High temperature causes harmful effects on growth, quality and yield of rice (Oryza sativa L.). Higher spikelet fertility is the most desirable trait for mitigating the effects of climate change, and thus need to develop rice varieties with climate resilience under future climate scenario for sustainable rice productivity. In our study, spikelet fertility and panicle weight were investigated under controlled environmental conditions in a set of 241 rice genotypes, which were sequenced in 3000 rice genomes project. High temperature significantly reduced the spikelet fertility and panicle wight by over 50% in this study. Genome wide association mapping was performed on spikelet fertility and panicle weight with 1 million SNPs using an efficient mixed model. Three promising MTAs viz., qHTSF19_5.2, qHTSF19_5.4 and qHTPW19_9.2 and haplotype variants of four putative candidate genes namely, LOC_Os05g15160 (a triose phosphate/phosphate translocator 2), LOC_Os05g16420 (SHR5-receptor-like kinase), LOC_Os09g15670 (an ABA-induced protein phosphatase 2Cs) and LOC_Os09g15700 (a receptor like protein kinase) were identified. The variations of non-synonymous SNPs (nsSNPs) in the gene sequences were used to group the association panel and identify superior donors and haplotypes. IRIS 313-8704 and IRIS 313-11307 were identified as superior donors with higher spikelet fertility and panicle weight under HT stress. Moreover, both the identified donors were found to be in the same haplotype group, highlighting their significance in developing haplotype specific markers that could be beneficial for marker-assisted breeding and making reproductive stage high temperature stress tolerant rice globally.

A study was conducted with clonal and seedling-derived trees of Pongamia pinnata in the field conditions at the ICAR-Central Agroforestry Research Institute, Jhansi, India, with an objective to unravel the mechanistic insights for drought stress tolerance in clonal and seedling trees of Pongamia pinnata through comparative physio-biochemical determinants. Photosynthetic CO2 assimilation (PNmax) and its associated parameters, along with chlorophyll fluorescence traits were analysed. Leaf water potential (LWP) was measured with the PSΨPRO water potential system. Findings of the study showed that clonal plants performed better than seedling plants during dry heat summer (DHS) by maintaining higher PNmax and its associated traits and PNmax was supported by a higher LWP. Additionally, elevated peroxidase (POD) activity and diminished malondialdehyde (MDA) levels in clonal plants as compared to seedling plants during DHS were validated by photosynthetic and chlorophyll fluorescence traits, thereby affirming their superior performance. In addition, clonal plants also recorded higher plant height, diameter at breast height (DBH) and 100-seed weight, signifying their higher resilience during DHS. Principal component analysis (PCA) unveiled that LWP, PNmax and Gs were major contributors to total variance. The study inferred that clonal plants of Pongamia pinnata maintained relatively higher physiological functioning during DHS.

Agri-silviculture and agri-horticulture systems, which integrate trees and crops on the same land, are important sustainable land-use strategies. However, the dynamics of basal soil respiration (BSR) in such systems are not fully unravelled. This study investigated the effects of agroforestry systems on BSR dynamics [rate (RBSR) and cumulative CO2evolution (CBSR)] and identified the roles of soil organic carbon (SOC), soil moisture content (SMC) and dehydrogenase (DHA) enzyme activity on BSR. Basal soil respiration was quantified using the alkali trap method over 15 days at 3-day intervals from pre-sowing to crop maturity under 2 agroforestry systems-Tectonagrandis L.f. (teak; agrisilviculture) and Phyllanthusemblica L. (aonla; agri-horticulture) and compared with a sole cropping system without trees. Black gram (Vigna mungo (L.) Hepper) and mustard (Brassica juncea (L.) Czern.) were cultivated as understory crops. Distinct temporal dynamics in BSR (RBSRand CBSR) were observed. In black gram, CBSR increased from pre-sowing to flowering (by 24.7 % and 32.4 %) and declined toward maturity (by 10.8 % and 15.9 %) at 0-30 and 30-60 cm depths, respectively. The maximum CBSR was observed in the teak-based system at flowering stage of black gram and mustard that ranged from 2.5-13.3 and 1.9-11.2 mg CO2-C 100 g-1 soil at 0-30 and 30-60 cm depths, respectively. Similarly, at flowering stage of the crops, CBSR ranged from 1.2-11.6 and 0.9-9.1 mg CO2-C 100 g-1 soil and 2.3-9.2 and 1.3-6.1 mg CO2-C 100 g-1 soil in aonlabased system and sole cropping at 0-30 and 30-60 cm depths, respectively. DHA activity (67-77 % variance) was the best predictor of CBSR followed by SOC (36-78 % variance) while SMC played a fair predictor (21-25 % variance). The study highlights the potential of agroforestry systems to enhance soil biological activity and managing soil carbon while supporting sustainable crop productivity.

