Prediction of melon sweetness using a mini spectrometer C11708MA
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Abstract
This study evaluates the feasibility of using a C11708MA mini-spectrometer for the non-destructive prediction of melon sweetness (°Brix). The spectrometer was integrated with an STM32 microcontroller to acquire and transmit spectral data to a computer for machine-learning-based prediction. Spectra in the range of 640–1050 nm were collected from 50 melons using a multi-point sampling strategy. Preprocessing techniques, including Savitzky–Golay filtering, standard normal variate, multiplicative scatter correction, and their combinations, were applied before developing partial least squares regression (PLS) and support vector regression (SVR) models. SVR generally outperformed PLS, achieving RPD values of about 1.7–1.8, indicating acceptable prediction capability for rapid screening. These results are comparable to previous studies using mini-spectrometers and highlight the potential for developing low-cost handheld spectroscopic devices for rapid fruit quality assessment.
Tóm tắt
Khả năng ứng dụng phổ kế mini C11708MA trong dự đoán không phá hủy độ ngọt (°Brix) của dưa lưới được đánh giá trong nghiên cứu. Phổ kế được tích hợp với vi điều khiển STM32 để thu nhận và truyền dữ liệu phổ về máy tính, nơi mô hình học máy được sử dụng để dự đoán °Brix. Phổ trong dải 640–1050 nm được thu thập từ 50 quả dưa lưới theo chiến lược lấy mẫu đa điểm. Các kỹ thuật tiền xử lý như lọc Savitzky–Golay, biến chuẩn hóa, hiệu chỉnh tán xạ nhân và các tổ hợp của chúng được áp dụng trước khi xây dựng mô hình hồi quy bình phương tối thiểu từng phần (PLS) và vector hỗ trợ (SVR). Kết quả cho thấy SVR thường cho hiệu suất tốt hơn PLS, với RPD khoảng 1,7–1,8, cho thấy khả năng dự đoán chấp nhận được cho các ứng dụng sàng lọc nhanh. Kết quả này tương đương một số nghiên cứu trước đây sử dụng phổ kế mini, cho thấy tiềm năng phát triển thiết bị quang phổ cầm tay chi phí thấp cho đánh giá nhanh chất lượng nông sản.
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