection and preservation. The objective of this study was to determine the interrelationships between wheat (Triticum aestivum L.) grain N content and other indicators of N nutrition efficiency to better understand the N nutrition process in wheat plants. The experiment included 30 wheat cultivars and experimental lines from Serbia. Plant samples of each genotype were taken at anthesis and maturity. The following parameters related to N accumulation and translocation within the wheat plant were calculated: N content (at anthesis, grain, straw, and total at maturity), N harvest index (NHI), N reutilization (N reU), and N lost (-) or gained (N post-anthesis). Our results showed that N content in the aboveground part of the plant expressed very strong direct positive effects on N yield (phenotypic coefficient 3.78** to 9.34** and genotypic coefficient 1.43** to 2.32**), while its indirect effects varied. The influence of independent variables on grain N content has been changing from year to year in a negative way. Total N accumulation (N total) had the highest negative direct effect in the first year of the study (phenotypic coefficient -2.11**), N total in the second (phenotypic coefficient -2.78**), and N reutilization in the third (phenotypic coefficient -8.49**). Genotypic coefficients indicate that the most frequent strong direct negative effect was N reutilization (-0.47** and -0.99** in the first 2 yr of research, respectively). Nitrogen reutilization and its current assimilation are very important and related to grain N supply processes. Their interaction leads to the conclusion that forming N yield is a very complex mechanism and, as a result, grain yield and quality. The abovementioned parameters could be considered as important criteria in wheat breeding to improve production efficiency and reduce adverse impacts of N fertilizers on the ecosystem. [ABSTRACT FROM AUTHOR]

Sorghum is one of the staple crops for millions of people in Sub-Saharan Africa (SSA) and South Asia (SA). The future climate in these sorghum production regions is likely to have unexpected short or long episodes of drought and/or high temperature (HT), which can cause significant yield losses. Therefore, to achieve food and nutritional security, drought and HT stress tolerance ability in sorghum must be genetically improved. Drought tolerance mechanism, stay green, and grain yield under stress has been widely studied. However, novel traits associated with drought (restricted transpiration and root architecture) need to be explored and utilized in breeding. In sorghum, knowledge on the traits associated with HT tolerance is limited. Heat shock transcription factors, dehydrins, and genes associated with hormones such as auxin, ethylene, and abscisic acid and compatible solutes are involved in drought stress modulation. In contrast, our understanding of HT tolerance at the omic level is limited and needs attention. Breeding programs have exploited limited traits with narrow genetic and genomic resources to develop drought or heat tolerant lines. Reproductive stages of sorghum are relatively more sensitive to stress compared to vegetative stages. Therefore, breeding should incorporate appropriate pre-flowering and post-flowering tolerance in a broad genetic base population and in heterotic hybrid breeding pipelines. Currently, more than 240 QTLs are reported for drought tolerance-associated traits in sorghum prospecting discovery of trait markers. Identifying traits and better understanding of physiological and genetic mechanisms and quantification of genetic variability for these traits may enhance HT tolerance. Drought and HT tolerance can be improved by better understanding mechanisms associated with tolerance and screening large germplasm collections to identify tolerant lines and incorporation of those traits into elite breeding lines. Systems approaches help in identifying the best donors of tolerance to be incorporated in the SSA and SA sorghum breeding programs. Integrated breeding with use of high-throughput precision phenomics and genomics can deliver a range of drought and HT tolerant genotypes that can improve yield and resilience of sorghum under drought and HT stresses. [ABSTRACT FROM AUTHOR]