Root traits during post-tillering stages in wheat are critical for adapting to moisture-deficit stress. This study mapped 24 traditional quantitative trait loci (QTLs) of root and yield traits in wheat across 14 chromosomes using 198 recombinant inbred lines (RILs), developed by crossing two contrasting parents, HD 3086 and HI 1500. Genotyping was done with the 35 K Axiom Wheat Breeder’s Array, followed by QTL mapping through Inclusive Composite Interval Mapping (ICIM) software. From the 5 conditional QTLs (Y75|Y45) mapped, QARFC.iari-2 A was mapped as the major stable QTL for root fresh weight, explaining 11.23

Heat stress negatively impacts key yield-contributing physiological traits in wheat, leading to a decrease in grain yield. Scanning of genomic regions linked to these traits, along with the identification of the most relevant candidate genes (CGs), is an effective strategy for developing heat-tolerant wheat cultivars in the near future. In this context, a genome-wide association mapping approach has been employed to identify chromosomal regions associated with these traits, along with to identify the putative CGs for heat tolerance in wheat. Genotyping was performed using the 35 K Axiom Wheat Breeder Array. From our study, principal component analysis (PCA) revealed that biomass (BM), canopy temperature (CT), and seed weight per pot (SWPP) explained a higher cumulative variance. Population structure and diversity analysis filtered 13,947 markers and revealed three subpopulations with sufficient diversity. A large whole-genome LD block size of 7.15 MB was obtained at a half LD decay value. We have mapped 14 significant MTAs linked to these traits with − log10(p) value > 5.44 after Bonferroni correction and also identified 14 high-confidence CGs. Our study also identified four haplotype groups, suggesting the potential for a haplotype-based breeding program under heat stress. Promoter analysis revealed 174 cis-regulatory elements (CREs). Phylogenetic analysis of the pleiotropic gene TraesCS7A02G200200 revealed three major clades of closely related species. We have also reported several orthologous genes related to our 14 major CGs. Untranslated regions (UTRs) analysis found several upstream Open Reading Frames (uORFs) in few identified genes, which can be employed to understand the stringent mechanism of gene regulation under heat stress. By using the Multitrait-genotype ideotype index (MGIDI), we have selected 13 high-performance genotypes for their use as donor parent for heat tolerance. Henceforth, after successful validation, these SNPs can be utilized for marker-assisted transfer of genes/QTLs to develop heat-tolerant wheat cultivars. Mapped 14 significant marker-trait associations (MTAs) for yieldcontributingtraits in wheat under heat stress. Identified 14 high-confidence CGs and four haplotype groups. Promoter analysis revealed 174 cis-regulatory elements (CREs) in identified CGs.

