Dr. Y.S.R Horticultural University

Understanding the genotype × environment interaction (GEI) on the performance and stability of curcuminoids among turmeric genotypes across production environments is essential for selecting suitable genotypes for different production environments. In the present investigation, 21 turmeric genotypes of various geographical locations in India were assessed for curcuminoids (CUR-curcumin, DMC-demethoxycurcumin, and BDMC-bis demethoxycurcumin) under three environmental conditions viz, green house, vertical structures and open field. The analysis of variance indicated significant GEI effects on curcuminoids, underscoring the importance of GEI on genotype performance. In vertical structures, IISR Pragati and Waigon Turmeric were found to be superior for all three curcuminoids. In greenhouse conditions, CIM Pitambar, CO 3, and Acc. 1545 were superior for BDMC, while CIM Pitambar, IISR Prathiba, and IISR Pragati excelled for DMC, and Acc. 1545 for CUR. Under field conditions, Waigon Turmeric recorded higher BDMC and DMC, while Roma, Acc. 1545, and IISR Prathiba had the highest CUR. Our findings revealed that the curcuminoids relative ratio among the genotypes, which grouped into four patterns, was primarily influenced by genotype rather than environment. The promising genotypes for curcuminoids across the production environments were Waigon Turmeric, Rajendra Sonali, Roma, IISR Prathiba, Acc. 1545, NDH 8, IISR Pragati, and CIM Pitambar. Additionally, IISR Pragati for BDMC, Acc. 69/22/5/I3 for DMC, and Rajendra Sonali for CUR exhibited both superior performance and greater stability compared to other genotypes. In the present study, Field conditions, followed by greenhouse conditions, were found to be the best for all three curcuminoid across three production environments. These findings are crucial for extraction industries and farmers to choose the best genotypes and suitable production environments for targeted production of higher curcuminoids in turmeric.

The diamond back moth, Plutella xylostella (Linneaus), is a serious pest of cruciferous crops and is notorious for its rapid development of resistance to conventional insecticides. The present study evaluated the antifeedant, larvicidal and developmental inhibitory effects of sweet flag, Acorus calamus Linneaus methanolic extract and its green-synthesized silver nanoparticles (AgNPs) against third instar larvae of P. xylostella. The methanolic extract exhibited strong dose-dependent bioactivity with low AI50 (0.053%),LC50 (0.031%) and I50 (0.024%) values. The biosynthesized AgNPs, confirmed by UV–Vis spectroscopy(SPR peak at 420 nm), DLS (30–80 nm), zeta potential analysis (–35 mV), FE-SEM (spherical morphology)validating successful nanoparticle fabrication showed enhanced insecticidal efficacy, recording completelarval mortality and total suppression of adult emergence at lower concentrations, with AI50, LC50 and I50 values of 6.877, 9.974 and 54.183 ppm, respectively. The results indicate that both A. calamus extract and its nano formulation possess strong insecticidal potential and may serve as eco-friendly alternatives to synthetic insecticides for the management of P. xylostella.

Russeting is one of the most important horticultural problemsin apple production worldwide. Fruit cultivars differ generally in their susceptibility to russet. Apple variety “Red Velox” lately introduced in Himachal Pradesh is very prone to russeting. Hence, an experiment was conducted during 2021–2022 at Regional Horticultural Research and Training Station, Mashobra, Shimla, to investigate the effect of different concentrations and timings of gibberellins A 4 and A 7 (GA 4 + 7 ) + 6‐benzyladenine (BA) application on russet control and quality of “Red Velox” apple. Minimum russet formation on skin surface of apple (1.21%) was observed when GA 4 + 7 + BA at 10 ppm were sprayed at full bloom and petal fall stage. Physical parameters, viz., fruit weight (193.00g), fruit size in terms of length and breadth (66.88 mm × 73.20 mm) and fruit volume (385.33 cc), fruit firmness (9.10 kg cm −3 ), and total sugar (10.13%), were recorded maximum with three sprays of GA 4 + 7 + BA at 10 ppm at petal fall and later at 10‐day intervals. Fruit shape index (0.96) was recorded maximum in plants treated with GA 4 + 7 + BA at 25 ppm at petal fall and full bloom stage. However, titratable acidity (0.42%) was maximum with two sprays of GA 4 + 7 + BA at 1 ppm at petal fall and later at 10‐day interval. Ascorbic acid content (6.33 mg/100g) was maximum in plants treated with three sprays of GA 4 + 7 + BA at 2.5 ppm at petal fall and later at 10‐day interval. Thus, a targeted plant growth regulators regime robustly suppresses russet and elevates overall fruit quality in this russet‐susceptible cultivar “Red Velox.”

