PLANT CELL BIOTECHNOLOGY AND MOLECULAR BIOLOGY

Trait Associations and Path Analysis for Green Fruit Yield in Elite Selections from Multi-parent Derived Populations of Chilli (Capsicum annuum L.)

K. Bhargavi — 2026-09-09

Green fruit yield is a complex quantitative trait influenced by several yield-related components, and understanding the relative contribution of these traits is essential for effective selection in chilli breeding. The present study was undertaken to assess the association of green fruit yield with yield-related traits among elite selections derived from five superior eight-parent multi-parent (MP) populations of chilli. The selected MP-derived populations comprised D4 × D3, D4 × D2, D5 × D2, D6 × D2 and D7 × D2. Elite progenies derived from superior plants within these populations were evaluated during the 2020 rainy season at the experimental farm of the University of Agricultural Sciences, Bengaluru. Observations were recorded for average fruit weight, average fruit number plant^-1, average fruit length, average fruit width and green fruit yield per plant. Phenotypic correlation coefficients were estimated separately for each MP-derived population, while path coefficient analysis was performed using the pooled dataset to partition the correlations into direct and indirect effects. Average fruit number plant^-1 exhibited a strong and positive association with green fruit yield across all five populations. Average fruit length showed significant positive associations with green fruit yield. Path analysis revealed the highest positive direct effect for average fruit number plant^-1, followed by average fruit width and average fruit weight. The findings suggest that fruit number plant^-1 may serve as an important selection criterion for improving green fruit yield, with fruit length and fruit width serving as complementary traits depending on the genetic background of the population.

Genetic Diversity in Chickpea (Cicer arietinum L.) Using Microsatellite Markers

Malagouda D. Patil — 2026-09-09

Aim: This study assessed SSR-based genetic diversity among 75 chickpea (Cicer arietinum L.) genotypes to identify genetically diverse parental resources for chickpea improvement.

Study Design: Laboratory-based molecular characterisation and genetic diversity analysis using SSR markers followed by similarity and cluster analyses.

Place and Duration of Study: Molecular Biology Laboratory, Department of Biotechnology, College of Agriculture, Vijayapur, University of Agricultural Sciences, Dharwad in 2021.

Methodology: Seventy-five chickpea genotypes were characterised using 20 polymorphic SSR markers distributed across the genome. Genomic DNA was extracted from young leaf samples using the CTAB method, followed by PCR amplification and separation of SSR products on 3% agarose gels. The amplification profiles were scored as binary data and used to estimate genetic similarity based on the Nei and Li coefficient. Genetic relationships were assessed through UPGMA cluster analysis using NTSYSpc and marker informativeness was evaluated using polymorphic information content (PIC).

Results: The 20 SSR markers generated a total of 73 alleles across the 75 chickpea genotypes, with an average of 3.65 alleles per marker. The number of alleles per marker ranged from 1 to 6, with TA22, TA28 and TA29 exhibiting the highest allelic variation (6 alleles each). PIC values ranged from 0.419 (TA194) to 0.797 (TA28), with 17 markers recording PIC values above 0.50, indicating their high discriminatory potential. UPGMA cluster analysis grouped the genotypes into 23 distinct clusters, with Cluster II being the largest (29 genotypes), followed by Cluster I (10 genotypes), while the remaining clusters comprised fewer or single genotypes, reflecting substantial genetic differentiation among the genotypes.

Conclusion: The SSR markers effectively revealed substantial genetic diversity and distinct molecular relationships among the chickpea genotypes. The identified genetically diverse genotypes can be utilised as promising parents to broaden the breeding base and develop diverse populations for improving chickpea productivity and adaptability.

Comparative in vitro Evaluation of Systemic Fungicides and Bioagents against Pigeonpea Wilt Caused by Fusarium oxysporum f. sp. udum

S. N. Shaikh — 2026-09-04

Aims: To evaluate the in vitro fungitoxic potential of seven systemic fungicides at concentrations of 500 and 1000 ppm and seven fungal biological control agents against Fusarium oxysporum f. sp. udum, the causal pathogen of pigeonpea wilt.

Study Design: Completely Randomized Design (CRD).

Place and Duration of Study: Department of Plant Pathology, College of Agriculture, Latur, Maharashtra, India. The study was conducted during 2025–2026.

Methodology: The wilt pathogen (F. oxysporum f. sp. udum) was isolated from infected pigeonpea root tissues displaying characteristic vascular discolouration. Seven systemic fungicides (Carbendazim 50% WP, Myclobutanil 10% WP, Propiconazole 25% EC, Thiophanate methyl 70% WP, Difenoconazole 25% EC, Tebuconazole 25.9% EC, and Hexaconazole 5% EC) were screened at concentrations of 500 and 1000 ppm using the Poisoned Food Technique. Seven fungal bioagents (T. harzianum, T. virens, T. hamatum, T. asperellum, Penicillium chrysogenum, Aspergillus niger, and Aspergillus flavus) were evaluated using the dual-culture technique on Potato Dextrose Agar (PDA).

Results: All tested systemic fungicides significantly inhibited pathogen mycelial growth compared with the control (P = .01). Carbendazim 50% WP produced complete growth inhibition (100.00%) at both 500 ppm and 1000 ppm. Among the remaining fungicides, Tebuconazole 25.9% EC exhibited mean inhibition of 85.18%, followed by Propiconazole 25% EC (82.78%), Thiophanate methyl 70% WP (80.14%) and Hexaconazole 5% EC (71.77%). Among the bioagents, T. harzianum achieved the maximum growth inhibition (82.04%), closely followed by T. virens (80.55%) and T. asperellum (74.82%), whereas Aspergillus flavus recorded the lowest inhibition (63.71%).