The present study aimed to validate the identified marker trait associations (MTAs) for stay-green (SG) and stem reserve mobilisation (SRM) using 12 wheat genotypes. Out of 12 genotypes, equal number of genotypes (6 each) had higher and lower SG and SRM traits. These genotypes were selected from our previous genome-wide association study for SG and SRM traits. Validation of mapped MTAs have been accomplished by using physiological and gene expression approach. Gene expression analysis of the identified genes in the MTAs region were carried out in these selected contrasting lines in a pot experiment site at Division of Plant Physiology, Indian Agricultural Research Institute (IARI), New Delhi, India. For SG traits, canopy temperature (CT), soil plant analysis development (SPAD) value, leaf senescence rate (LSR) was recorded, whereas for SRM, stem reserve mobilisation efficiency (SRE) was measured. The experiment was carried out in completely randomized design (CRD), under control and combined heat and drought stress (HD) condition. Plants in the control condition (timely sown) were irrigated at their critical phenological stages throughout the cropping period, while under combined stress (50 days late sown), irrigation was withheld at the flowering stage to impose drought stress. Candidate genes found in the overlapping region and within the region of 100 Kb intervals flanking either side of the associated markers were identified through BioMart tool in Ensemble Plants platform. Real-time gene expression analysis was performed on SG-associated genes in the flag leaf and SRM- associated genes in the peduncle. Phenotypic assessment showed that there was significant genotypic variation for the SG and SRM traits and yield. Low SG and SRM performing genotypes showed around 27% and 37% faster leaf senescence rate (LSR) than high SG and SRM performing genotypes under control and HD conditions, respectively, which confirming to our mapped MTAs for SG and SRM traits. HD3366 showed highest stem reserve mobilisation efficiency (SRE) of around 85% under combined stress, while lowest of around 27% was recorded in MP1369 under control condition. Thousand grain weight (TGW) showed negative association with LSR, while positive correlation with SRE. However, highest relative gene expression of cytokinin dehydrogenase 11-like (TaCKX11) was recorded in low performing SG and SRM genotypes, while lowest expression was recorded in high performing SG and SRM genotypes. Expression analysis of candidate genes like protein phosphatase 2C (TaPP2C), TaCKX11, protein detoxification 40-like (TaPD), F-box protein (TaFBP) and pentatricopeptide repeat (TaPPR) were associated with leaf senescence (SG- linked). Genes linked with SRE, such as serine/threonine-protein kinase 2 (TaSK2) and wall-associated receptor kinase 4- like (TaWAK) exhibited the highest expression levels during 12 days after anthesis, suggesting their involvement in enhanced carbon reserve mobilization to the grain under stress conditions. Our study confirmed the association of mapped markers and its linked traits, which can be used in further marker-assisted selection (MAS) using efficient breeding tools.

The study was carried out during the winter (rabi) season of 2023–24 and 2024–25 at ICAR-Indian Agricultural Research Institute, New Delhi to reveal the potential of Kappaphycus alvarezii extract (KE), applied as Sagarika concentrate liquid in enhancing drought tolerance in wheat (Triticum aestivum L.). In this study, plants were subjected to foliar sprays of KE at varying concentrations (2.5%, 7.5%, and 10% v/v) and exposed to short-term drought stress (10 days) during initial vegetative phase (one-month old wheat seedlings). The results revealed that KE application significantly improved plant performance and physiological parameters under water stress conditions. The treatment combining irrigation with 10% KE (T5) recorded the highest soil moisture content (29.17%) and shoots biomass (1.858 g DW/plant) while drought-stressed plants without KE (T2) showed the lowest values. KE-treated plants retained higher relative water content, membrane stability and chlorophyll levels indicating improved stress tolerance. In addition, cellular oxidative stress markers such as electrolyte leakage and hydrogen peroxide accumulation were notably reduced in KE-applied treatments, confirmed through both biochemical analysis and DAB staining. These findings suggest that KE foliar application enhances drought resilience in wheat by alleviating oxidative stress and supporting physiological stability making it a sustainable and eco-friendly strategy for improving crop growth responses under water-deficit conditions.

Heat stress is considered to be a major limitation to crop production, especially in the northern part of India. Chickpea is a cool-season crop and faces heat stress during the terminal phase of its life cycle. Heat stress leads to a decline in water use efficiency (WUE) and dry matter partitioning to economic sink. The present study aimed to investigate the hormonal-regulated dry matter partitioning and water use efficiency under heat stress conditions in relation to alternation in vascular bundle anatomy. A chickpea field trial was conducted under late-sown heat stress condition to assess the effect of foliar spray of bioregulators viz . Abscisic acid (ABA), Benzyl adenine (BA), Salicylic acid (SA) on dry matter partitioning, water use efficiency and vascular bundles anatomy. Bioregulators (ABA, BA and SA) application enhanced photosynthesis rate, carboxylation efficiency, dry matter partitioning towards the economic sink. Maximum water use efficiency (WUE) was recorded in ABA treated plants followed by BA treated plants. Under heat stress, the foliar spray of ABA improved the genesis of the xylem vessel as well as secondary phloem development while BA and SA treatments improved the development of the secondary phloem only. Bioregulators-induced alternation in vascular bundle anatomy was found to be associated with dry matter partitioning and water use efficiency under heat stress in chickpea. The present study reports first time in chickpea that bioregulators-induced dry matter partitioning and water use efficiency (WUE) is mediated by altered vascular bundles anatomy under heat stress condition.

