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The dairy sector has been poised for fierce competitiveness due to the commercialization of the dairy sector and the presence of a global market size of 893 billion dollars. It has received a new dimension with the challenge of environmental sustainability. Considering all these challenges, the present research paper studies the major growth factors and the sustainable approach to dairy development in an emerging economy like India. Fifteen major dairy-developed states of India have contributed 90% of the milk production of the country examined from 2001 to 2019. The significance of key growth factors for dairy farming and the dairy value chain is assessed. The opportunity for sustainable dairying is examined. The authors have found that the growth factors of dairy farming and dairy value chain are significant by 1% through the fixed effect (FE) model and random effect (RE) model respectively. Indian dairy farming practices and their approach create optimism about environmental sustainability. The present study has observed a series of operational activities that are conducive to the triple bottom approach. With that, this study has mentioned strategies that can steer growth momentum and support sustainable Indian dairy development in the coming times. [Display omitted] • Three key areas, namely, dairy farming, dairy value chain and environmentally friendly practices for sustainable dairy development. • Two main types of variables (internal and external growth factors) are involved in the development of the dairy farming. • Strategies are formulated to improve milk productivity. • In line with the triple bottom line approach, a series of operational activities are suggested. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has posed unprecedented challenges to the livelihoods of rural households, especially in developing countries. The reverse migrated workers faced the most economic crisis. They have created additional pressure on local resources and opportunities to maintain their livelihood. In this connection the agriculture-livestock-forestry nexus plays a significant role by providing them livelihood opportunities. This paper attempts to understand the resource use patterns during the post-COVID period, and analyse the impact of agriculture-livestock-forest nexus on household income diversification and poverty reduction. The present study uses a novel approach to fulfil the objectives of the study. A well-designed survey was conducted to collect the necessary primary data from sixteen sample villages of West Bengal, India. The scientific design of the survey and data collection procedure is maintained. Moreover, geospatial techniques are used to examine the land use and land cover patterns of the study areas. The econometric models are estimated to inspect the role of agriculture-livestock-forest nexus and household characteristics on household level income diversification and the reduction of poverty. Our analysis reveals that a significant number of the sample households depend on agriculture, livestock and forestry to maintain their livelihoods. The reverse migration of workforce has created additional pressure on these activities. This is mainly due to non-availability of other non-farm employment opportunities locally. The analysis of econometric models shows that while engagement in different activities of the primary sector makes income diversified, it is more so when the households possess necessary technologies, skills and financial supports. All of these are crucial given that income diversification helps households to overcome of poverty. The intricate web of the agriculture-livestock-forestry nexus serves as a critical source of livelihood for a substantial number of households, yet the challenges and opportunities it presents necessitate targeted policy interventions. Enabling technology transfer, fostering skill development, and extending financial support emerge as key measures to diversify rural livelihoods, thereby fostering sustainable rural development and poverty reduction in the post-pandemic landscape. The integration of socioeconomic data and geospatial satellite information offers an invaluable basis for formulating effective policy strategies in this evolving era. [Display omitted] • Examines the agriculture-livestock-forest nexus and its impact on income diversification during the post-COVID period. • Analysing resource use and livelihoods with primary data, geospatial and econometric methods. • Technology transfer, skill development, and financial aid boost rural income diversification. • Socio-economic and satellite data integration aids in crafting impactful policies. [ABSTRACT FROM AUTHOR]

India's agricultural systems are increasingly affected by climate change's adverse effects. The Government of India has an impressive set of programs to address this issue, but they have substantial shortcomings, especially in reaching women farmers. We aim to understand policy and implementation gaps in reaching women farmers with climate-smart agriculture (CSA) practices and study how women and men farmer's different roles in agriculture shape their needs and access to complementary services needed to adapt to climate change. An extensive review of India's agriculture and climate policies and program and a series of focus group discussions with farmers in Gujarat, India to discuss constraints and potential entry points for better reaching women farmers with CSA practices. Women's increased vulnerability to climate change and reduced access to CSA practices can be attributed to limited land ownership, poor access to credit, reduced access to information and formal extension, and multiple pressures on their time. Village cooperatives and self-help groups can be leveraged to support women's access to agricultural information and adoption of CSA practices. This paper highlights constraints to information and extension access by Indian women farmers that could impede the widespread adoption of CSA practices. It fills an important knowledge gap in designing gender-responsive policies and inclusive agricultural extension systems to promote adoption of CSA practices among smallholder farmers. [Display omitted] • Women farmers have limited land ownership, access to credit, access to information and formal extension, and time, constraining adoption of climate smart practices. • Building gender-responsive extension systems is critical for promoting adoption of climate smart agriculture practices. • Knowledge of gendered experience of climate change, availability of gender-disaggregated data and gendered analyses are important aspects. • Participatory approaches to policy making and involvement of local and community organizations needs to be strengthened in India. • Village cooperatives and self-help groups can be key intermediary organizations to support women's access to information and adoption of CSA practices. [ABSTRACT FROM AUTHOR]