The biodiversity of agricultural pests and diseases has changed significantly due to climate change, posing an immense challenge to sustainable crop production. Finger millet, the third most important millet, is typically cultivated in arid, semi-arid, hilly and tribal provinces across Africa and Asia. However, its growth and yield are severely threatened by blast disease, a destructive condition caused by the filamentous ascomycete fungus Magnaporthe grisea. Because the pathogen produces rapidly evolving virulence genes, blast resistance frequently breaks down, leading to yield instability in all provinces where finger millet is cultivated. Blast disease is estimated to reduce yield by 28 %–36 % on average and in extreme cases, it can result in total crop loss. The disease affects the crop in three progressive stages: leaf blast, neck blast and finger blast. In comparison to leaf blast, the loss is higher in neck blast and finger blast, which drastically decrease grain size and number and in extreme cases, this results in total panicle sterility. In this current review, we emphasized the significance of finger millet and its susceptibility to blast disease, pathogen, field screening technique, genetic resources available at different research organizations involved in the advancement of finger millet in the world, genetic diversity of blast pathogen, conventional and molecular tools like transcriptome analysis and transgenesis that have been employed to increase finger millet's resistance to blast disease and explored prospective future paths for the creation of new blast-resistant finger millet cultivars.

A field experiment on mango cv. Banganpalli evaluated the combined effects of drip irrigation (control, 75%, 100%, and 125% ETc), fertigation (50%, 75%, 100% recommended N and K; 100% N-K via soil application) and mulching on fruit quality at harvest and post-harvest behaviour under ambient storage. Drip irrigation at 100–125% ETc with 75–100% N-K fertigation and mulching significantly improved fruit quality attributes: higher TSS (up to 19.60 °Brix), total sugars (up to 15.96%), non-reducing sugars, ascorbic acid (up to 7.56 to 10.4 and 5.00-6.28 mg 100 g⁻¹, respectively), Brix: acid ratio (up to 83.26), and lower titratable acidity. These treatments delayed the climacteric peak, suppressed respiration rate (O₂ uptake and CO₂ evolution), retained higher fruit firmness (up to 3.3 kg cm⁻²), slowed chlorophyll degradation (higher DA-index), and extended shelf life up to 14.75 days compared to conventional flood irrigation and soil fertilization (shelf life ~10–11 days). The study demonstrates that integrated drip irrigation (100–125% ETc) and fertigation (75–100% N-K) with mulching offer an effective pre-harvest strategy to optimize both eating quality and post-harvest life of mango cv. Banganpalli.

The experiment was planted on tomato were conducted at a private farm in Village in Kafr el-Sheikh city, Kafr el-Sheikh Governorate the North Delta region is considered one of the most important areas in Egypt affected by salts. Salinity is a significant constraint that limits tomato productivity and tomatoes are only moderately salt-tolerant. Five parental cultivars (Edkawy, Castle Rock, CLN2498E, SuperMarmand, Super Strain B). Diallel crosses to produce F1 hybrids, leading to evaluation of genotypes. The experiment was laid out in Completely Randomized Design (C.R.D.) with three replications, A two-factor pot experiment in a greenhouse (2022/2023 and 2023/2024), Factor A: 15 genotypes (5 parents + 10 hybrids) and Factor B: Four salinity treatments (control plus three salinity levels) Design with Each genotype-treatment combination replicated three times (total: 180 pots). Results Significant positive GCA for chlorophyll Castle Rock (P2) and SuperMarmand (P4) were strong general combiners. Strong SCA Hybrids such as P1×P3, P2×P3, and P3×P5 showed high SCA for chlorophyll and/or proline, revealing favorable specific combinations for stress tolerance through osmolyte accumulation. Na⁺/K⁺ Ratio and Ascorbic Acid SCA variances generally exceeded GCA, indicating non-additive gene action was predominant. Nevertheless, some parents displayed positive GCA effects for ascorbic acid content, while favorable SCA for reduced Na⁺/K⁺ ratio and increased ascorbic acid appeared in crosses such as P1×P2, P2×P3, and P4×P5. Yield Traits SCA mean squares surpassed GCA under all conditions; low GCA/SCA ratios (<0.12) reinforce the dominance of non-additive gene action for yield, highlighting the importance of heterosis and hybrid development Breeding Objectives Efforts focus on developing F1 hybrids with both high yield and improved tolerance to salinity by analyzing gene actions and inheritance.

Pedestrian detection has become a significant research focus in autonomous driving. Many investigation mechanisms have developed detection techniques using simple camera devices, which can affect the performance of detection as they produce low-quality images, such as RGB, especially in cases of imbalanced illumination and a lack of texture. The images produced by a thermal camera can retain quality for better detection in complex scenes. Popular works attained maximum accuracy in the detection of pedestrians in a few scenarios. However, there is scope to improve the efficiency of detection in critical scenarios, such as daytime and nighttime, as well as densely populated regions. To address this issue, this article presented Enhanced Pedestrian Detection for Autonomous Driving Using Multimodal Spatio-Contextual Deep Networks to enhance detection accuracy in broad scenarios. This approach is developed in the combination of multimodal data and deep networks. The useful features can be extracted during the pipeline process, which can improve detection accuracy. All input images are normalized into a standard $640 \times 640$ resolution. The contrast of the image is enhanced with the help of CLAHE. Further, the objects are detected using a pretrained R-CNN framework, and the latter model is adjusted with user-defined threshold values for improving the confidence of detection. This investigation was implemented in a user-friendly web application built using the Flask web framework. The web page allows researchers to upload and investigate the detection summary. The proposed approach can be further investigated in real-world applications.