Conclusion: Among the chemical treatments, Carbendazim 50% WP, and among the biocontrol agents, T. harzianum, exhibited high efficacy in vitro, highlighting their potential for incorporation into integrated disease management strategies against pigeonpea wilt.

Influence of Plant Growth Regulators in Enhancing Fruit Retention, Yield, and Quality of Anola (Emblica officinalis L.)

Amit Singh Yadav — 2026-09-01

A field experiment was conducted during 2025-26 at the Nursery Farm, Department of Fruit Science, C.S. Azad University of Agriculture and Technology, Kanpur (U.P.), to evaluate the response of aonla (Emblica officinalis L.) cv. NA-7 to foliar sprays of gibberellic acid (GA₃) and naphthalene acetic acid (NAA), applied singly and in combination. Nine treatments comprising GA₃ at 25 and 50 ppm, NAA at 25 and 50 ppm, their four combinations, and a water-sprayed control were evaluated in a Randomised Block Design with three replications; sprays were applied at flowering and post-fruit-set stages. All recorded parameters responded significantly to the treatments. The combined spray of GA₃ 50 ppm + NAA 50 ppm (T₈) consistently produced the best response among the treatments: fruit drop decreased to 19.10% compared with 62.10% in the control, fruit retention increased to 80.90%, and yield reached 216.00 kg per plant, representing a 32.52% increase over the untreated trees. The same treatment produced the longest, widest, and heaviest fruits, the highest pulp weight, and the most favourable pulp-to-stone ratio (21.09, approximately 1.78 times that of the control). In terms of quality, it increased total soluble solids to 12.20°Brix, reduced titratable acidity to 1.72%, increased the TSS:acid ratio to 7.09, and increased ascorbic acid content to 608.32 mg per 100 g pulp. These results suggest a synergistic response to the combined application of GA₃ and NAA rather than a simple additive effect and support the use of GA₃ 50 ppm + NAA 50 ppm to reduce pre-harvest fruit drop and improve yield and fruit quality in aonla cv. NA-7 under the agro-climatic conditions of the Central Plain Zone of Uttar Pradesh.

Screening of Tomato Germplasm for Resistance to Fusarium Wilt Caused by Fusarium oxysporum f. sp. lycopersici under in vivo Conditions

Nentia Chib — 2026-08-29

Fusarium wilt, caused by Fusarium oxysporum f. sp. lycopersici, is a major constraint on tomato production worldwide. The present study was undertaken to evaluate thirty tomato germplasm accessions obtained from the ICAR-Indian Institute of Vegetable Research (IIVR), Varanasi, for their response to Fusarium wilt under field conditions during the 2023 and 2024 cropping seasons at SKUAST-Jammu, Chatha. The thirty germplasm accessions were evaluated under artificial disease pressure, and disease development was assessed through disease incidence, apparent infection rate (r), and area under the disease progress curve (AUDPC), with Pusa Ruby included as the susceptible cultivar. Significant variation was observed among the germplasm accessions in disease development and progression. Based on pooled disease incidence, one germplasm accession was categorised as tolerant (T), two as moderately susceptible (MS), ten as susceptible (S), and seventeen as highly susceptible (HS), whereas no germplasm accession showed resistant (R) or moderately resistant (MR) reactions. The germplasm accessions also exhibited considerable differences in infection rate and AUDPC values, reflecting variability in the speed and cumulative development of Fusarium wilt. Arka Saurabh exhibited comparatively lower disease development, while highly susceptible germplasm accessions showed rapid disease progression and greater disease accumulation. The identified tolerant and less susceptible germplasm accessions can be utilised as potential sources in tomato improvement programmes for developing Fusarium wilt-resistant cultivars.

Genetic Variability, Trait Association and Path Analysis for Yield and Yield-Contributing Traits in Linseed (Linum usitatissimum L.)

P. M. Talekar — 2026-08-27

Linseed (Linum usitatissimum L.) is an important oilseed crop in which improvement of seed yield depends on the availability of genetic variability and the identification of useful yield-associated traits. The present investigation was undertaken to assess genetic variability, heritability, genetic advance, correlation and path relationships for ten quantitative traits in 40 linseed genotypes. The experiment was conducted during rabi 2024–2025 at the College of Agriculture, Latur, Maharashtra, India, in a randomised block design with two replications. The traits evaluated included days to 50% flowering, days to maturity, plant height, number of branches per plant, number of capsules per plant, number of seeds per capsule, 1000-seed weight, oil content, harvest index, and seed yield per plant. Analysis of variance revealed significant differences among the genotypes for all the assessed traits.The recalculated estimates showed that GCV ranged from 4.61% for days to maturity to 22.15% for number of branches per plant, while PCV ranged from 5.14% for harvest index to 22.53% for number of branches per plant. Broad-sense heritability ranged from 63.06% for days to maturity to 98.24% for harvest index. Genetic advance as a percentage of the mean was highest for number of branches per plant (44.86%), followed by oil content (35.74%), 1000-seed weight (28.49%), number of capsules per plant (26.80%), number of seeds per capsule (26.16%) and seed yield per plant (25.96%). At the genotypic level, seed yield showed positive associations with number of branches per plant (0.7118), number of capsules per plant (0.7044), number of seeds per capsule (0.7265), plant height (0.0073) and 1000-seed weight (0.0141). The reported path analysis indicated positive direct effects of number of seeds per capsule (0.8083) and number of capsules per plant (0.3397) at the genotypic level, while number of branches per plant showed a high positive direct effect at the phenotypic level (1.6152). Thus, number of branches per plant, number of capsules per plant and number of seeds per capsule may be considered important selection criteria for improving seed yield under the present experimental conditions. The study was conducted at one location in one season; therefore, further multi-location and multi-season evaluation is necessary.