To meet the ever-increasing demand for food, there is a huge concern about the selection of superior genotypes with enhanced resilience to abiotic stress. However, choice/selection of suitable genotype/line is complex due to significant interaction of genotypes with environmental factors. Aiming few traits for selection may simplify the statistical analysis, however selection of genotypes using multiple traits is quite difficult. Furthermore, use of any single index may bias the selection of genotypes. Here, we proposed one method for selection of superior genotypes using combined approach of four selection indexes such as, multi-trait genotype-ideotype distance index (MGIDI), factor analysis and genotype-ideotype distance (FAI-BLUP), Smith-Hazel index (SHI) and multi-trait stability index (MTSI) under multi-environment stress conditions by using R programming. From our study, twenty random recombinant inbred wheat lines among the 220 lines developed by crossing HD3086 and HI1500 has been taken for analysis. The selection intensity (SI) was 15% for all the indexes. The lines were tested for stay-green and stem reserve mobilisation traits under control, drought, heat and combined stress conditions. Result found that RIL-10 was common to these four indexes by using venn diagram and was considered to be superior among the lines, which can perform better under multi-environment stress conditions. Thus, we recommend that combined approach of several indexes can be used a robust method for selection of ideal genotypes in wheat and other crop as well.

Object detection is a crucial aspect of computer vision used to address drought tolerance in the biological context. In this context, we address the crucial task of selection of drought-tolerant mustard genotypes (B. juncea) based on automatic and non-destructive deep learning YOLOv5-based silique count software MuSiC v1.0. Our approach utilizes YOLOv5, based on images acquired using a DSLR camera (SONY Alpha 7iii, 24.2MP), securely affixed to a tripod. The user-friendly desktop software named MuSiC v1.0, underpinned by the YOLOv5 model discriminates drought tolerant and susceptible mustard genotypes based on Multi-trait Genotypte Ideotype Distance Index (MGIDI) and the results are comparable with the manual count. This model was trained using an annotated dataset for each of the 30 genotypes, crafted with the assistance of the Roboflow annotator, comprising approximately 22,800 annotations. Drought effect on the silique count trait was comparable both in manual as well as MuSiC v1.0 software-based count method. Stress tolerance indices are derived using iPASTIC software for 30 genotypes and ultimately these traits are used for selecting drought tolerance based on MGIDI index. Superior drought-tolerant mustard genotypes were chosen with a 25

Water-soluble carbohydrates (WSCs) serve as a potential buffer for grain filling in wheat, when current leaf photosynthesis is inhibited by abiotic stress. The potential of genotype to store WSCs for its remobilisation is determined by its stem-specific weight i.e. stem density. To examine the extent to which mobilisation of carbon reserve occurs under multi-environment conditions and the genomic regions associated with stem density in wheat, a field experiment was conducted at Indian Agricultural Research Institute (IARI), New Delhi, India with 220 wheat RILs developed by crossing HD3086 and HI1500 under control, drought, heat and combined stress (heat and drought) conditions. Genotyping of population (21 days seedling) was done with 35 K Wheat Breeder Array followed by QTL mapping with inclusive composite interval mapping (ICIM) software. Selection of superior lines were carried out by using combined approach of multi-trait genotype-ideotype distance index (MGIDI), factor analysis and genotype-ideotype distance (FAI-BLUP) and Smith-Hazel index (SH). In our study, total 9 quantitative traits loci (QTLs) were mapped, which were linked to stem density (peduncle, penultimate and lower internode) with LOD score > 3.5, of which 7 were mapped as major QTLs. In-silico gene expression analysis revealed various important genes like sugar transport protein MST4, PPR containing protein, trehalose phosphate synthase, NRT1/PTR FAMILY 8.3-like etc., which are probably involved in maintaining stem density in wheat. Moreover, four lines (HDHI-12, HDHI-87, HDHI-142 and HDHI-194) were identified as superior lines, which can be used as potential donors to elite wheat cultivars. Our study shed light on genetic basis of regulation of stem density in wheat, which accelerates the possible marker-assisted and genomic selection for higher stem density and stem reserve mobilisation.