Global experiences reveal the positive impact of watershed-based interventions in improving livelihoods and environmental security. In the drylands, increasing forage resources and improving livestock productivity is a critical challenge. The overarching aim of this paper is to analyse the impact of watershed-based interventions on livestock population, productivity, fodder resources, and biomass availability. The paper describes the interrelationship between land, water, crop, and livestock and how the gap in forage deficit can be bridged through a range of watershed interventions. The study was undertaken in the Parasai-Sindh watershed of Central India between 2011 and 2016. A 300-year-old defunct haveli (a traditional rainwater harvesting structure) was renovated and nine check dams along the drainage line were constructed. Nearly 25,000 running-meters of field bunds were constructed. Large fields (2-3 ha) were divided into relatively smaller plots (0.3–0.5 ha) to reduce runoff velocity. The impact of watershed interventions on water availability, livestock productivity, forage yield, and income was studied through hydrological monitoring, primary household survey and principal component analysis (PCA) biplot and hierarchical clustering. The watershed interventions enhanced groundwater availability leading to greater fodder availability, 22% increase in livestock population (ACU) and a 120% increase in milk production over a period of five years. The bovine population recorded a surge of 193% (cattle) and 32% (buffalo) over this period. Mean dry matter (DM, fodder) availability also increased from 10 t/household/year to 16.7 t/household/year owing to improved water availability. Groundnut (rainy season) and wheat (post rainy season) contributed significantly as forage resources. There was an annual forage demand of 5560 t DM for a livestock population of 2175 ACU in 2011 and of 6770 t DM for a livestock population of 2650 ACU in 2016. Annual forage biomass availability was estimated at 4219 t DM in 2011 and 6977 t DM in 2016. There was a deficit of 1341 t DM (24%) in 2011 which turned into a 3% surplus of 210 t DM in 2016 through watershed-based interventions. With increased cropping intensity and milk production, average annual household income increased from US$ 1325 to US$ 2430 over the five-year period. This case study clearly illustrates the impact of watershed-based interventions on livestock population, productivity, forage resources, and biomass availability to bridge the gap in forage deficit. Its findings serve as a guide to widely scale up watershed-based interventions for improved water and biomass availability, and livestock productivity in semi-arid and dryland regions. [Display omitted] • Poor crop and livestock productivity is a critical challenge in drylands and watershed interventions could help build resilience to this • Interlinkages among land-water-crop-livestock sectors and their sustainability have been studied • Watershed based interventions enhanced groundwater availability, which reduced risk of crop failure, increased crop intensification and productivity • Forage availability has improved from deficit to surplus status due to watershed interventions despite significant increase in livestock population • Integrating land-water-crop-livestock interventions in watersheds can provide opportunities to improve rural livelihoods in drylands [ABSTRACT FROM AUTHOR]

Indian agriculture is highly vulnerable to climate shocks, such as floods, droughts and heat-stress. In this paper, using a dynamic panel-data approach we have assessed the impact of rainfall-deficit and heat-stress on agricultural productivity, and subsequently evaluated effectiveness of crop diversification in mitigating their adverse effects. The findings show that both rainfall-deficit and heat-stress damage agricultural productivity, and the damage increases with increase in their severity. Nevertheless, we find crop diversification as an important ex ante adaptation measure to climatic shocks and its adaptation benefits are more apparent against severe shocks and in the long-run. Our findings reinforce the dynamic role of crop diversification in improving resilience of agricultural production systems to climatic shocks. • There exists a dynamic relationship between climatic shocks, diversification and system productivity. • Climatic shocks adversely affect system productivity, and the effect intensifies with their rising severity. • Diversification enhances resilience of production system to climatic shocks. • Resilience benefits of diversification are more apparent in the long-run. [ABSTRACT FROM AUTHOR]