Stability Analysis Over Different Environments in Sesame (Sesamum indicum L.)

S. Sakthivel — 2026-08-26

Background: Sesame (Sesamum indicum L.) is an important oilseed crop whose productivity is strongly influenced by environmental variation and genotype × environment interaction. Identification of stable genotypes is therefore essential for improving yield consistency across diverse production conditions.

Aim: The study aims to evaluate the stability of 25 sesame genotypes across three environments for seed yield and associated quantitative traits using the Eberhart and Russell stability model.

Method: The experiment was conducted during kharif 2025 at Latur, Ambajogai, and Parbhani using a randomised complete block design with two replications. Ten quantitative traits were recorded, including days to 50% flowering, days to maturity, plant height, branches per plant, capsules per plant, capsule length, seeds per capsule, 1000-seed weight, oil content, and seed yield per plant. Data were analysed using analysis of variance and stability parameters.

Results: Significant genotypic differences were observed for all traits across environments. Environmental effects were significant for most traits, while pooled deviation was significant for all traits except days to maturity. For seed yield per plant, TBS-9, TS-14, and AKT-101 recorded the highest mean values. Stability analysis identified TBS-5-1, TBS-7-3, and TLT-408 as stable under average environments, TBS-7-2 as adapted to favourable conditions, and V-21, TS-14, TLT-5, and AKT-101 as adapted to unfavourable conditions.

Conclusion: The study demonstrated substantial variation in genotype performance and stability across environments. The identified genotypes may provide useful material for further multi-environment evaluation and breeding programmes aimed at improving yield stability in sesame.

Phenotypic Diversity and Correlation Analysis of Morphological Traits in Rice (Oryza sativa L.)

Namata Kumari — 2026-08-25

Sixty rice genotypes were evaluated during the Kharif season of 2023 at the Norman E. Borlaug Crop Research Centre (NEBCRC), G.B. Pant University of Agriculture and Technology, Pantnagar, Uttarakhand, using an alpha-lattice design with two replications to quantify phenotypic diversity and examine associations among 15 morphological and yield-related traits. The traits comprised plant height, flag-leaf length, flag-leaf breadth, leaf area, days to 50% flowering, number of panicles per plant, panicle length, number of grains per panicle, grain yield, biological yield, harvest index, grain length, grain breadth, grain length/breadth ratio and test weight. Pearson correlation analysis revealed that grain yield was strongly and positively associated with harvest index (r = 0.81, P < 0.01) but negatively associated with biological yield (r = -0.35, P < 0.01). Biological yield was positively associated with days to 50% flowering (r = 0.79, P < 0.01), flag-leaf length (r = 0.69, P < 0.01), leaf area (r = 0.68, P < 0.01), grains per panicle (r = 0.36, P < 0.01), plant height (r = 0.27, P < 0.05) and panicle length (r = 0.27, P < 0.05). Standardised Euclidean-distance-based hierarchical analysis partitioned the genotypes into five clusters containing 19, 8, 14, 10 and 9 entries, respectively. The greatest inter-cluster distance occurred between Clusters II and IV (6.885), while the smallest occurred between Clusters I and II (4.826). Cluster V showed the largest within-cluster distance (4.713), indicating comparatively high heterogeneity. Genotypes belonging to the widely separated Clusters II and IV constitute useful parental pools, provided their trait means and agronomic performance are also complementary. The results demonstrate appreciable morphological differentiation and identify trait relationships relevant to selection for rice improvement.

Estimation of Combining Ability in Early Genotypes of Pigeonpea [Cajanus cajan (L.) Millsp.]

Kamal Kumar Sharma — 2026-08-24

The present investigation was conducted to estimate general combining ability (GCA), specific combining ability (SCA) and the nature of gene action for yield and associated traits in early pigeonpea genotypes [Cajanus cajan (L.) Millsp.]. Eight genotypes, namely ICPL-20338, ICPL-20340, ICPL-87, Pusa-991, Pusa-992, PA-16, PA-291 and AL-882, were crossed using a diallel mating design during Kharif 2022–23. A total of 36 entries, comprising eight parents and 28 F₁ crosses, were evaluated in a randomised block design with three replications during Kharif 2023–24 at the AICRP on Pigeonpea, Agricultural Research Station, Kota, Rajasthan. Observations were recorded for days to 50% flowering, days to maturity, plant height, primary branches per plant, number of pods per plant, pod length, number of seeds per pod, 100-seed weight, biological yield per plant, seed yield per plant, harvest index, protein content and carbohydrate content. Analysis of variance for combining ability showed significant GCA effects for all traits except pod length, whereas SCA effects were significant for all traits. The ratio of GCA variance to SCA variance was less than unity for all traits, indicating the predominance of non-additive gene action. Among the parents, ICPL-20338, ICPL-20340, ICPL-87 and Pusa-992 were identified as good general combiners for seed yield per plant and related traits. The crosses ICPL-87 × PA-16, ICPL-20340 × AL-882, Pusa-992 × PA-16, ICPL-20338 × AL-882 and ICPL-20338 × PA-291 showed desirable SCA effects for seed yield and important yield-attributing traits. The cross ICPL-20338 × ICPL-87 exhibited significant SCA effects for protein content and carbohydrate content. These parents and cross combinations may be useful in pigeonpea breeding programmes aimed at improving yield and associated traits.