Introduction:Micronutrient deficiencies, particularly zinc (Zn) and iron (Fe), are prevalent global health issues, especially among children, that lead to hidden hunger. Wheat is a primary food source for billions of people, but it contains low essential minerals. According to recent studies, the optimum application of nitrogen (N) fertilizers can significantly enhance the micronutrient uptake and accumulation in wheat grains. Methods:The aims of this study were to identify superior wheat recombinant inbred lines (RILs) of RAJ3765 × HD2329 with high nutrients in grain using the multi-trait genotype-ideotype distance index (MGIDI) and to identify quantitative trait loci (QTLs)/genes associated with grain nutrient content using a single-nucleotide polymorphism (SNP)-based genetic linkage map. The parents and their RIL population were grown under control and nitrogen-deficient (NT) conditions, and nutrient content was determined using inductively coupled plasma optical emission spectroscopy (ICP-OES). Results and discussion:Analysis of variance and descriptive statistics showed a significant difference among all the nutrients. The highest mean values of grain iron concentration (GFeC) and grain zinc concentration (GZnC) were 52.729 and 35.137 mg/kg, respectively, under the control condition, while the lowest mean values were 41.016 and 33.117 mg/kg, respectively, recorded under NT; a similar trend was observed in all the elements. Genotyping was carried out using the 35K Axiom® Wheat Breeder's Array. A genetic linkage map was constructed using 2,499 polymorphic markers identified for parents across 21 wheat chromosomes. Genetic linkage mapping identified a total of 26 QTLs on 17 different chromosomes. A total of 18 QTLs under the control condition and eight QTLs under the nitrogen stress condition were identified. QTLs for each nutrient were selected based on the high percentage of phenotypic variation explained (PVE%) and logarithm of odds (LOD) score value of more than 3. The LOD scores for studied nutrients varied from 3.04 to 13.42, explaining approximately 1.1% to 27.83% of PVE. One QTL was mapped for grain calcium concentration (GCaC), whereas two QTLs each for grain potassium concentration (GKC), GFeC, grain copper concentration (GCuC), and grain nickel concentration (GNiC) were mapped on different chromosomes. Four QTLs were mapped each for GZnC, grain manganese concentration (GMnC), and grain molybdenum concentration (GMoC), while the highest five were linked to grain barium concentration (GBaC). In silico analysis of these chromosomal regions identified putative candidate genes that code for 30 different types of proteins, which play roles in many important biochemical or physiological processes. Putative candidate gene magnesium transporter MRS2-G linked to GFeC and probable histone-arginine methyltransferase CARM1 and ABC transporter C family were found to be linked to GZnC. These QTLs can be utilized to generate cultivars adapted to climate change by marker-assisted gene/QTL transfer.

The experiment was conducted during winter (rabi) season of 2020–21 and 2021–22 at ICAR-Indian Agricultural Research Institute, New Delhi to assess the individual and combined effects of drought and heat stresses on bread wheat (Triticum aestivum L.), focusing on yield, yield-contributing parameters, and grain nutritional quality in four contrasting wheat genotypes (C306, HD2967, Raj3765 and WL711). The experiment was laid out in completely randomized design (CRD) with 15 replications of each genotype. The results revealed that combined drought and heat stress had a more severe impact on yield-related traits compared to individual stresses. Yield losses under drought stress ranged from 17.7–32.24%, while heat stress alone caused reductions of 29.98–46.55%. However, the combined stress led to the highest yield loss (42.13–61.06%), emphasizing the additive detrimental effects of both stresses. Similarly, 1000-kernel weight (TKW) declined significantly under combined stress conditions, with reductions ranging from 33.22–52.23%, due to impaired starch synthesis and reduced enzymatic activity. Genotype Raj3765 exhibited the highest tolerance, followed by C306, HD2967, and WL711, as indicated by the Stress Susceptibility Index (SSI) and Yield Stability Ratio (YSR). Additionally, nutritional quality assessments showed a decline in zinc (Zn) and iron (Fe) concentrations under drought and combined stresses, with Raj3765 exhibiting the least reduction and WL711 the highest. Despite reductions in starch content, protein content increased under heat stress, suggesting differential regulation of nitrogen metabolism. These findings highlight the necessity of breeding wheat varieties with enhanced resilience to multiple stress factors to sustain grain yield and nutritional quality under climate change scenarios.

