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<p><b>Rapid non-destructive nutritional analysis using advanced imaging technologies</b></p> <p>Traditional nutritional analysis methods are destructive, slow, and impractical for large-scale applications. <i>Nutritional Imaging in Agri-Food Systems</i> presents image processing as a rapid, non-destructive alternative with real-time monitoring capabilities. A team of specialists in food science, imaging, and data analytics demonstrates how visual data can assess quality, detect adulteration, and monitor safety with unprecedented speed.</p> <p>This volume covers imaging technologies from visible light to multispectral, hyperspectral, thermal, fluorescence, and microscopy techniques, detailing specific applications in nutritional assessment. Case studies demonstrate scalable utilization in agriculture and food systems, including spoilage detection, automated grading, and real-time monitoring using edge AI and IoT. The book integrates machine learning, remote sensing, and digital agriculture insights.</p> <p>Readers will also find:</p> <ul> <li>Detailed coverage of how cameras and sensors detect color, texture, and chemical composition to identify ripeness, spoilage, and fat content</li> <li>Practical applications for smartphones, drones, and smart farming equipment that make food analysis faster and more accessible across operations</li> <li>Integration strategies connecting machine learning, robotics, and remote sensing technologies for comprehensive agricultural and nutritional monitoring systems</li> <li>Methods for reducing food waste and improving food safety through automated quality control and real-time assessment at production scale</li> <li>Scalable solutions linking agriculture, nutrition, and digital innovation for healthier food systems and more efficient supply chain management</li> </ul> <p>Written for scientists in agricultural science, food science, nutrition, computer vision, and image processing, this reference serves professionals in food processin