Staple Crops Research Articles

Conventional and Molecular Improvement of Maize for Drought Tolerance: Research Review

Maize (Zea mays L.) is an important staple crop for food, feed, and industry globally. Despite the importance of maize as a principal food crop in developing countries, drought is a major constraint that affects maize production, particularly in Sub-Saharan Africa, where maize is grown under rainfed conditions. Plant breeders have been striving to improve and develop drought-tolerant crops. Nevertheless, these efforts still cannot meet the demand for food security due to fast population growth and climatic change. Conventional maize breeding for drought tolerance follows a diverse approach that includes recurrent selection, backcrossing, pedigree breeding, and subsequently evaluating inbred lines and hybrids at optimum conditions, a managed screening site, and random stress across multiple environments. Molecular markers were used to select donor parents with drought-adaptive alleles and then integrated into elite maize lines to create a new population of drought-tolerant inbred lines.

Iron, Zinc and Total Phenolic Content in Cooked Biofortified NUA 45 and Gloria Sugar Beans: The Case of Zimbabwe

Biofortification involves breeding of staple crops that are micronutrient-dense and high yielding for example iron-biofortified beans. The biofortification of crops has been found to be cost effective and feasible to fight micronutrient deficiencies. The aim of the study was to determine the iron, zinc and total phenolic composition for the biofortified NUA 45 and Gloria sugar beans in raw as well as cooked samples with and without previous soaking. Determination of iron and zinc content in the raw, cooked bean grain samples with and without soaking was carried out by Inductively Coupled Plasma (ICP) Optical Emission Spectrometry whereas the determination of Total Phenolic Content was done using the Folin-Ciocalteau colorimetric method. The highest zinc concentration (0.295ppm) was found in raw Gloria sugar beans whilst the raw NUA 45 sugar beans had the highest iron content (0.755ppm) and total phenolic composition (352.8mg/100g). For the cooked bean samples Gloria sugar beans had the highest zinc concentration (0.247ppm) cooked after soaking. NUA 45 sugar beans had no significant difference on the zinc content after being cooked with and without soaking. Amongst the cooked samples the biofortified NUA 45 sugar beans cooked after soaking had the highest iron content (0.373ppm) as well as the highest total phenolic content in the beans cooked without soaking (200.5mg/100g). Biofortified NUA 45 and Gloria sugar beans proved to be good sources of iron, zinc and phenolic compounds. However, cooking with and without soaking diminished the iron, zinc and the total phenolic composition of the cooked NUA 45 and Gloria sugar beans.

Unraveling the Relationship between Soil Nutrients and Maize Leaf Disease Occurrences in Mopani District Municipality, Limpopo Province, South Africa

Maize is a staple crop important for food security that millions globally depend upon as an energy source, primarily due to its high starch and fat content. For growth and disease resistance, maize production requires a balanced intake of essential nutrients, including nitrogen (N), phosphorus (P) and potassium (K). This study investigated the relationship between soil nutrient levels and maize disease occurrences in the Mopani District Municipality, Limpopo Province, South Africa. Soil and maize leaves were collected using a systematic sampling approach. Grids of 10 × 10 m were created, covering a maize field. Forty soil samples were collected a day before the planting date and sent to the laboratory for analysis of N, P and K. During the tasseling stage of the maize plant, 40 maize leaf samples were collected and sent to the laboratory for disease identification. Maize leaves were classified as healthy, southern corn leaf blight (Bipolaris maydis), northern corn leaf blight (Exserohilum turcicum), maize streak disease (Maize streak virus), nitrogen-deficient or phosphorus-deficient. Generalized Linear Models (GLMs) with a corrected Akaike Information Criterion (AICc) showed a significant relationship between low soil nutrient levels of N, P and K and maize disease occurrence (p < 0.0001). The interaction of the N*P*K model had the lowest AIC value (AICc = 28.53), indicating the necessity of considering synergistic effects in maize disease management. All the model performances had a delta AICc = 0. These findings highlight the significance of comprehensive soil management strategies in enhancing the disease resistance, well-being and yields of maize crops.

Localized nitrogen management strategies can halve fertilizer use in Chinese staple crop production.

