Design and experiment of a handheld non-destructive detection device for potato dry matter content

doi:10.3969/j.issn.1004-1524.20230381

Acta Agriculturae Zhejiangensis ›› 2024, Vol. 36 ›› Issue (4): 943-951.DOI: 10.3969/j.issn.1004-1524.20230381

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Design and experiment of a handheld non-destructive detection device for potato dry matter content

CONG Jie¹^,²(), ZHANG Yueru², LI Xilong², PAN Yuxuan², LYU Huangzhen², LYU Chengxu²^,^*()

1. School of Mechanical and Electrical Engineering, Qingdao Agricultural University, Qingdao 266109, Shandong, China
2. National Key Laboratory of Agricultural Equipment Technology, China Academy of Agricultural Mechanization Sciences Group Co., Ltd., Beijing 100083, China

Received:2023-03-20 Online:2024-04-25 Published:2024-04-29
Contact: LYU Chengxu

Abstract

Abstract:

In response to the demand for quality inspection of potatoes, a handheld non-destructive detection device for potato dry matter was developed. The hardware components of the device included a spectrum acquisition module, a circuit control module, a control and display module, device housing module. The design of the device was gun-shaped with dimensions of 180 mm×85 mm×210 mm. The device utilized visible-near infrared diffuse reflectance spectroscopy, comparing pre-processing methods such as Savitzky-Golay convolution smoothing (SM), first-order derivative (FD), multiple scattering correction (MSC), and standard normal variate transformation (SNV), with SM yielding better results. Competitive adaptive reweighted sampling (CARS) was used to select 27 feature wavelengths to establish a support vector regression (SVR) prediction model for potato dry matter content, with validation set coefficient of determination and root mean square error of 0.802 and 0.98%, respectively. The device software was developed using the QT development tool, including modules for black and white calibration and measurement, power display, spectral data display, data storage, spectral data refresh, and detection result display. Device verification was conducted, showing a prediction root mean square error of 1.01% and an average time consumption of 0.62 s per measurement. The results indicated that the handheld non-destructive detection device for potato dry matter could rapidly and accurately detect dry matter content, demonstrating potential for application at the source and processing sites of potato production.

Key words: potato, dry matter content, hand-held device, visible/near infrared diffuse reflectance spectroscopy

CLC Number:

TH79

CONG Jie, ZHANG Yueru, LI Xilong, PAN Yuxuan, LYU Huangzhen, LYU Chengxu. Design and experiment of a handheld non-destructive detection device for potato dry matter content[J]. Acta Agriculturae Zhejiangensis, 2024, 36(4): 943-951.

Figures/Tables 13

Fig.1 Frame diagram of the device hardware system

Fig.2 Structure of the spectral acquisition module

Fig.3 Working schematic diagram of diffuse reflection light path bracket

Fig.4 Physical picture of handheld non-destructive detection device for potato dry matter content

Fig.5 Original spectra

Table 1 Statistic of calibration and prediction sets of DMC

数据集 Data set	样本数 Sample size	最小值 Minimum/%	最大值 Maximum/%	平均值 Average/%	标准差 Standard deviation/%	变异系数 Coefficient of variation/%
校正集Correction set	102	11.18	23.52	15.69	2.30	0.15
验证集Validation set	30	11.78	21.67	15.82	2.17	0.14

Fig.6 Spectral images after different pretreatments SM, Savitzky-Golay convolution smoothing; MSC, Multiple scattering correction; FD, First-order derivative; SNV, Standard normal variate transformation.

Table 2 Modeling results of different pretreatment methods

预处理方式 Preprocessing method	R²_c	RMSEC/%	R²_p	RMSEP/%	RPD
无None	0.676	1.31	0.604	1.39	1.563
MSC	0.680	1.30	0.638	1.32	1.636
SNV	0.706	1.25	0.633	1.33	1.623
FD	0.551	1.43	0.574	1.44	1.500
SM	0.715	1.23	0.675	1.26	1.724

Fig.7 Characteristic wavelength

Fig.8 Scatterplot of model results

Fig.9 Software interface

Fig.10 Operational flow chart

Fig.11 Measurement result

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Design and experiment of a handheld non-destructive detection device for potato dry matter content

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