When on March 24, 2020 the Government of India ordered a complete lockdown of the country as a response to the COVID-19 pandemic, it had serious unwanted implications for farmers and the supply chains for agricultural produce. This was magnified by the fact that, as typically in developing countries, India's economy is strongly based on farming, industrialization of its agricultural systems being only modest. This paper reports on the various consequences of the COVID-19 lockdown for farming systems in India, including the economy, taking into account the associated emergency responses of state and national governments. Combining quantitative and qualitative sources of information with a focus on the Indian state of Uttar Pradesh, including expert elicitation and a survey of farmers, the paper identifies and analyzes the different factors that contributed to the severe disruption of farming systems and the agricultural sector as a whole following the lockdown. Among other issues, our study finds that the lack of migrant labor in some regions and a surplus of workers in others greatly affected the April harvest, leading to a decline in agricultural wages in some communities and an increase in others, as well as to critical losses of produce. Moreover, the partial closure of rural markets and procurement options, combined with the insufficient supply of products, led to shortages of food supplies and dramatically increased prices, which particularly affected urban dwellers and the poor. We argue that the lessons learned from the COVID-19 crisis could fuel the development of new sustainable agro-policies and decision-making in response not only to future pandemics but also to the sustainable development of agricultural systems in India and in developing countries in general. • The lockdown in response to COVID-19 has seriously disrupted Indian farms. • Farms have been less profitable amid rising food prices, putting pressure on food security. • A lack of migrant labor has led to a loss of produce and affected the spring harvest. • Experience and relief packages may help to develop Indian agriculture sustainably. [ABSTRACT FROM AUTHOR]

Global warming is predicted to increase in the future, with detrimental consequences for rainfed crops that are dependent on natural rainfall (i.e. non-irrigated). Given that many crops grown under rainfed conditions support the livelihoods of low-income farmers, it is important to highlight the vulnerability of rainfed areas to climate change in order to anticipate potential risks to food security. In this paper, we focus on India, where ~ 50% of rice is grown under rainfed conditions, and we employ statistical models (climate envelope models (CEMs) and boosted regression trees (BRTs)) to map changes in climate suitability for rainfed rice cultivation at a regional level (~ 18 × 18 km cell resolution) under projected future (2050) climate change (IPCC RCPs 2.6 and 8.5, using three GCMs: BCC-CSM1.1, MIROC-ESM-CHEM, and HadGEM2-ES). We quantify the occurrence of rice (whether or not rainfed rice is commonly grown, using CEMs) and rice extent (area under cultivation, using BRTs) during the summer monsoon in relation to four climate variables that affect rice growth and yield namely ratio of precipitation to evapotranspiration ( PER ), maximum and minimum temperatures ( T max and T min ), and total rainfall during harvesting. Our models described the occurrence and extent of rice very well (CEMs for occurrence, ensemble AUC = 0.92; BRTs for extent, Pearson's r = 0.87). PER was the most important predictor of rainfed rice occurrence, and it was positively related to rainfed rice area, but all four climate variables were important for determining the extent of rice cultivation. Our models project that 15%–40% of current rainfed rice growing areas will be at risk (i.e. decline in climate suitability or become completely unsuitable). However, our models project considerable variation across India in the impact of future climate change: eastern and northern India are the locations most at risk, but parts of central and western India may benefit from increased precipitation. Hence our CEM and BRT models agree on the locations most at risk, but there is less consensus about the degree of risk at these locations. Our results help to identify locations where livelihoods of low-income farmers and regional food security may be threatened in the next few decades by climate changes. The use of more drought-resilient rice varieties and better irrigation infrastructure in these regions may help to reduce these impacts and reduce the vulnerability of farmers dependent on rainfed cropping. [ABSTRACT FROM AUTHOR]

