Subjects: Agriculture, Forestry,Livestock & Aquatic Products Science >> Other Disciplines of Agriculture, Forestry,Livestock & Aquatic Products Science submitted time 2023-02-17 Cooperative journals: 《智慧农业（中英文）》
Abstract： The internal quality of citrus is an important index for citrus grading, and the most common factors affecting the internal quality of citrus are peel puffing and granulation, which affect the fruit quality and lose the market value due to the large consumption of nutrients. In this study, a soft X-ray imaging device was developed, including a transmission device, a soft Xray imaging device, a trigger device and a soft X-ray protection device, for the problem that traditional methods cannot detect citrus peel puffing and granulation efficiently and non-destructively. In this research, the detection parameters were determined according to the physical characteristics of wide peeled citrus, and the clarity, contrast and aberration rate of citrus images were used as the judging criteria. The best imaging parameters were determined by adjusting the parameters of the imaging device as follows: The tube voltage of X-ray source was 60 kV, the tube current was 1.3 mA, the integration time of line array detector was 5.5 ms, and the transmission speed of citrus conveyor belt was 10 cm/s. The aberrations in the column direction were detected by the circular hole metal plate, and the results showed that the transmission speed was stable and the aberrations in the column direction were negligible. The aberrations in the row direction ware detected by using the 70 mm stainless steel calibration sphere, and the projection aberration coefficients at different positions in the row direction were calculated, and the aberration correction model was established. The soft X-ray images of citrus were acquired under the above parameters, and Gaussian filtering was used to denoise the citrus images. The image enhancement algorithm was used to enhance the contrast of the denoised images. The fixed threshold segmentation method and morphological algorithm were fused to remove the background area, separate the flesh area and the peel area of the citrus images. Finally, the area percentage method was used to calculate the ratio of citrus flesh area to citrus fruit area to discriminate the degree of citrus peel puffing; the grayscale features of citrus fruit area were extracted to obtain the citrus withered area, and the ratio of citrus withered area to citrus flesh area was calculated to discriminate the degree of citrus granulation. Qingjiang Ponkan were taken as the experimental object, and the results showed that the overall recognition rate of the homemade soft X-ray imaging device were 96.2% and 86.9% for the peel puffing and granulation of Qingjiang Ponkan, respectively. The method proposed in this study may achieve nondestructive detection of peel puffing and granulation inside citrus.
Subjects: Agriculture, Forestry,Livestock & Aquatic Products Science >> Other Disciplines of Agriculture, Forestry,Livestock & Aquatic Products Science submitted time 2023-02-17 Cooperative journals: 《智慧农业（中英文）》
Abstract： Vegetable and fruit planting areas and products of China have always ranked first in the world, and the vegetable and fruit industry is respectively the second and third largest agricultural planting industry after grain. Vegetables and fruits are prone to quality deterioration during postharvest storage and transportation, resulting in reduced edible value and huge economic losses. To ensure fruit and vegetable quality and reduce the waste of resources caused by postnatal deterioration, this paper summarizes the latest research status of sensor detection and monitoring technology for fruit and vegetable quality deterioration and analyzed the principle, characteristics, advantages, and disadvantages of various detection technology. Among them, machine vision can detect the external quality and surface defects of fruits and vegetables, but fruits and vegetables are different from the standard machined products, and they are affected by many factors in the growth process, which seriously interfere with the image collection work and easily lead to misjudgment. An electronic nose equipped with expensive gas sensors can monitor the odor deterioration of fruits and vegetables but would require improved sensitivity and durability. Near-infrared can detect the internal quality and recessive defects of fruits and vegetables, but the applicability of the model needs to be improved. Hyperspectral imaging can visually detect the internal and external quality of fruits and vegetables and track the deterioration process, but the huge amount of data obtained leads to data redundancy, which puts forward higher requirements for system hardware. Therefore, low-cost multispectral imaging systems should be developed and characteristic wavelength extraction algorithms should be optimized. Raman spectroscopy can detect fruit and vegetable spoilage bacteria and their metabolites, but there is no effective Raman enhanced substrate production and accurate Raman standard spectrogram database. The comprehensive evaluation of fruit and vegetable deterioration can be realized by multi-technology and multi-information fusion. It can overcome the limitation of single sensor information analysis, improve the robustness and parallel processing ability of the detection model, and provide a new approach for high-precision detection or monitoring of fruit and vegetable quality deterioration. The Internet of Things monitoring system is constructed with various sensors as the sensing nodes to realize the intelligent real-time monitoring of fruit and vegetable quality deterioration information, provide a reference for solving the technical limitation of quality deterioration control in the processing of fruit and vegetable. This is of great significance for reducing the postpartum economic loss of fruits and vegetables and promoting the sustainable development of the fruit and vegetable industry.
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