Climate change is viewed as the main obstacle to agricultural development in developing countries. The high dependence on agriculture and allied sectors makes many countries vulnerable to the climate change phenomenon. There is a gap in macro and micro-level understanding of climate change. Thoughtful farmers’ perceptions and impacts of climate change on farming are fundamental for developing various mitigation and adaptation strategies. Therefore, the main aim of the present study was to understand the pattern of climate variability, farmers’ perceptions about climate change, and farmers’ adaptation strategies based on their socio-cultural background in the villages of Goa, on the west coast of India. The results reveal that about 62% of the sampled farmers have experienced climate change in terms of meteorological indicators such as increased average temperature, decreased total rainfall, delayed onset of monsoon, and an increase in the length of the summer season. The temperature trend analysis (0.009 °C/year) validated farmers’ perceptions, while the perception of rainfall differed (−1.49 mm/year). Farmers are convinced that climate change has affected their farming (declining crop and livestock productivity, water depletion, and other related farm operations). They strive to adapt to climate change through crop diversification, an integrated crop-livestock system, contingency crop planning, and the adaptation of new crops and varieties. This study could be helpful for policymakers to establish a climate-resilient agriculture system by ensuring timely availability of farm inputs, accurate weather forecasting, and encouraging insurance products for crop and livestock enterprises, which will help farmers cope with the changing climate to enhance their income and economic wellbeing. Further, adaption of integrated farming, agroforestry, and indigenous technical knowledge is imperative to combat the ill effects of climate change.

The measurement of sustainability in terms of social, economic, and ecological indicators significantly influences the achievement of sustainable development goals. This paper presents a sustainable livelihood security index (SLSI) by selecting 20 indicators and positions them within the ecological, economic, and social dimensions of sustainable development for the Indian west coast. These indicators were first normalized and, using estimated weights, indices were computed. Important indicators were shortlisted by a two-step process, namely, principal component analysis and linear and nonlinear weighted scores. The results revealed that indicators such as forest cover, net sown area, milk availability, groundwater availability, land productivity, food grain availability, rural road connectivity, villages electrified, and land degradation were found to be important indicators. Kerala was found as the most developed state followed by Gujarat, Karnataka, Maharashtra, and Goa in linear and non-linear weighted scoring. The study identifies the Jamnagar, Junagadh, Kachchh, Ratnagiri, and Sindhudurg districts as the districts with the highest priority for development through investment and policy interventions. The study concludes that the west coast region, in terms of its sustainable development levels, improved significantly with a focus on low-SLSI districts by considering ecological, economic, and social dimensions in planning for technological development and dissemination.

Climate change impacts agricultural productivity and farmers’ income, integrated farming systems (IFS) provide a mechanism to cope with such impacts. The nature and extent of climatic aberrations, perceived impact, and adaptation strategies by the farmers reduce the adverse effects of climate change on agriculture. Therefore, a study was conducted to investigate 2160 IFS farmers about their perceptions of climate change, barriers, and the likelihood of adapting to the negative impacts of climate change. The study observed an increasing rainfall trend for humid (4.18 mm/year) and semi-arid (0.35 mm/year) regions, while a decreasing trend was observed in sub-humid (−2.02 mm/year) and arid (−0.20 mm/year) regions over the last 38 years. The annual rise in temperature trends observed in different ACZs varied between 0.011–0.014 °C. Nearly 79% of IFS farmers perceived an increase in temperature, decreasing rainfall, variability in the onset of monsoon, heavy terminal rains, mid-season dry spells, and frequent floods due to climate change. The arid, semi-arid, sub-humid, and humid farmers’ adapted several measures in different components with an adaption index of 50.2%, 66.6%, 83.3%, and 91.6%, respectively. The majority of the IFS farmers perceived constraints in adopting measures to climate change, such as meta barriers, capacity barriers, and water barriers. Therefore, we infer that educated farmers involved in diversified and profitable farms with small to medium landholdings are concerned more about climate change in undertaking adaptive strategies to reduce the environmental impact of climate change.

The oil palm is a tropical oil bearing tree. Recently EST-derived SNPs and SSRs are a free by-product of the currently expanding EST (Expressed Sequence Tag) data bases. The development of high-throughput methods for the detection of SNPs (Single Nucleotide Polymorphism) and small indels (insertion / deletion) has led to a revolution in their use as molecular markers. Available (5452) Oil palm EST sequences were mined from dbEST of NCBI. CAP3 program was used to assemble EST sequences into contigs. Candidate SNPs and Indel polymorphisms were detected using the perl script auto_snip version 1.0 which has used 576 ESTs for detecting SNPs and Indel sites. We found 1180 SNP sites and 137 indel polymorphisms with frequency 1.36 SNPs / 100 bp. Among the six tissues from which the EST libraries had been generated, mesocarp had high frequency of 2.91 SNPs and indels per 100 bp whereas the zygotic embryos had lowest frequency of 0.15 per 100 bp. We also used the Shannon index to analyze the proportion of ten possible types of SNP/indels. ESTs from tissues of normal apex showed highest values of Shannon index (0.60) whereas abnormal apex had least value (0.02). The present report deals the use of Shannon index for comparing SNP/ indel frequencies mined from ESTlibraries and also confirm that the frequency of SNP occurrence in oil palm to use them as markers for genetic studies.