Multivariate Analysis in Maize (Zea mays L.) Inbred Lines

Vijay Anjana — 2026-08-22

Maize (Zea mays L.) is a leading cereal crop whose genetic improvement depends largely on the availability of diverse and divergent parents. The present investigation was undertaken to assess the mean performance and to quantify the genetic divergence among thirty maize inbred lines for sixteen quantitative characters. The experiment was conducted during the Kharif season of 2023–24 at the Research Farm of the Faculty of Agriculture Science and Technology, AKS University, Satna (M.P.), India, using a randomised complete block design with three replications. Analysis of variance revealed highly significant differences among the genotypes for all sixteen characters, and wide ranges were recorded, particularly for grain yield per plant (108.69–223.99 g), flag leaf length and shelling percentage, indicating the presence of substantial genetic variability. Genetic divergence was estimated using Mahalanobis’ D² statistic, and the genotypes were grouped into four clusters by the non-hierarchical Euclidean clustering method. Clusters I and IV were the largest, each comprising ten genotypes, whereas Clusters II and III contained five genotypes each. The maximum inter-cluster distance was observed between Clusters II and III (55.18) and the minimum between Clusters I and IV (22.00). Cluster I recorded the highest mean grain yield per plant, Cluster II the tallest plants and highest test weight, and Cluster IV the highest shelling percentage with the earliest flowering, although the clusters differed only modestly in mean performance for most yield components. The genotypes HKL-163, AMI-106 and AMI-118 emerged as the most promising parents. Hybridisation between genotypes drawn from the divergent Clusters II and III is suggested for exploiting heterosis and recovering desirable transgressive segregants in maize.

Assessment of Genetic Variability and Character Associations in Maize (Zea mays L.) Inbred Lines

Vijay Anjana — 2026-08-22

This study was undertaken to quantify the extent of genetic variability, characterise trait associations, and partition the direct and indirect effects of yield components on grain yield in maize (Zea mays L.). Thirty inbred lines were evaluated for sixteen quantitative characters in a randomised block design replicated three times. Analysis of variance detected highly significant differences among the inbred lines for every character, confirming a broad base of genetic variability in the material. The phenotypic coefficient of variation (PCV; 4.13–117.97%) exceeded the genotypic coefficient (GCV; 4.13–115.89%) only marginally for all traits, both being high for cob length (115.89, 117.97), days to 50% pollen shed (43.70, 43.73), flag leaf length (26.22, 26.24) and flag leaf width (24.65, 26.37). Broad-sense heritability was consistently high (72.61–99.86%), and the combination of high heritability with high genetic advance as per cent of mean—recorded for cob length (91.53%, 242.70%), days to 50% pollen shed (99.54%, 89.97%), flag leaf length (92.65%, 53.98%), tassel length (88.16%, 34.70%) and cob diameter (92.59%, 31.87%)—points to predominantly additive gene action and to the effectiveness of straightforward selection for these traits; because the estimates derive from a single season and location, however, they require confirmation across multiple environments. Grain yield per plant was significantly and positively correlated, at both the genotypic and phenotypic levels, with cob weight, test weight, number of cobs per plant, cob compact index, cob length and shelling percentage, the corresponding genotypic correlations being 0.581**, 0.562**, 0.523**, 0.512**, 0.472** and 0.448*. Path coefficient analysis interpreted in light of the strong intercorrelation among yield components (genotypic residual effect 0.2561) identified cob length (0.459), cob weight (0.412), shelling percentage (0.354) and cob compact index (0.276) as the traits with the highest positive direct effects on grain yield. These traits are accordingly proposed as reliable selection criteria for improving grain yield in maize.

Efficacy of Varied Liquid Microbial Formulations on the Growth and Yield Performance of Mulberry (Morus indica L.)

K. R. Shashidhar — 2026-08-20

Optimising fertiliser application effectively boosts mulberry yields without degrading soil quality in high-density sericulture systems. A field experiment was conducted during 2021–22 and 2022–23 in farmers' fields at Gaddekannuru village, Kolar Taluk, Karnataka, by ICAR–Krishi Vigyan Kendra (KVK), Kolar, to evaluate the efficacy of different liquid microbial formulations on growth, yield, leaf quality, cocoon productivity, and the economics of mulberry (Morus indica L.). The treatments included the recommended dose of fertilisers (RDF) and farmyard manure (FYM) alone (T₁), RDF + Liquid Microbial Consortia (T₂), RDF + Arka Microbial Consortia (T₃), and RDF + Waste Decomposer Solution (T₄), with the microbial formulations applied through drip irrigation at 8 and 25 days after pruning. Pooled data from two consecutive years revealed significant differences among the treatments. Among the treatments, T₂ (RDF + Liquid Microbial Consortia) recorded the highest number of branches (15.40 per plant), leaves (26.36 per branch), leaf yield (1.302 kg per plant and 120.51 q per ha per crop), and cocoon yield (457.96 kg per ha). It also produced superior leaf quality, with the highest leaf moisture content (77.50%), moisture retention capacity (71.90%), total chlorophyll (45.80%), protein (25.10%), and carbohydrate content (16.65%). Economic analysis indicated that T₂ generated the highest gross return (183,184 per ha), net return (132,734 per ha), and benefit–cost ratio (3.63), followed by T₃ (RDF + Arka Microbial Consortia). The results revealed that combining liquid biofertilisers with standard nutrient recommendations significantly improved mulberry biomass, leaf nutritive value, silkworm cocoon output, and net farm profits. The application of liquid microbial consortia through drip irrigation represents a sustainable nutrient-management approach that enhances fertiliser-use efficiency, reduces dependence on chemical fertilisers, and promotes environmentally sustainable sericulture.

