This open access book brings together varying perspectives for transformational change needed in India’s agriculture and allied sectors. Stressing the need of thinking for a post-Green Revolution ...future, the book promotes approaching this change through eight broad areas, indicating the policy shifts needed to meet the challenges for the coming decade (2021-2030). The book comprises of ten contributions. Apart from the overview chapter on transformational change and the concluding chapter on pathways for 2030, there are eight thematic chapters on topics such as transforming Indian agriculture, dietary diversity for nutritive and safe food; climate crisis and risk management; water in agriculture; pests, pandemics, preparedness and biosecurity natural farming; agroecology and biodiverse futures; science, technology and innovation in agriculture; and structural reforms and governance. The writing style of these papers written by technical experts is forward-looking—not merely an analysis of what has been and why it was so, but what ought to be. This is an essential reading for those interested in agriculture, food and nutrition sectors of India, and more so their interconnectedness.
Winner of the Don D. and Catherine S. Fowler Prize.
Eastern North America is one of only a handful of places in the world where people first discovered how to domesticate plants. In this book, ...anthropologist Shane Miller uses two common, although unconventional, sources of archaeological data—stone tools and the distribution of archaeological sites—to trace subsistence decisions from the initial colonization of the American Southeast at the end of the last Ice Age to the appearance of indigenous domesticated plants roughly 5,000 years ago.
Miller argues that the origins of plant domestication lie within the context of a boom/bust cycle that culminated in the mid-Holocene, when hunter-gatherers were able to intensively exploit shellfish, deer, oak, and hickory. After this resource “boom” ended, some groups shifted to other plants in place of oak and hickory, which included the suite of plants that were later domesticated. Accompanying these subsistence trends is evidence for increasing population pressure and declining returns from hunting. Miller contends, however, that the appearance of domesticated plants in eastern North America, rather than simply being an example of necessity as the mother of invention, is the result of individuals adjusting to periods of both abundance and shortfall driven by climate change.
People like to believe in a past golden age of `traditional' English countryside, before large farms, machinery, and the destruction of hedgerows changed the landscape forever. However, that ...countryside may have looked both more and less familiar than we imagine. Take, for example, today's startling yellow fields of rapeseed, seemingly more suited to the landscape of Van Gogh than Constable. They were in fact, thoroughly familiar to fieldworkers in seventeenth-century England. At the same time, some features that would have gone unremarked in the past now seem like oddities. In the fifteenth century, rabbits were reared in specially guarded warrens as luxury food for rich men's tables; whilst houses had moats not only to defence but to provide a source of fresh fish. In the 1500s we find Catherine of Aragon introducing the concept of fresh salad to the court of Henry VIII; and in the 1600s, artichoke gardens became a fashion of the gentry in their hope of producing more male heirs. The common tomato, suspected of being poisonous in 1837, was transformed into a household vegetable by the end of the nineteenth century, thanks to cheaper glass-making methods and the resulting increase in glasshouses. In addition to these fascinating images of past lives, Joan Thirsk reveals how the forces which drive our current interest in alternative forms of agriculture - a glut of mainstream meat and cereal crops; changing patterns of diet; the needs of medicine - have striking parallels with earlier periods of our history. She warns us that today's decisions should not be made in a historical vacuum. We can still find solutions to today's problems in the hard-won experience of people in the past.
Two of the world's most pressing needs—biodiversity conservation and agricultural development in the Third World—are addressed in Karl S. Zimmerer's multidisciplinary investigation in geography. ...Zimmerer challenges current opinion by showing that the world-renowned diversity of crops grown in the Andes may not be as hopelessly endangered as is widely believed. He uses the lengthy history of small-scale farming by Indians in Peru, including contemporary practices and attitudes, to shed light on prospects for the future. During prolonged fieldwork among Peru's Quechua peasants and villagers in the mountains near Cuzco, Zimmerer found convincing evidence that much of the region's biodiversity is being skillfully conserved on a de facto basis, as has been true during centuries of tumultuous agrarian transitions.
Diversity occurs unevenly, however, because of the inability of poorer Quechua farmers to plant the same variety as their well-off neighbors and because land use pressures differ in different locations. Social, political, and economic upheavals have accentuated the unevenness, and Zimmerer's geographical findings are all the more important as a result. Diversity is indeed at serious risk, but not necessarily for the same reasons that have been cited by others. The originality of this study is in its correlation of ecological conservation, ethnic expression, and economic development.
In theory, chemical-free sustainable agriculture not only has ecological benefits, but also social and economic benefits for rural communities. By removing farmers' expenses on chemical inputs, it ...provides them with greater autonomy and challenges the status quo, where corporations dominate food systems. In practice, however, organisations promoting sustainable agriculture often maintain connections with powerful institutions and individuals, who have vested interests in maintaining the status quo. This book explores this tension within the sustainable farming movement through reference to three detailed case studies of organisations operating in rural India.
The diversity of natural, climatic, and economic conditions of Russian regions implies a wide range of approaches to their classification. Simultaneously, the task of creating an abstract methodology ...for any branch of the national economy becomes more complicated. Effective clustering plays an important role in the establishment and implementation of agricultural and economic policies. The paper explores the potential of basic agricultural and economic regional clustering based on time series of main economic and agricultural development indicators. The dynamic segmentation technique was applied in order to monitor and predict the direction of meso-economic changes. Official Russian statistics were analysed to identify groups of indicators on production, production and institutional, and production and structural criteria. The k-means clustering algorithm was chosen as the key research method. Based on the three simulated regional segments, baseline average values were calculated. Then, the segments were classified according to the obtained characteristics. The outliers, significantly differing from the main data sets, were considered separately. The findings confirmed a wide spatial distribution of regions included in certain agricultural and economic segments. The presented classification can be applied to justify the directions and choice of instruments of agricultural and economic policy and a strategy for creating production clusters. Moreover, it can be used to plan the activities of regional agri-businesses and reduce their development imbalances. To improve the dynamic segmentation technique in the field of agricultural and economic development, the analysis can be expanded by changing the examined time interval, increasing the number of factors included in the model and their interactions, and introducing new clustering algorithms. Additionally, this model can be used to forecast structural changes and production dynamics.
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