The market demand for uniformity and productivity of commercial carrot roots has prioritized hybrid materials over open-pollinated varieties. In this sense, the objective of this work was to estimate the combining ability of carrot genitors for root productivity and resistance to leaf scorch. The experiments were conducted in Gama, DF, in the agricultural years 2012/13 and 2013/14. We evaluated 33 carrot hybrids, originated from crosses between three male-sterile populations, with 11 male-fertile S2 lines, all the genitors being of tropical origin. At 90 days after sowing, the severity of the leaf blight disease was estimated in the plots. At 100 days after sowing, harvesting was performed and root yield characters were evaluated. Analysis of variance and partial diallel analysis were performed for each year and jointly for both years. It was found that additive and non-additive genes are important in the manifestation of root yield and leaf blight resistance traits in carrot hybrids. The male-sterile parents with higher overall combining ability for root productivity are strains LM-649 and LM-650 and, among the male-fertile, strain LM-555-2-2. The best hybrids for root yield and leaf blight resistance are LM-649 × LM-555-11-1, LM-650 × LM-555-7-1 and LM-650 × LM-554-8-1.

Leaf litter decomposition and carbon release patterns in five homegarden tree species of Kumaun Himalaya viz. Ficus palmata, Ficus auriculata, Ficus hispida, Grewia optiva and Celtis austalaris were investigated. The study was carried out for 210 days by using litter bag technique. In the current investigation, the duration needed for desertion of the original biomass of diverse leaf litter varied from 150 to 210 days and specifies a varying pattern of decomposition and carbon release among the species. Grewia optiva took the longest time to decompose (210 days) while Ficus hispida decomposed more quickly than rest of the species (150 days). The relative decomposition rate (RDR) was reported highest in Ficus hispida (0.009-0.02 g-1d-1) and lowest in Grewia optiva (0.008-0.004 g-1d-1). Carbon (%) in remaining litter was in the order: Ficus auriculata (24.4 %) >Ficus hispida (24.3%) > Celtis austaralis (19.8%) > Ficus palmata (19.7%) > Grewia optiva (19%). The relationship between percentage weight loss and time elapsed showed the significant negative correlation with carbon release pattern in all the species. Releasing nutrients into the soil through the decomposition of homegarden tree residuals is a crucial ecological function that also regulates the nutrient recycling in homegarden agroforestry practices.

In agriculture, crop yield and quality are critical for global food supply and human survival. Challenges such as plant leaf diseases necessitate a fast, automatic, economical, and accurate method. This paper utilizes deep learning, transfer learning, and specific feature learning modules (CBAM, Inception-ResNet) for their outstanding performance in image processing and classification. The ResNet model, pretrained on ImageNet, serves as the cornerstone, with introduced feature learning modules in our IRCResNet model. Experimental results show our model achieves an average prediction accuracy of 96.8574% on public datasets, thoroughly validating our approach and significantly enhancing plant leaf disease identification.