Abstract
Barley quality estimation method with Unmanned Aerial Vehicle: UAV based Near Infrared: NIR camera data based on regressive analysis is proposed. The proposed method allows to predict barley quality, anthocyanin, β-glucan and water contents in the harvested “Daishimochi” of barley grains before the harvest. The prediction method proposed here is based on regression analysis with the Near Infrared: NIR camera data mounted on UAV which allows to estimate barley quality, anthocyanin, β-glucan and water contents in the harvested “Daishimochi” of barley grains before the harvest.. This is the first original attempt for the prediction in the world. Through experiment, it is found that water content (%), Anthocyanin content (mg Cy3G/100 g), Anthocyanin content (mg Cy3G/100 g: which corresponds to dry matter), and barley β-glucan (%) can be predicted before the harvest with high R2 value (more than 0.99). Therefore, farmers can control fertilizer and water supply for improvement of the Daishimochi barley grain quality.
Highlights
There is a strong demand on a prediction of the harvested agricultural product quality before the harvest
The prediction method proposed here is based on regression analysis with the Near Infrared: NIR camera data mounted on UAV which allows to estimate barley quality, anthocyanin, β-glucan and water contents in the harvested “Daishimochi” of barley grains before the harvest
The anthocyanin accumulation time is later than the accumulation time of catechin and proanthocyanidins, which are the causes of browning after heating and are the main polyphenol components of barley grain
Summary
There is a strong demand on a prediction of the harvested agricultural product quality before the harvest. The reason is that "barley β-glucan" suppresses the absorption of sugars and continues until the meal This feature is called the "second meal effect". The prediction method proposed here is based on regression analysis with the Near Infrared: NIR camera data mounted on UAV which allows to estimate barley quality, anthocyanin, β-glucan and water contents in the harvested “Daishimochi” of barley grains before the harvest. This is the first original attempt for the prediction in the world. Conclusion is described with some discussions and future works
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