Stay-green (SG) and stem reserve mobilization (SRM) are two significant mutually exclusive traits, which contributes to grain-filling during drought and heat stress in wheat. The current research was conducted in a genome-wide association study (GWAS) panel consisting of 278 wheat genotypes of advanced breeding lines to find the markers linked with SG and SRM traits and also to screen the superior genotypes. SG and SRM traits, viz. soil plant analysis development (SPAD) value, canopy temperature (CT), normalized difference vegetation index (NDVI), leaf senescence rate (LSR) and stem reserve mobilization efficiency (SRE) were recorded. The trial was conducted in α-lattice design, under control and combined heat and drought stress (HD). Analysis of variance and descriptive statistics showed a significant difference across the evaluated traits. The highest mean of SRE (31.7

Introduction:Abiotic stress significantly reduces the wheat yield by hindering several physiological processes in plant. Stay-green (SG) and stem reserve mobilization (SRM) are the two key physiological traits, which can contribute significantly to grain filling during stress period. Validation of genomic regions linked to SG and SRM is needed for its subsequent use in marker-assisted selection in breeding program. Methods:Using a physiological and gene expression approach, quantitative trait loci (QTLs) for stay-green (SG) and stem reserve mobilization (SRM) were validated in a pot experiment study using contrasting recombinant inbred lines including its parental lines (HD3086/HI1500) in wheat. The experiment was laid down in a completely randomized design under normal (control, drought) and late sown (heat and combined stress) conditions during the 2022-2023 rabi season. Drought stress was imposed by withholding irrigation at the anthesis stage, whereas heat stress was imposed by 1-month late sowing compared to the normal sowing condition. Combined stress was imposed by 1-month late sowing along with restricted irrigation at the flowering stage. Superior lines (HDHI113 and HDHI87) had both SG and SRM traits, whereas inferior lines (HDHI185 and HDHI80) had contrasting traits, i.e., lower SG and SRM traits. HD3086 and HI1500 had SG and SRM traits respectively. Potential candidate genes were identified based on the flanking markers of the mapped QTLs using the BioMart tool in the Ensembl Plants database to validate the identified QTLs. Real-time gene expression was conducted with SG-linked genes in the flag leaf and SRM-linked genes in the peduncle. Results and Discussion:In this study, HDHI113 and HDHI87 showed higher expression of SG-related genes in the flag leaf under stress conditions. Furthermore, HDHI113 and HDHI87 maintained higher chlorophyll a content of 7.08 and 6.62 mg/gDW, respectively, and higher net photosynthetic rates (PN) of 17.18 and 16.48 µmol CO2/m2/s, respectively, under the combined stress condition. However, these lines showed higher expression of SRM-linked genes in the peduncle under drought stress, indicating that drought stress aggravates SRM in wheat. HDHI113 and HDHI87 recorded higher 1,000-grain weights and spike weight differences under combined stress, further validating the identified QTLs being linked to SG and SRM traits. Henceforth, the identified QTLs can be transferred to developed wheat varieties through efficient breeding strategies for yield improvement in harsh climate conditions.

