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Our AI-powered visual inspection technology is capable of detecting and classifying impurities such as foreign materials, weed seeds, and other grains. In addition, it provides detailed insights and data for each sample by measuring the width, thickness, length, volume, and color of every individual kernel. ...
ByCgrain AB based in Uppsala, SWEDEN
Validation and accuracy of phenotyping information is crucial for plant research and crop improvement. Conventional phenotypic analysis in plant relies on the assessment and characterization of vegetation constitution mainly with manual observations. But visual assessment and manual measurements can be subjective, prone to human bias, time-consuming and labour-intensive, leading to variations in interpretations and being impractical for large-scale. Due to the subjectivity in data collection, reproducibility is ...
ByKonica Minolta Sensing based in Ramsey, NEW JERSEY (USA)