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Climate Smart Agriculture (CSA) is an integrated approach that transforms the agri-food system and mitigates climate change. They connect the use of farming techniques in order to increase food productivity, Climate resilient practice, and decrease greenhouse gases. The main aim of this review is to demonstrate the typical interrelationship between climate and agriculture and get knowledge regarding this. In addition, focus on traditional agriculture along with its mitigating measures for climate agriculture. They approach collective development practices through the efforts of individuals in order to manage agriculture and the food system under climate change. Therefore, there is an increasing need for a strategic plan to balance agriculture and the food system.

Broccoli (Brassica oleraceae var. Italica) belongs to the family cruciferae which is mainly used as vegetable at its tender stage. The study was conducted to evaluate the morphological, phenological, head and yield traits of broccoli genotypes at Karma Innovative Research and Development Stations of Kathmandu, Kavre and Kaski district of Nepal from September 2019 to March 2020. The experiment was laid out on Randomized Complete Block Design with four replications at each location. Genotypes, location and interaction between them showed significant variation on almost all parameters. BL-17001, BL-18012 and Centauro genotypes were observed with no lateral heads, which means low yield than other varieties. BL-16003 was observed with maximum yield (1.0 kg/plant at Kathmandu and kavre and 0.9 kg/plant at Kaski) at all locations comparing to other genotypes. Among high-yielding genotypes (BL-16003 and BL-18009) BL-16003 found as early maturing and also had lateral heads so, it can also be used for multi-harvesting. In addition, the height of this genotype was in the lower range with highest number of leaves. Thus, BL-16003 is found as the promising genotype at all localities.

A field survey was conducted to study the factor that determines farmers’ decisions to adapt to climate change in Deurali and Agyouli V.D.Cs of Nawalparasi District. Altogether 180 household, 90 from each V.D.C were selected randomly for the study. A logit regression model was employed in the study. However, in order to measure the magnitude of the impact of the explanatory variables on the decision of the farmer to adapt to climate change marginal effects were computed. The study uses a binary dependent variable taking the value 1 if the farmer adapted to climate change and 0 otherwise. A farmer is considered to have adapted to climate change if he/she has employed at least one of the adaptation strategies such as early and late planting, use of drought resistant crops, zero tillage operation, crop diversification, use of mulching and composting of weeds to control water loss and conserving moisture in the field. This current research considers the following as potential factors determining farmers’ decisions to adapt to climate change; economically active members, education of the household head, farm size, annual cash earnings, access to credit, training and extension. Findings reveal that these factors influence farmers’ decisions to adapt to climate change in Nawalparasi District and marginal effects computed showed that per unit increase in these variables increased the probability of practicing different adaptation strategies by 4.3%, 31.4%, 3%, 1.5%, 17%, 66% respectively. The log likelihood was computed to be -43.45. Psuedo. R2 was calculated to be 39%.