Influence of Various Levels of IBA and NAA on Shoot Development and Survival of Stem Cuttings in Dragon Fruit

Ravi Patel — 2026-08-20

Dragon fruit (Hylocereus costaricensis) is a high-value, drought-tolerant cactus fruit whose commercial expansion in India is presently constrained by the poor and inconsistent availability of quality planting material. Since the crop is propagated almost entirely through stem cuttings, a field-cum-nursery experiment was conducted during 2025–26 at the Department of Fruit Science, College of Horticulture, C.S. Azad University of Agriculture and Technology, Kanpur (U.P.), to determine a reliable auxin schedule for rooting. Thirteen treatments, comprising three levels each of Indole-3-butyric acid (IBA at 1000, 2000 and 3000 ppm) and Naphthalene acetic acid (NAA at 100, 200 and 300 ppm), six IBA × NAA combinations, and an untreated control, were laid out in a Randomised Block Design with three replications. Cuttings treated with IBA at 3000 ppm consistently gave the quickest and most vigorous response, with root initiation in 16.53 days and sprouting in 9.39 days, compared with 22.90 and 17.33 days, respectively, in the control. The same treatment produced the highest rooting (53.20% at 60 days after planting), the longest roots (20.13 cm) and greatest root number (40.95) at 90 days, the tallest shoots (14.20 cm), and the best survival of rooted cuttings (90.12%), and remained statistically on par with IBA at 2000 and 1000 ppm across most parameters. NAA alone was distinctly less effective than IBA, and the IBA + NAA combinations did not improve upon IBA used alone. On the basis of these results, a quick-dip treatment with IBA at 3000 ppm (or, where cost is a constraint, 1000–2000 ppm) can be recommended for the commercial nursery propagation of dragon fruit through stem cuttings.

Diversity and Molecular Characterization of Fungal Pathogens Associated with Paddy in the Cauvery Delta Region

K. Balamurugan — 2026-08-19

Fungal diseases severely threaten rice productivity and food security across the Cauvery Delta. This study investigated the prevalence, morphological variation, pathogenicity, and molecular identities of three primary fungal pathogens Bipolaris oryzae, Pyricularia oryzae and Rhizoctonia solani collected across Tamil Nadu and Karaikal U.T. Field surveys revealed wide spatial variation in disease intensity, with maximum percent disease index (PDI) recorded for sheath blight (54.00% in Nannilam), blast (42.34% in Aduthurai) and brown spot (30.40% in Pattukkottai). In vitro characterisation of ten isolates per species demonstrated notable diversity in mycelial growth rates, colony pigmentation, conidial features, and sclerotial formation. Controlled greenhouse evaluations on susceptible rice cultivar BPT-5204 confirmed varying degrees of virulence among isolates, identifying Bo₈ (mean PDI 28.95%), Pg₇ (mean PDI 38.99%) and Rs₆ (mean PDI 36.85%) as the most aggressive pathotypes for brown spot, blast, and sheath blight, respectively. PCR amplification and Sanger sequencing of the ribosomal DNA internal transcribed spacer (rDNA-ITS) region definitively confirmed species identities for the hyper-virulent isolates: B. oryzae Bo₈ (558 bp; ON556554), P. oryzae Pg₇ (541 bp; ON556555) and R. solani Rs₆ (514 bp; ON556551). These characterised pathotypes provide critical reference strains for regional resistance breeding and targeted disease management strategies.

Integrating Multi-omics and Artificial Intelligence for Next-generation Crop Improvement: Advances, Constraints and Future Directions

Shweta — 2026-08-19

Crop improvement increasingly depends on extracting useful breeding signals from data that span DNA sequence variation, gene regulation, molecular phenotypes, high-throughput field measurements and environmental exposure. Multi-omics can connect genotype to phenotype through intermediate biological layers, while artificial intelligence (AI) and machine-learning methods can model nonlinear, high-dimensional relationships that are difficult to represent with conventional approaches. Yet greater data volume and model complexity do not automatically translate into greater genetic gain. This critical narrative review evaluates how genomics, pangenomics, transcriptomics, epigenomics, proteomics, metabolomics, phenomics and environmental covariates are being integrated with statistical learning, machine learning and deep learning for crop improvement. Literature was selected from accessible scholarly databases and indexes through 13 June 2026, with emphasis on peer-reviewed studies that permit evaluation of predictive value, biological interpretation and breeding relevance. The evidence is strongest where additional modalities capture non-redundant information that is biologically proximal to the target trait or environment, as demonstrated in hybrid prediction, stress adaptation, grain-quality analysis and environment-aware genomic prediction. Conversely, classical genomic best linear unbiased prediction and related models remain competitive in many settings, particularly when sample size is modest, relationships among individuals dominate prediction, or nonlinear signal is weak. Reported AI advantages are sensitive to validation design, relatedness between training and test sets, tissue and developmental stage, environmental transfer, missing modalities and hyperparameter tuning. Pangenomes, single-cell regulatory maps and interpretable multimodal models broaden the biological search space, but evidence for routine breeding utility remains less mature than their mechanistic promise. The most defensible path forward is therefore not unrestricted model escalation, but decision-focused integration: biologically informed feature representation, prospective multi-environment validation, explicit uncertainty, robust missing-data handling and functional validation of discovered mechanisms. Multi-omics and AI are most likely to accelerate crop improvement when evaluated against breeding decisions and realised genetic gain rather than prediction accuracy alone.

Combining Ability Analysis for Seed Yield and Associated Traits in Indian Mustard (Brassica juncea L. Czern & Coss.)

