Driving innovation in agriculture with synthetic data
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Data is the cornerstone of agricultural product innovation. It’s necessary to develop products, meet regulatory requirements, discover new mechanisms, and educate the market on how to optimize the use of agriculture inputs and practices. Today, huge amounts of data are collected around various parameters including soil data, rainfall, water usage, fertilizer needs, crop health, quality, and yield among others. Using data science in agriculture allows unlocking the true potential of collected data to gain insights that can be used for predictive modeling and making better-informed decisions.
Driving innovation in agriculture with synthetic data
Driving innovation in agriculture with…
Driving innovation in agriculture with synthetic data
Data is the cornerstone of agricultural product innovation. It’s necessary to develop products, meet regulatory requirements, discover new mechanisms, and educate the market on how to optimize the use of agriculture inputs and practices. Today, huge amounts of data are collected around various parameters including soil data, rainfall, water usage, fertilizer needs, crop health, quality, and yield among others. Using data science in agriculture allows unlocking the true potential of collected data to gain insights that can be used for predictive modeling and making better-informed decisions.