Nitrogen (N) management is the key to achieving food security and environmental sustainability. Here we analyse N flows using a localized N management model for wheat, maize and rice in 1,690 Chinese counties, with a breakdown of multiple reactive N (Nr) loss pathways. Results show that the total N input for producing these three staple crops in China was 22.2 Tg N in 2015, of which 7.4 Tg N was harvested as grain N and 4.0 Tg N was Nr losses in the forms of NH3 (47%), NOx (10%), N2O (3%), and leaching and runoff (40%). By assuming a production level equivalent to that of the top 10% of counties with the highest N use efficiency and yields surpassing the regional average, we reveal the possibility of achieving national staple crop production targets while improving net ecosystem economic benefit in 2050 through a 49% reduction (10.4 Tg N) in synthetic N fertilizer inputs and a 52% decrease (2.9 Tg N) in Nr losses.

Biofortification-enabled strategies to mitigate the challenges of malnutrition

Scientific and technological intervention have significantly contributed to global food security, especially due to the enabling technologies during the so-called Green-revolution era. However, ending all kinds of hunger poses a daunting challenge to fulfill the food and nutritional demands of the ever-growing human population. Hidden hunger also referred as malnutrition is very common problem in the developing countries in Sub-Sahara Africa and South Asia. Consistent with malnutrition, an associated challenge is to improve the health-benefits of food crops to overcome the problems of obesity, type II diabetes, cardiovascular diseases, and some types of cancer by developing functional foods. Biofortification of food crops, especially staple crops like rice, wheat and maize by using innovative genomics and breeding technologies should be given priority to overcome this formidable challenge.

Recent advances of CRISPR-based genome editing for enhancing staple crops.

An increasing population, climate change, and diminishing natural resources present severe threats to global food security, with traditional breeding and genetic engineering methods often falling short in addressing these rapidly evolving challenges. CRISPR/Cas systems have emerged as revolutionary tools for precise genetic modifications in crops, offering significant advancements in resilience, yield, and nutritional value, particularly in staple crops like rice and maize. This review highlights the transformative potential of CRISPR/Cas technology, emphasizing recent innovations such as prime and base editing, and the development of novel CRISPR-associated proteins, which have significantly improved the specificity, efficiency, and scope of genome editing in agriculture. These advancements enable targeted genetic modifications that enhance tolerance to abiotic stresses as well as biotic stresses. Additionally, CRISPR/Cas plays a crucial role in improving crop yield and quality by enhancing photosynthetic efficiency, nutrient uptake, and resistance to lodging, while also improving taste, texture, shelf life, and nutritional content through biofortification. Despite challenges such as off-target effects, the need for more efficient delivery methods, and ethical and regulatory concerns, the review underscores the importance of CRISPR/Cas in addressing global food security and sustainability challenges. It calls for continued research and integration of CRISPR with other emerging technologies like nanotechnology, synthetic biology, and machine learning to fully realize its potential in developing resilient, productive, and sustainable agricultural systems.

Evaluating the effect of organic NPK granules on yield, nutrient uptake, post-harvest soil fertility and soil microbial population in rice (Oryza sativa L.)

Rice is the most important and staple food crop for more than two third of population of India. India is the second largest rice producing country in the world after China. Although, rice planted area in India is 40 per cent higher than in China, Indian rice production is 30 percent below Chinese production because of lower yields. Among several constraints of production, nutrient management plays a key role in realizing sustainable yield from any given cultivation practices. Integrated nutrient management system plays a vital role in balancing the soil fertility and plant nutrient supply to an optimum level through the judicious and efficient use of chemical fertilizers, green manure, FYM and biofertilizers leading to an eco-friendly approach and economically viable solution for this problem. Continuous integrated use of organic manures with chemical fertilizers would be quite promising in assessing the sustainability of a cropping system vis-à-vis monitoring the soil properties. To investigate further, a field experiment was conducted at the Experimental Farm, Department of Agronomy, Annamalai University, Annamalai Nagar, Cuddalore district of Tamil Nadu from June to September 2023 with a key objective of evaluating the effect of combined application of graded levels of conventional fertilizers along with organic NPK granules in lowland rice. The experiment was laid out in randomized block design with seven treatments comprised of different levels of conventional fertilizers along with organic NPK granules. Among the nutrient management evaluated, all the yield attributes of lowland rice viz., grain yield, straw yield, uptake of nutrients and post-harvest soil available nutrients were significantly influenced by the application of 70% NPK through synthetic fertilizers and 30% NPK through organic granules. Combining conventional fertilizers along with organic NPK granules improved nitrogen use efficiency via metabolite production, enzyme activity stimulation, and microbial rhizosphere interactions significantly enhancing the yield attributes and yield.

