Dự đoán độ ngọt của xoài trên cơ sở dữ liệu phổ thu thập từ cảm biến đa phổ giá thành thấp
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Abstract
Recent studies have shown that low-cost multispectral sensors have attracted much interest in developing agricultural applications. This study evaluated the potential of using a low-cost multispectral sensor to predict the sweetness of mango fruit with high export values. A few spectral data preprocessing and wavelength selection algorithms were applied to develop an accurate prediction model. Experimental results showed that unprocessed spectral data of fourteen wavelengths selected by the “regression coefficients” algorithm were suitable for developing a partial least square regression model with a correlation coefficient of 0.703 and a root mean square error of 1.439 °Brix. These results were comparable to recent studies using the same multispectral sensor, confirming the potential use of low-cost multispectral sensors in developing applications and portable devices for fruit quality assessment.
Tóm tắt
Nhiều nghiên cứu gần đây cho thấy cảm biến đa phổ giá thành thấp được quan tâm nhiều trong việc phát triển các ứng dụng trong nông nghiệp. Nghiên cứu này đánh giá tiềm năng sử dụng cảm biến đa phổ giá thành thấp trong việc dự đoán độ ngọt của xoài, loại trái cây có giá trị xuất khẩu cao. Để phát triển được mô hình dự đoán chính xác, một số giải thuật tiền xử lý và lựa chọn bước sóng đã được áp dụng. Kết quả cho thấy dữ liệu phổ không qua tiền xử lý trích xuất từ mười bốn bước sóng được chọn bởi giải thuật “hệ số hồi quy” là phù hợp để xây dựng mô hình hồi quy bình phương tối thiểu từng phần có hệ số tương quan bằng 0,703 và sai số RMSE là 1,439 °Brix. Kết quả này có thể so sánh được với các nghiên cứu gần đây sử dụng cùng loại cảm biến đa phổ vì thế khẳng định tiềm năng sử dụng cảm biến đa phổ giá thành thấp trong việc phát triển ứng dụng và thiết bị cầm tay để đánh giá chất lượng trái cây.
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