Titlebook: Digital Ecosystem for Innovation in Agriculture; Sanjay Chaudhary,Chandrashekhar M. Biradar,Mehul S Book 2023 The Editor(s) (if applicable

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Machine Learning and Deep Learning in Crop Management—A Reviewes faced while applying the ML and DL algorithms to different crop management activities. Moreover, the available agriculture data sources, data preprocessing techniques, ML algorithms, and DL models employed by researchers and the metrics used for measuring the performance of models are also discussed.

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A Theoretical Framework of Agricultural Knowledge Management Process in the Indian Agriculture Contetive of size, location, and economic background. This structure could direct agricultural organizations in their knowledge management initiatives by exploring various ecosystem components for better operation and usage.

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A Brief Review of Tools to Promote Transdisciplinary Collaboration for Addressing Climate Change Chagricultural efficiencies and greening the energy sector by making room for sustainable renewable bioenergy crops. Efforts for climate change mitigation and adaptation with a focus on agriculture must come from transdisciplinary collaboration, which is often not easy and require one to come out of on

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Machine Learning and Deep Learning in Crop Management—A Reviewoutput in a cost-effective manner. Researchers have used ML and DL techniques for different agriculture applications such as crop classification, automatic crop harvesting, pest and disease detection from the plant, weed detection, land cover classification, soil profiling, and animal welfare. This

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An Algorithmic Framework for Fusing Images from Satellites, Unmanned Aerial Vehicles (UAV), and Farmrial vehicles (UAVs) provide multispectral farm data with very high resolution spanning a few hundred square meters. In contrast, low-cost sensors and IoT sensors provide accurate spatial and time series data of land and soil characteristics spanning a few meters. However, in practice, each of these

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Globally Scalable and Locally Adaptable Solutions for Agricultureg the productivity of crops and also optimizing the inputs, and at the same time sustaining the environmental resources. The ability of satellite data in precision farming has been made evident through several projects and research activities adopted across India. The past decade has seen a rapid in

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A Theoretical Framework of Agricultural Knowledge Management Process in the Indian Agriculture Contean also help improve the livelihood of rural communities in developing countries like India. However, little information on agriculture knowledge management processes and the ecosystem required for their implementation in the literature is available. This chapter attempts to derive a theoretical fra

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Simple and Innovative Methods to Estimate Gross Primary Production and Transpiration of Crops: A RevDGs). New technology advancements and sources of information play a critical role in supporting agriculture to achieve the SDGs goals and increase production capabilities to meet rising food demands. Gross primary production (GPP) and transpiration (T) of crops are the largest carbon and water fluxe

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Role of Virtual Plants in Digital Agricultureural plant models (FSPM), which are used to model an accurate plant shape and architecture and combines it with physiological processes. Static or dynamic FSPMs are a well-established approach to serve as a versatile tool for predicting crop growth patterns in response to variations in?environmental