Analysis of Component of Genetic Variance, Combining Ability, Gene Action and Heterotic Response in Rice (Oryza sativa. L)

Rice (Oryza sativa L.) is an important staple crop, particularly in Asia, where it feeds more than half the world's population. The analysis of variance (ANOVA) for nine traits in a rice breeding experiment with seven lines, three testers, 24 F1 hybrids, and two checks indicated significant variations between treatments, showing significant genetic diversity. General combining ability (GCA) effects revealed that line MTU 1010 and tester NDR 2026 had favorable GCA effects on grain yield per plant, but NDR 2064 and Barani Deep had negative effects. Three crosses, showed considerable favorable benefits on grain yield due to specific combining ability (SCA). Heterosis analysis identified promising crosses, including Gopal Bhag × Prakhar and NDR-2064 × NDR-2026, that demonstrated considerable positive heterosis above the parent and standard varieties Shushk Samrat and Ashwani. These findings emphasize the possibility of specific crosses to improve grain production in rice breeding efforts.

Comparative analysis of leaf area index and maize yield estimation assimilating remote sensing and DSSAT crop simulation model

Maize is a global staple crop, impacting food security, economic development, and agricultural sustainability. This study investigates the integration of Sentinel-1A Synthetic Aperture Radar (SAR) data with the DSSAT CERES-Maize crop simulation model to estimate Leaf Area Index (LAI) and rabi maize yield in Belagavi district, Karnataka. Field data, including LAI, days to anthesis, silking, grain filling, and farmers' field practices, were collected for model calibration and validation, supplemented by crop-cutting experiments (CCE) to determine actual yields. The study revealed strong correlations between LAI values obtained from remote sensing (RS) and field observations, with RS-derived LAI showing an average agreement of approximately 96.07% compared to field measurements. The DSSAT model exhibited slightly better performance, averaging 97.09%. Statistical analysis for LAI showed an R² value of 0.853 for RS and 0.864 for DSSAT, indicating strong correlations with observed LAI values. For maize yield estimation, the DSSAT model demonstrated higher accuracy with an average yield of 8129 kg/ha, compared to RS-derived yield averages of 7533.9 kg/ha and CCE yield averages of 8096.6 kg/ha. The average concordance between DSSAT and CCE yields was 94.19%, while RS and CCE yields had an average concordance of 92.29%. Statistical analyses revealed coefficients of determination of 0.854 for DSSAT-CCE and 0.867 for RS-CCE comparisons. The study underscores the value of combining RS data with DSSAT for comprehensive and accurate crop yield forecasting, highlighting the potential for improved agricultural assessments and decision-making.

Intensifying droughts render more Sahel drylands unsuitable for cultivation

Two-fifth of the world's population will be confronted by dire land and water shortage for food production by 2050. Here we provide nuanced insights into the Sahel dryland dynamics and rationale behind its underperforming croplands amid climate extremes. We develop a gridded multi-criteria drought index for the growing season (June-October) and analyse its spatial and temporal degree of uniformity to designate the drought, climate and cultivable zones. Evidence is drawn from Sahelian Sudan, representing 1.03 million km2 of the African Sahel, during 1940–2020. Results show that cultivation of marginal lands has persisted apace. The peak areas of these marginal lands explain ∼50 % of the variations in crop yield, considering the two staple crops, sorghum and millet. Furthermore, the low yields mismatch the steadily growing planted areas of these crops. Compared to wet conditions, droughts expand (shrink) the median size of hyper-arid (arid) area by 466 % (46 %), limiting farming opportunities for 3.5–35.8 % of the croplands. The northernmost borderline of the arid zone determines the rainfed suitability, but potentially cultivable arid areas require contingency risk-reduction plans. Conversely, semi-arid and dry sub-humid zones reveal areas endowed with uniform climate. Skillful climate forecasting should thus guide policymaking towards sustainable agriculture therein. The paper suggests paths towards more effective agricultural policy interventions. Agricultural production entails the Sahel drought being defined in terms of agricultural impacts instead of meteorological conditions. Land use planners and inhabitants must relieve the plight of misconceiving and overlooking the fact of intrinsic interannual rainfall variability. Determining what a dangerous drought is for the Sahel agriculture sector or system is crucial. Sahel farming systems should opt for highly flexible agricultural practices based on the above-identified cultivable areas.