Soyal Davalasab Wathar — 2026-08-14

Indian mustard belongs to the family Brassicaceae and the genus Brassica and is a major oilseed crop cultivated in India. Worldwide, it is the third-ranked oilseed crop in terms of consumption after palm oil and soybean. However, productivity remains below its potential because of various biotic and abiotic stressors coupled with a narrow genetic base, highlighting the need to broaden the genetic base and exploit heterosis to develop superior cultivars. Therefore, in the present study, general and specific combining ability analyses were conducted to assess the combining abilities of the parents and the performance of hybrids at the Zonal Agricultural Research Station, Morena, Rajmata Vijayaraje Scindia Agricultural University, Gwalior, M. P., India, during Rabi 2026. During the present investigation, 16 yield-attributing traits were evaluated using 10 lines, 3 testers, and their thirty F1 hybrids developed through a line × tester mating design to estimate the magnitude and direction of combining abilities. Among the lines and testers, GCA effects showed that parents viz., Pusa Bold, Rohini, Varuna, and Vardhan were good general combiners because they exhibited desirable negative and highly significant GCA effects for days to 50% flowering, days to siliquae initiation, and plant height. However, Pusa Bold was recognized as a good general combiner because it displayed positive and highly significant GCA effects for the maximum number of quantitative traits, including seed yield per plant and harvest index. The cross-combination Pusa Jagannath × PAB-2014-4 had the highest SCA effect for seed yield per plant, biological yield, number of siliquae per plant and number of primary branches per plant, while Maya × PAB-2014-8 showed high SCA effects for seed yield per plant, biological yield and number of siliquae on the main raceme.

Rapid Micropropagation Using Nodal Explants of Bacopa monnieri (L.) Pennell: An Endangered Medicinal Plant

Nikita D. Kokare — 2026-08-14

This study evaluated an in vitro micropropagation protocol for Bacopa monnieri using nodal explants. Healthy nodal segments were collected from nursery-grown plants, surface sterilised, and cultured on Murashige and Skoog medium supplemented with different plant growth regulators. The sterilisation sequence consisted of 1% Bavistin for 10 min, 70% ethanol for 30 s, and 0.01% mercuric chloride for 5 min, followed by repeated rinsing with sterile distilled water. For shoot initiation, nodal explants were cultured on MS medium containing different concentrations of 6-benzylaminopurine. Among the tested treatments, MS medium supplemented with 3.0 mg/L BAP showed the strongest shoot initiation response, with bud break observed within 7–10 days. For shoot multiplication, the best response was obtained on MS medium supplemented with 4.0 mg/L BAP and 0.5 mg/L NAA. Elongated shoots were transferred to half-strength MS medium containing IBA at 0.1–0.4 mg/L for root induction, and the highest rooting response was observed at 0.4 mg/L IBA. Rooted plantlets were subsequently acclimatised through primary and secondary hardening before transfer to soil conditions. The study indicates that nodal explants can be used for rapid in vitro propagation of B. monnieri, although further validation with additional replication and statistical analysis is required. All experiments were conducted in triplicate, and the data were subjected to appropriate statistical analysis.

Multivariate Characterization and Nutritional Profiling of Advanced Soybean (Glycine max (L.) Merr.) Breeding Lines Using Atomic Absorption Spectroscopy

P. S. Raja — 2026-08-13

Soybean (Glycine max (L.) Merr.) is a leguminous crop known for its high nutritional potential and its capacity to address prevalent nutrient deficiencies through breeding and biofortification strategies. The current study assessed the mineral composition of 97 advanced soybean breeding lines using atomic absorption spectroscopy (AAS) to measure two macronutrients - calcium (Ca) and magnesium (Mg) - and four micronutrients - iron (Fe), zinc (Zn), copper (Cu) and manganese (Mn). The observations were subjected to correlation analysis, principal component analysis (PCA) and hierarchical clustering, and a nutritional index was calculated. Considerable differences were observed in mineral distribution profiles among the genotypes and among the minerals. Calcium showed the highest variability, while magnesium displayed more consistent accumulation. A weak to moderate positive relationship was detected among several micronutrients, especially Fe–Zn, Fe–Cu and Fe–Mn, suggesting potential for simultaneous enhancement of multiple nutritional traits in the breeding programmes. PCA and hierarchical clustering categorised the genotypes into distinct groups based on their mineral composition, confirming noticeable diversity within the breeding material. PS 26 had high calcium content, PS 1505 showed high iron content, PS 1733 had high magnesium content and NRC 142 had high copper content according to these observations. The nutritional index highlighted PS 1670, PS 1521, PS 1734, EC 69729 and NRC 142 as outstanding genotypes with balanced and above-average levels of overall mineral composition as indicated by the nutritional index. These results demonstrate informative genetic diversity in seed mineral content and identify promising donor lines for soybean biofortification and nutrient enhancement. The study offers essential insights for the development of mineral-rich soybean cultivars aimed at promoting sustainable agriculture and improving human nutrition.

Character Association and Path Coefficient Analysis of Yield and Quality Traits in Early and Mid-late Sugarcane (Saccharum spp. Complex)

Hitesh — 2026-08-12

The genetic improvement of sugarcane (Saccharum spp. complex) for cane and sugar yield relies heavily on understanding the intricate associations among yield-attributing traits and partitioning their causal direct and indirect effects. This study evaluated 30 diverse sugarcane genotypes (27 advanced generation clones and 3 commercial standards) using a randomised block design with three replications to estimate phenotypic and genotypic correlations, alongside path coefficients, for seventeen morphological and biochemical quality traits. Correlation studies revealed that cane yield had a significant and positive association with CCS (t/ha) followed by single cane weight, stalk length, number of millable canes at harvest and Brix % at 8^th month. Path analysis revealed that the characters, viz., Pol % at 8^th month, CCS % at 10^th month, CCS (t/ha), CCS % at 8^th month, Brix % at 10^th month, single cane weight, number of millable canes at harvest, number of tillers at 120 DAP and stalk length recorded positive direct effects on the dependent variable, i.e. cane yield, while the other traits also showed indirect positive effects on cane yield through these characters, indicating that these characters are major contributing traits to cane yield in sugarcane. Sugarcane clones viz., 15-1805, 16-266 and 16-123 were significantly or numerically superior to the best check Co-0238 for both cane yield and quality attributes. These clones require further testing in multi-locational trials to sustain sugarcane productivity.