Livestock provides an important source of income and nourishment for around one billion rural households worldwide. Demand for livestock food products is increasing, especially in developing countries, and there are opportunities to increase production to meet local demand and increase farm incomes. Estimating the scale of livestock yield gaps and better understanding factors limiting current production will help to define the technological and investment needs in each livestock sector. The aim of this paper is to quantify livestock yield gaps and evaluate opportunities to increase dairy production in Sub-Saharan Africa and South Asia, using case studies from Ethiopia and India. We combined three different methods in our approach. Benchmarking and a frontier analysis were used to estimate attainable milk yields based on survey data. Household modelling was then used to simulate the effects of various interventions on dairy production and income. We tested interventions based on improved livestock nutrition and genetics in the extensive lowland grazing zone and highland mixed crop-livestock zones of Ethiopia, and the intensive irrigated and rainfed zones of India. Our analyses indicate that there are considerable yield gaps for dairy production in both countries, and opportunities to increase production using the interventions tested. In some cases, combined interventions could increase production past currently attainable livestock yields. [ABSTRACT FROM AUTHOR]

This paper describes an investigation of various adaptations of rice based cropping systems to climate variability in India's Telangana State. All adaptations were generated through participatory engagement and were field-tested with local smallholder households before being evaluated through cropping system simulation analysis. This approach contrasts with most research about adaptation of cropping systems to climate variability and climate change that is mostly based on simplifying assumptions about current farmer management practices and where the feasibility of implementing proposed adaptations is rarely tested. In this study, the investigation commenced with discussions about climate related issues in rice based farming systems between researchers, farmers and NGOs in three villages in three Mandals of the state of Telangana. Participatory intervention was used to identify new practices that could provide more adaptive and robust responses to climate variability. Suggested adaptations were implemented in on-farm experimentation. Fields demonstrating these adaptations were monitored and results were discussed with participating farmers at regular ‘Climate Club’ village meetings. Crop and soil data from these fields were used to locally parameterise the cropping systems simulator APSIM. Local adaptations that were trialled in the villages were simulated using local soil and long term historical weather data. In each of the case studies, a number of adaptations that were developed and implemented in the villages were shown through simulation to be successful in terms of agricultural production, stability of yields and resource use efficiency. Of the adaptations investigated, sowing rules to reduce the chance of crop failure due to early dry spells were most readily adopted and are also relatively easy to extend to other villages. Strategic irrigation of rainfed crops such as maize and cotton resulted in significant gains to profitability and stability of these crops but cannot be considered in isolation where access to water is limited. Reduced irrigation of rice resulted in over 60 mm/ha/yr. savings in water and some improvements in gross margins but this adaptation was not popular with farmers due to its burden on labour and added risks associated with unreliable supply of electricity for pumping at critical times. The reduced rice area for strategic irrigation of rainfed crops adaptation resulted in improved gross margins per hectare per year and higher net water productivity. This adaptation is most promising but will require institutional change around water use policy and more equitable allocation of limited water resources within villages. These results led us to the proposition that participatory action research with smallholder farmers, coupled with field-testing and simulation analysis can produce practical and productive adaptations to climate variability. [ABSTRACT FROM AUTHOR]

Land is a limited resource that provides food and cooking fuel to the rural population. In this paper, we determine the land required for food production and compare it with the land required for cooking fuel (i.e. fuelwood) for six different regions of India. We use regional data to assess the land requirements for both food and fuelwood. Dietary patterns and agricultural yields are the major drivers of land demand for food production. The average land requirement for food is about 1000 m2/cap/yr, but the values range between 800-1300 m2/cap/yr. The greatest proportion of this land requirement is for cereals, especially rice and wheat. Determining the land needed for cooking fuel requires biomass productivity and fuelwood use. We found that the average land requirement for fuelwood is about 3 to 7 times larger than the area required to produce food. Thus, there is a wide disparity in land demand between all the regions of India. Dietary change is not an option as rural inhabitants are already consuming less than their urban counterparts. Changes to cooking fuels could be another option. This comparative study shows the high demand for land for cooking fuel in comparison to food. It implies that, from a land requirement perspective, reducing the fuelwood consumption and shifting to a more efficient cooking fuel would be a better option. • Land required for food and fuelwood in rural India was studied. • Large regional variations in food consumption and cooking fuel use were found. • Land requirement for food is about 1000 m2/cap/yr. • Land required for fuelwood was seven times as higher than land required for food. • This study is typical for rural areas in developing nations comprising three billion people. [ABSTRACT FROM AUTHOR]