Rice yield prediction through integration of biophysical parameters with SAR and optical remote sensing data using machine learning models

In an era marked by growing global population and climate variability, ensuring food security has become a paramount concern. Rice, being a staple crop for billions of people, requires accurate and timely yield prediction to ensure global food security. This study was undertaken across two rice crop seasons in the Udham Singh Nagar district of Uttarakhand state to predict rice yield at 45, 60 and 90 days after transplanting (DAT) through machine learning (ML) models, utilizing a combination of optical and Synthetic Aperture Radar (SAR) data in conjunction with crop biophysical parameters. Results revealed that the ML models were able to provide relatively accurate early yield estimates. For summer rice, eXtreme gradient boosting (XGB) was the best-performing model at all three stages (45, 60, and 90 DAT), while for kharif rice, the best-performing models at 45, 60, and 90 DAT were XGB, Neural network (NNET), and Cubist, respectively. The combined ranking of ML models showed that prediction accuracy improved as the prediction date approaches harvest, and the best prediction of yield was observed at 90 DAT for both summer and kharif rice. Overall rankings indicate that for summer rice, the top three models were XGB, NNET, and Support vector regression, while for kharif rice, these were Cubist, NNET, and Random Forest, respectively. The findings of this study offer valuable insights into the potential of the combined use of remote sensing and biophysical parameters using ML models, which enhances food security planning and resource management by enabling more informed decision-making by stakeholders such as farmers, policy planners as well as researchers.

A Farmer-Centric Cost–Benefit Analysis of Climate-Smart Agriculture in the Gandaki River Basin of Nepal

Climate-smart agriculture (CSA) is a climate-resilient practice that stands out globally as an important practice through which we can deal with emerging challenges through adaptation and mitigation to increase crop productivity and resilience. Despite its significance, a comprehensive cost–benefit analysis of the adoption of these practices has not yet been carried out. This study aims to bridge the knowledge gap between the cost and effectiveness of CSA practices adopted by small-scale farmers in growing rice, wheat and maize, the most staple crops in the Gandaki River Basin of Nepal. In this study, net present value (NPV), internal rate of return (IRR), benefit–cost (BC) ratio, net benefit investment (NK) ratio and payback period, along with the value of externalities (social and environmental), were employed to assess the profitability of CSA practices. The findings indicate that almost all the CSA practices analyzed were profitable, with the exception of solar water management in maize with very low IRR (6%) and a longer payback period. The outcome of this study offers valuable insights for farmers in choosing profitable CSA technology and for policy makers in promoting better CSA technology, upscaling CSA practices, and formulating new agricultural policies and programs in the context of the changing climate.

Characterization of active transposable elements and their new insertions in tuber propagated greater yam (Dioscorea alata)