CRISPR and Artificial Intelligence in Crop Improvement: A Critical Synthesis for Precision Plant Breeding

Anilkumar Lalasing Chavan — 2026-08-10

Clustered regularly interspaced short palindromic repeats (CRISPR)-based genome editing and artificial intelligence (AI) are increasingly presented as a unified route to precision plant breeding. Their convergence is scientifically plausible but unevenly demonstrated. CRISPR systems can create targeted sequence changes, whereas AI can prioritise candidate genes, integrate genomic and phenomic data, optimise guide RNAs and editors, predict editing outcomes, and support iterative genotype-to-phenotype learning. This critical narrative review evaluates the evidence linking these capabilities across the crop-improvement pipeline. Literature published from 1 January 2012 to 5 June 2026 was selected through transparent searches of accessible scholarly indexes and bibliographic resources, followed by citation tracking, metadata verification and thematic appraisal. Evidence is strongest for CRISPR-mediated improvement of discrete, biologically well-characterised traits, including disease resistance, quality attributes, plant architecture and selected stress responses. AI has also achieved useful performance in phenotyping, genomic prediction and CRISPR design, but superiority over conventional statistical or rule-based approaches is not consistent across datasets, species or prediction tasks. Direct evidence for fully integrated, AI-guided CRISPR breeding programmes that deliver stable field performance remains limited. Major constraints include uncertain causal target identification, small and non-representative training datasets, poor transferability across genetic backgrounds, polyploidy, genotype-by-environment interaction, transformation and regeneration bottlenecks, incomplete detection of unintended outcomes, and heterogeneous regulation. The most defensible interpretation is therefore that AI and CRISPR are complementary components of an emerging design-build-test-learn framework rather than a mature autonomous breeding platform. Progress will depend on plant-specific benchmark datasets, prospective validation, multi-environment field trials, interoperable data standards, equitable access to transformation and computational infrastructure, and governance focused on the properties and evidence of resulting products. Their integration can accelerate precision breeding, but biological causality, experimental validation and breeding judgement remain indispensable.

Application of Indole-3-acetic Acid (IAA), Indole Butyric Acid (IBA) and Naphthalene Acetic Acid (NAA) for Enhancing Clonal Propagation of Fig (Ficus carica L.)

C. Muruganandam — 2026-08-08

The present study entitled “Application of Indole-3-acetic acid (IAA), Indole Butyric Acid (IBA) and Naphthalene Acetic Acid (NAA) for Enhancing Clonal Propagation of Fig fruit (Ficus carica L.)” was conducted during 2022–2023 at a farmer’s nursery in Erode District, Tamil Nadu, to evaluate the influence of experiment was laid out in a Completely Randomised Design (CRD) with ten treatments and three replications, using 450 cuttings of the drought-tolerant ‘Afghan’ cultivar. Treatments included three concentrations each of Indole-3-butyric acid (IBA), Indole-3-acetic acid (IAA) and Naphthalene acetic acid (NAA), along with an untreated control. The basal ends of the cuttings were subjected to a 30-second quick dip in the respective plant growth regulator solutions, and rooting was carried out under mist-chamber conditions. Data were statistically analysed using standard methods and critical differences were determined at the 5% level of significance. The highest values were recorded with IBA @ 3500 ppm (T3), which showed the earliest sprouting (10.70 days), maximum shoot length (21.43 cm), fresh shoot weight (46.44 g), dry shoot weight (35.63 g), shoot diameter (12.98 mm), leaf number (10.59), leaf dimensions (length 15.56 cm, width 13.28 cm) and survival rate (87.88%). The findings suggest that IBA at 3500 ppm is optimal for efficient clonal propagation of fig hardwood cuttings, as the enhanced growth and survival of treated cuttings may be attributed to auxin-mediated stimulation of physiological processes, including root initiation, cell elongation and nutrient uptake.

Morphological Characterization of Genotypes for Seed Yield and Its Component Traits of Indian Mustard (Brassica juncea L.)

Adarsh Mishra — 2026-08-07

The present investigation evaluated fifteen Indian mustard (Brassica juncea L.) genotypes for seed yield and associated component traits during the Rabi season of 2025-26 at the Agricultural Research Farm, Prof. Rajendra Singh (Rajju Bhaiya) University, Naini, Prayagraj, Uttar Pradesh. The experiment was laid out in a Randomised Block Design with three replications. Eleven quantitative traits were recorded and analysed for variability, heritability, genetic advance, correlation and path coefficient effects. Analysis of variance showed highly significant differences among genotypes for most traits, indicating the presence of exploitable genetic variability. High genotypic and phenotypic coefficients of variation were recorded for the number of siliquae per plant, number of siliquae per shoot and number of seeds per plant. Broad-sense heritability was highest for the number of siliquae per plant, number of siliquae per shoot and plant height at 90 DAS, and these traits also showed high genetic advance as a percentage of the mean. Seed yield per plot showed strong positive genotypic associations with the number of siliquae per shoot, number of seeds per siliqua and number of seeds per plant. Path coefficient analysis indicated that plant height at 90 DAS, number of siliquae per shoot and number of siliquae per plant were important contributors to seed yield at the genotypic level. The findings indicate that these traits may support selection for yield improvement in Indian mustard under the studied conditions.