In changing climate scenarios, practically sound and suitable agronomic management options are of utmost need for sustainable crop production. An experiment involving three irrigation scheduling, two mulching, and four integrated nutrient management (INM) treatments was undertaken for consecutive two years at the Research Farm of the Institute of Agricultural Sciences, Banaras Hindu University, Varanasi, India in a split-split plot design with three replicates. This study evaluated the effect of irrigation scheduling, mulching, and INM on the performance of summer groundnut under sub-tropical conditions. Irrigation scheduling, mulching, and INM had a significant influence on growth and developmental parameters, yield attributes, yields, shelling (%), harvest index, quality parameters, and economics. Scheduling irrigation at lower cumulative pan evaporation (CPE) hugely benefited crops through increased pod yield (8.3%) haulm yield (5%), kernel yield (8.4%), oil yield (8.6%), and net returns (12.7%) over higher CPE (100 mm). The use of paddy straw mulch enhanced pod yield, haulm yield, kernel yield, oil yield, and net returns by 8.2, 3.6, 8.3, 9.0, and 13.2%, respectively as compared to dust mulch. Among INM, 75% RDN (recommended dose of nitrogen) + 25% N (FYM) + 60 kg S (gypsum) adjudged significantly better and recorded higher biological yield (16%), net returns (39%), and B:C ratio (16.2%) than 100% RDN. It is concluded that scheduling irrigation at 60 mm CPE along with paddy straw mulch and 75% RDN + 25% N (FYM) + 60 kg S (gypsum) can be adopted for better yield and economics of summer groundnut under sub-tropical conditions.

The present study was conducted to evaluate the role of traits associated with photosynthesis, Radiation interception (RI) and Radiation Use Efficiency (RUE) in relation to biomass and yield in Basmati rice genotypes. It was hypothesized that, whether yield improvement of Basmati rice will depend on enhancing the biomass through better RI and RUE or harvest index or both. A field experiment was conducted with nineteen aromatic rice genotypes, which included eighteen Basmati and one aromatic hybrid (PRH-10). Among the nineteen genotypes there was variability in biomass production and leaf area and the biomass production was linearly correlated with total intercepted PAR (TIPAR) between 55 and 95 DAS. Higher radiation interception was associated with the variability in crop growth rate among the genotypes. There was a high variability in the RUE ranging from (1.46–2.89 g MJ−1), and those genotypes maintained higher crop growth rate (CGR). Genotypes with higher LAI were associated with a lower extinction coefficient (k) and improved RUE. However, the leaf photosynthetic parameters viz. photosynthesis rate, transpiration rate and stomatal conductance were negatively associated with the aboveground biomass at anthesis. The net assimilation rate (NAR) was positively correlated with the photosynthetic parameters. Comparison of the mean of five highest biomass Basmati genotypes (HBBG), namely PB 1121, Sarbati, Pant Basmati-1, PB 1728 and PB1718 was done with the aromatic rice hybrid PRH-10. At anthesis stage, there was not much difference in dry weight, CGR and in RUE in HBBG compared to PRH-10. At harvest, the HBBG showed higher biomass (+ 15

Agriculture is the backbone of Indian economy. It provides employment to the 70% of the country population and contributes about 30% in country GDP. The traditional farming seems to be not capable of feeding the burgeoning country population. Hence, the new generation technologies, namely precision agriculture (PA), need to be adopted to meet the forthcoming demand and challenges while enhancing crop productivity, resources use efficiency, and sustainability of the agricultural systems. The concept of PA uses the recent developments in sensors, greenhouse, and protected agriculture structures. In PA, the spatial variability occurring within a field is noted, mapped, and then management actions are taken by adopting site-specific management systems applying remote sensing, global positioning system, and geographical information system. PA visualizes economical and environmental benefits through reduced use of water, fertilizers, herbicides, and pesticides besides the farm equipment. Instead of managing/applying inputs to an entire field based upon some hypothetical average condition, the PA approach recognizes site-specific differences within fields and adjusts need-based management actions. The adoption of techniques is having greater scope for wider adoption in India for higher-quality production, sensible resources utilization, and environment protection. The scope of PA is different for the different countries due to many factors, namely socioeconomic condition, technical manpower, and size of landholding. As per the suitability and feasibility, variable rate technology, precision land leveling, precision planting and precision nutrient management by using leaf color chart, soil plant analysis development, green seeker, site-specific nutrient management, and soil test crop response are the main PA techniques commonly used in India for crop management.