BackgroundGreater yam is a key staple crop grown in tropical and subtropical regions, while its asexual propagation mode had led to non-flowering mutations. How transposable elements contribute to its genetic variations is rarely analyzed. We used transcriptome and whole genome sequencing data to identify active transposable elements (TEs) and genetic variation caused by these active TEs. Our aim was to shed light on which TEs would lead to its intraspecies variation.ResultsAnnotation of de novo assembly transcripts indicated that 0.8 − 0.9% of transcripts were TE related, with LTR retrotransposons (LTR-RTs) accounted for 65% TE transcripts. A large portion of these transcripts were non-autonomous TEs, which had incomplete functional domains. The majority of mapped transcripts were distributed in genic deficient regions, with 9% of TEs overlapping with genic regions. Moreover, over 90% TE transcripts exhibited low expression levels and insufficient reads coverage to support full-length structure assembly. Subfamily analysis of Copia and Gypsy, the two LTR-RTs revealed that a small number of subfamilies contained a significantly larger number of members, which play a key role in generating TE transcript. Based on resequencing data, 15,002 L-RT insertion loci were detected for active LTR-RT members. The insertion loci of LTR-RTs were highly divergent among greater yam accessions.ConclusionsThis study showed the ongoing transcription and transpositions of TEs in greater yam, despite low transcription levels and incomplete proteins insufficient for autonomous transposition. While our research did not directly link these TEs to specific yam traits such as tuber yield and propagation mode, it lays a crucial foundation for further research on how these TE insertion polymorphisms (TIPs) might be related to variations in greater yam traits and its tuber propagation mode. Future research may explore the potential roles of TEs in trait variations, such as tuber yield and stress resistance, in greater yam.

Detection and assessment of heavy metals concentration in wheat leaves collected from the vicinity of Sahiwal coal power plant, Pakistan, employing a modern data analysis approach

ABSTRACT Heavy metal pollution in food crops has become a global issue, especially in staple crops like wheat and rice. Electricity production utilising coal, ignites this issue in crops grown in the surrounding areas of coal power plants. Keeping this view in mind, the concentration of six heavy metals (HMs) Calcium (Ca), Cadmium (Cd), Chromium (Cr), Cobalt (Co), Lead (Pb) and Magnesium (Mg) in wheat leaves have been assessed in this study. Fifty samples of wheat leaves have been collected from the surrounding areas of the coal power plant in Sahiwal. The samples were prepared using the wet digestion method (WDM). Finally, these samples have been sent for analysis via atomic absorption spectroscopy (AAS). The limit of detection (LOD) and limit of Quantification (LOQ) of AAS were calculated with the help of blank samples. The concentration of Ca, Cd, Cr, Co, Pb and Mg in wheat leaves were 1.0187 ± 0.549 mg/kg, 0.00484 ± 0.00403 mg/kg 00,416 ± 0.00334 mg/kg, 0.0534 ± 0.0351 mg/kg, 0.035 ± 0.018 mg/kg, 0.464 ± 0.200 mg/kg respectively. The concentration of all understudy metals was below the Food and Agriculture Organization/World Health Organization (WHO/FAO) standards except for Co, in one sample. However, the concentration of heavy metals may increase, which may have profound repercussions. Therefore, preventive measures should be taken in this regard. The neutrosophic approach has been utilised to examine the variation of the heavy metals content in wheat leaves. This study provides a solid scientific foundation for future appropriate actions and management of heavy metals contamination in food crops near coal-fired power stations.

Nexus among climate change, food systems, and human health: An interdisciplinary research framework in the Global South

This article unravels the intricate connections between climate change, food systems, and human health, offering a comprehensive exploration within a concise framework focused on the Global South. The contemporary crisis stemming from the mass production model, emphasising climate change and public health repercussions, is a focal point. We highlight food production as an important driver of climate change, significantly contributing to greenhouse gas emissions. Livestock and staple crops exert varied environmental impacts. We scrutinise the implications of land-use changes, emphasising the imperative to curtail agricultural expansion into forested areas. Central to our analysis is the role of governance systems. We advocate for a multi-level, polycentric governance approach integrating health considerations with ecology and socio-economic drivers. By exploring the nuances of gender, age, and ethnicity, we underscore the need for a climate transition guided by climate justice principles. Finally, we discuss methodological challenges in researching the complex nexus of food systems, climate change, and health. We navigate the limitations of disciplinary boundaries and traditional analytical methods, urging an interdisciplinary approach for a comprehensive understanding. Our work aims to contribute to a holistic perspective, informing policy-making and action to build a resilient and sustainable future, especially in the Global South.

