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Avanços na ciência e tecnologia agrícola

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Abstrato

Cultivating Crop Productivity: Challenges and Strategies for Sustainable Food Production

Niwedita P

Cultivating crop productivity to meet the growing global demand for food while ensuring environmental sustainability is a critical challenge facing modern agriculture. This abstract provides an overview of the challenges and strategies involved in achieving sustainable food production through enhanced crop productivity. The increasing global population, changing dietary patterns and urbanization exert significant pressure on agricultural systems. To address this challenge, it is crucial to optimize crop yields in a sustainable manner that balances economic, environmental, and social considerations. Numerous factors influence crop productivity, including climatic conditions, soil health, water availability, pests and diseases, and nutrient management. Climate change further complicates the situation, as it leads to extreme weather events, altered precipitation patterns, and increased pest pressure. Adapting agricultural practices to mitigate climate change impacts is essential to maintain consistent crop yields. Sustainable food production practices, such as precision agriculture, organic farming, agroforestry, and soil conservation techniques, play a pivotal role in enhancing crop productivity while minimizing environmental impacts. These practices promote soil fertility, water conservation, greenhouse gas reduction, and biodiversity conservation. Technological innovations, including genetic engineering, biotechnology, and digital agriculture, offer promising opportunities to improve crop productivity. Genetic engineering techniques enable the development of crop varieties with enhanced traits, such as drought tolerance, disease resistance, and improved nutritional content. Digital agriculture tools help optimize resource utilization, pest and disease management, and precision farming techniques.

Isenção de responsabilidade: Este resumo foi traduzido usando ferramentas de inteligência artificial e ainda não foi revisado ou verificado.