Methodology of Nutritional and Yield Evaluation of Advanced Potato Clones for Eastern Indo-gangetic Plains of India

Sarala Yadav — 2026-08-06

Potato (Solanum tuberosum L.) is a modified stem crop of global significance and is recognised as one of the most important vegetable commodities worldwide. This study evaluated ten advanced potato clones (PS/19-02, PS/19-04, PS/19-12, PS/19-24, PS/19-26, PS/19-31, PS/19-41, PS/19-43, PS/19-44, and PS/19-50), together with five control varieties (Kufri Lohit, Kufri Manik, Kufri Lalit, Kufri Lalima, and Kufri Neelkanth) for yield, quality and nutritional traits relevant to breeding red-skinned varieties suitable for the Eastern Indo-Gangetic Plains of India. Field experiments were conducted at the ICAR-Central Potato Research Institute, Regional Centre, Patna, Bihar, and laboratory analyses were conducted at ICAR-CPRI, Shimla, during 2023–2024 and 2024–2025. The trials were laid out in a Randomised Block Design (RBD) with three replications. Potato tubers were planted on ridges at a spacing of 20 cm (plant-to-plant) × 60 cm (row-to-row) and a depth of 4–5 cm. Two crop durations, 75 and 90 days were conducted. The measured parameters included total tuber yield (t/ha), marketable tuber yield (t/ha), dry matter content (%) and nutritional composition (Fe, Zn, carotenoids, ascorbic acid and anthocyanins). Superior performance was observed in clone PS/19-50, which recorded a marketable tuber yield of 32.51 t/ha at 75 days and in PS/19-41, which achieved 36.88 t/ha at 90 days. These two clones exhibited low storage losses under ambient conditions (7.37% for PS/19-50 and 17.4% for PS/19-41). Nutritional profiling revealed high mineral contents with Fe at 34.65 ppm in PS/19-24 and Zn at 25.31 ppm in PS/19-50. Key selection traits included ovoid-to-round tuber shape, red skin colour, pigmented flesh ranging from dark to light red, shallow eyes, and desirable organoleptic qualities. The primary objective was to assess the yield and nutritional performance of advanced potato clones to develop red-skinned varieties adapted to the Eastern Indo-Gangetic Plains of India.

Assessment of Combining Ability and Gene Action for Yield and Yield-contributing Traits in Sunflower (Helianthus annuus L.)

Sharanabasava Sangamesh Ambakkanavar — 2026-08-06

Aims: To evaluate combining ability, determine the nature of gene action governing yield and yield-contributing traits, and identify superior parents and promising hybrid combinations in sunflower (Helianthus annuus L.).

Study Design: Line × tester mating design.

Place and Duration of Study: Oilseeds Research Station, Latur, Maharashtra, India, during kharif 2025 (hybrid development) and rabi 2025–26 (field evaluation).

Methodology: Six cytoplasmic male-sterile (CMS) lines and seven restorer lines were crossed in a line × tester mating design to generate 42 hybrids. The resulting hybrids, together with their 13 parents and three standard checks, were evaluated in a randomised block design with two replications for ten agro-morphological and quality traits. The data were subjected to analysis of variance, line × tester analysis to estimate general and specific combining ability, and assessment of gene action following Kempthorne (1957).

Results: Significant variation was observed among the 58 genotypes for all ten traits studied, indicating sufficient genetic variability for effective selection and hybrid development. Combining ability analysis revealed significant GCA and SCA effects for most traits, with SCA variance exceeding GCA variance and indicating the predominance of non-additive gene action. CMS-249A and CMS-47A exhibited desirable GCA effects for several yield-related traits, whereas EC-601924 and EC-601751 were superior restorers. The hybrid combinations DSP-11A × EC-601924, CMS-249A × RHAGPR-3, and CMS-10A × EC-601751 expressed high SCA effects together with desirable performance for yield and related traits, indicating their suitability for hybrid breeding.

Conclusion: Both additive and non-additive genetic effects contributed to the inheritance of yield and yield-contributing traits, although non-additive gene action was predominant. The identified superior parents and hybrids may be utilised in sunflower hybrid-breeding programmes to develop high-yielding hybrids.

Evaluation of Chickpea (Cicer arietinum) Germplasm for Yield and Yield Attributing Traits

Surbhi Gour — 2026-08-05

The present study was conducted using different chickpea genotypes during the Rabi 2022–23 season at the Field Experimentation Centre, Department of Genetics and Plant Breeding, Naini Agricultural Institute, Sam Higginbottom University of Agriculture, Technology and Sciences, Uttar Pradesh. The experiment was laid out in a randomised block design with three replications to estimate genetic variability parameters and conduct correlation and path analyses for thirteen quantitative traits. Analysis of variance indicated highly significant differences among the genotypes at the 1% probability level for all traits. Phenotypic coefficients of variation (PCV) were higher than genotypic coefficients of variation (GCV) for all traits, indicating environmental influence. Most traits exhibited high heritability, except days to 50% flowering. High heritability coupled with high genetic advance as a percentage of the mean was observed for the number of primary branches, number of secondary branches, number of pods per plant, pod length, number of seeds per pod, biological yield per plant, seed index and harvest index. Correlation and path coefficient analyses indicated that plant height, days to maturity, number of seeds per pod, biological yield per plant, seed index and harvest index had positive direct relationships with seed yield per plant. These findings indicate that effective selection based on these traits may improve chickpea seed yield.