Carbon Farming of Main Staple Crops: A Systematic Review of Carbon Sequestration Potential

Carbon farming has become increasingly popular as it integrates agriculture, forestry, and diverse land use practices, all crucial for implementing European strategies aimed at capturing 310 million tons of carbon dioxide from the atmosphere. These farming methods were proven to reliably increase the amount of carbon stored in the soil. However, there is a lack of discussion and consensus regarding the standards used to report these values and their implications. This article analyzes carbon sequestration rates, calculation methodologies, and communication procedures, as well as potential co-benefits and best practices. The average carbon sequestration rates in major staple crops range from very low values (0–0.5 Mg/ha/yr) to medium values (1–5 Mg/ha/yr). Scientific agricultural experiments in key global staple crops demonstrate positive rates of 4.96 Mg C ha−1 yr−1 in wheat–maize rotations and 0.52–0.69 Mg C ha−1 yr−1 in rice–wheat rotations. In agriculture, carbon sequestration rates are reported using different terms that are not consistent and pose communication challenges. This assessment involves a systematic review of the scientific literature, including articles, reviews, book chapters, and conference papers indexed in Scopus from 2001 to 2022. Specifically, this review focuses on long-term experiments, meta-analyses, and reviews that report an increase in soil carbon stock. The research trends observed, through a VOSviewer 1.6.18 analysis, show a steadily increasing interest in the field of carbon sequestration.

Impact of storage conditions on the shelf life of aflatoxin biocontrol products containing atoxigenic isolates of Aspergillus flavus as active ingredient applied in various countries in Africa

Aflatoxin contamination significantly threatens food safety and security, particularly in tropical and sub-tropical regions where staple crops such as maize, groundnut, and sorghum become frequently affected. This contamination is primarily caused by the fungus Aspergillus flavus. The contamination causes adverse health effects, reduced income, and trade restrictions. In response to this challenge, various technologies have been developed to mitigate the impacts of aflatoxin. Among these, biocontrol products containing atoxigenic isolates of A. flavus as the active ingredient can effectively reduce aflatoxin levels both at pre- and post-harvest. A notable example of such products is Aflasafe, which contains four atoxigenic isolates native to specific target regions. These products have undergone rigorous testing, have received regulatory approval, and are commercially available in multiple African countries. However, their manufacturing processes have evolved, and comprehensive shelf life studies for current formulations are lacking. Evaluations of the spore production ability of atoxigenic A. flavus isolates in Aflasafe products over 4 years, under various storage conditions, revealed a significant linear decrease in sporulation with storage months (P < 0.001; R2 = 0.203), with no significant differences observed between treatments. However, this marginal decline (P = 0.398) is unlikely to be sufficient to prevent the effectiveness in limiting aflatoxin. In addition, storing the products for 2 weeks at 54 °C did not affect (P > 0.05) the ability of the coated fungi to produce spores compared to when the products were stored at 24 °C. The findings contribute valuable insights for manufacturers and users of atoxigenic-based aflatoxin biocontrol products, informing best practices for product storage and utilization to ensure prolonged effectivenes in aflatoxin mitigation efforts.

IMPACT OF DIFFERENT ZINC APPLICATION METHODS AND PHOSPHORUS DOSES ON GROWTH, YIELD AND GRAIN ZINC CONTENTS OF WHEAT

Wheat is a staple crop of around half of the world's population. About 30 percent of the world’s population is suffering from Zn deficiency. Zn deficiency problems can be encountered by agronomic and genetic biofortification. Phosphorus (P) is an important plant macronutrient and has an antagonistic relationship with Zn. A field study was performed to evaluate the impact of different Zn application methods and P doses on growth, yield, and grain Zn contents of wheat at the Agronomic Research Farm, University of Agriculture Faisalabad, Pakistan, using a high accumulation wheat variety Zincol-2016. Three doses of P (100, 150, and 200% of recommended P) along with three Zn application methods (seed priming, soil mixing, and foliar application) were applied to wheat using randomized complete block design (RCBD) with three replicates under split-plot arrangement. All agronomic practices were kept normal and uniform for all treatments. Parameters including growth, yield, and Zn content in wheat grains were monitored using standard protocols. The results were evaluated using Fisher’s analysis of variance at a 5% probability level. A comparison of means of treatments was performed using the least significant difference (LSD) test. The highest value of SPAD reading (56.38) was noted in treatment where Zn was applied as priming and P was applied at 200%. Maximum crop growth rate (63.17) was observed in P3 where Zn was applied as mix in soil. Maximum spike length (14.25), spikelets per spike (17.67), and Zn concentration were observed in P3 as a result of foliar application of Zn. Highest grain weight per spike (1.89g), no. of tillers (691.01), grain yield (4.09 t ha-1), biological yield (11.01 t ha-1), harvest index (36.54%) and NDVI (0.42 were observed in P3 where Zn was applied as soil mix.

Planting pattern and nitrogen management strategies: positive effect on yield and quality attributes of Triticum aestivum L. crop

Wheat (Triticum aestivum L.) is a staple food crop that plays a crucial role in global food security. A suitable planting pattern and optimum nitrogen (N) split management are efficient practices for improving wheat production. Therefore, an experiment was performed to explore the effect of N split management and sowing patterns on wheat at the Agronomy Research Farm, The University of Agriculture Peshawar, during rabi season 2020-21 and 2021-22. The treatments consisted of different nitrogen rates of 0, 80, 120, and 160 kg ha− 1 and planting patterns of W, M, broadcast and line sowing. The pooled analysis of both cropping seasons showed that application of 120 kg N ha− 1 increased spikelets spike− 1, grains spike− 1, 1000 grains weight, grain yield, grain N content, evapotranspiration and water use efficiency by 21.9, 16.7, 21.8, 70, 13, 19.9 and 40% as compared to control, respectively. In addition, W and M were observed the best management practices among all planting patterns. The M planting pattern enhanced chlorophyll a, b, carotenoids and evapotranspiration while W plating pattern improved yield components and yield of wheat as compared to broadcast planting patterns. The principal component analysis biplot showed a close association of M and W planting patterns with 120 kg N ha− 1 in most of the studied traits. Hence, it is concluded that split application of 120 kg N ha− 1 in W and M sowing patterns enhanced growth, biochemical traits and water use efficiency, reducing N fertilization from 160 to 120 kg ha− 1 while increasing grain yield of wheat. Hence, it is recommended that application of 120 kg N ha⁻¹ in combination with W and M planting patterns offer a sustainable approach to enhancing wheat production in the alkaline soil conditions of the Peshawar valley.

Generic Workflow of a Highly Effective and Easy Anther Culture Method for Both Japonica and Indica Rice.

As one of the most important staple crops in the world, rice plays a pivotal role in world food security. The creation of doubled haploids based on anther culture is an important technology for rice breeding. However, at present, rice anther culture technology still faces many problems, such as genotype dependency, especially genotypes of indica rice. In this study, fifteen rice genotypes, including twelve japonica rice genotypes and three indica rice genotypes, were randomly selected and used to study anther culture by using a modified M8 medium. The results showed that the total callus induction rates of these different rice genotypes ranged from 0.81 to 13.95%, with an average of 6.64%, while the callus induction rates calculated for the top ten highest callus inductions for each rice genotype ranged from 2.75 to 17.00%, with an average of 10.56%. There were varying gaps between the total callus induction rates and the callus induction rates in these different rice genotypes. The fact that the gaps for some rice genotypes were relatively large indicated that standard tiller or anther collection was not applicable to all rice genotypes and that there was still a lot of room for improvement in the callus induction rate of some rice genotypes through optimization of the sampling method. The plantlet regeneration rates ranged from 12.55 to 456.54%, with an average of 200.10%. Although there were many albinos from anther culture for some rice genotypes, these would still meet the requirement if the rice genotypes had higher callus induction rates or regeneration rates. The percentages of seed setting of regenerated green seedlings ranged from 14% to 84%, with an average of 48.73%. Genetic diversity analysis showed that the genetic background of these different rice genotypes was representative, and the phylogenetic tree and Principal Component Analysis (PCA) divided them into indica and japonica types. Therefore, in this study, an anther culture method suitable for both indica and japonica rice genotypes was established, which could improve doubled haploid breeding in rice.