Potatoes have been one of the most important food crops in the world, due to their rich in starch, vitamins, and minerals. Their strong adaptability and short production cycle can greatly contribute to agricultural products globally. However, the storage of potatoes can often confine to the germination of tubers with irregular shapes and sizes. Physical and chemical approaches have been utilized to inhibit potato germination. Various metabolic pathways can involve significant physiological and biochemical alterations after harvest. The primary germination of potato tubers can also be dominated by enzymatic activities, carbohydrate metabolism, and hormonal regulation. Since the chemical inhibitors can effectively prevent sprouting, their use can often result in environmental contamination and potential food safety concerns. Although the low-temperature storage can effectively suppress sprouting, it can inadvertently promote undesirable saccharification to alter the color of processed potatoes. The harmful compounds can also be formed with carcinogenic risks, such as acrylamide. This study aims to prevent tuber infection and nutrient loss caused by potato germination during storage. The low-temperature plasma jetting was utilized to inhibit potato germination. A one-way experiment was conducted to determine the optimal influencing range of the plasma treatment voltage, gas flow rate, and treatment time on potato germination and weight loss. The box-Behnken response surface method was used to optimize the interaction levels among the three influencing factors (plasma treatment voltage, gas flow rate, and treatment time). The optimal conditions were then obtained for the plasma inhibition of potato germination. A systematic comparison was made on the SOD, CAT, POD, and PPO antioxidant enzyme activities between the optimal plasma treatment and the blank control group. The optimal plasma treatment was obtained on the potato quality indexes. The results showed that the optimal parameters were achieved for the plasma treatment of potatoes, including the voltage of 18 kV, treatment time of 20 s, and gas flow rate of 13 L/min. The germination rate and weight loss rate of potatoes were significantly reduced to 31.42% and 2.15%, respectively. Compared with the blank control group, the plasma treatment group significantly increased the activities of potato antioxidant enzymes (CAT, and SOD). The SOD and CAT activity of the plasma-treated group increased by 52.63% and 29.27% (P＜0.05), respectively, after 16 days of storage, compared with the control; Furthermore, the POD and PPO activities of the treated group increased by 8.69% and 18.58%(P＜0.05), respectively, compared with the control. Compared with the blank control, plasma-treated group increased the hardness and brittleness of the potatoes. Specifically, the hardness of the treated group increased by 6.06% (P＜0.05). While the brittleness of the treated potatoes was reduced by only 24.00% within 16 days, compared with 37.19% in the control. In addition, the plasma treatment reduced the sugar accumulation and dry matter consumption, thus maintaining the storage quality of potatoes. Among them, the reducing sugar was reduced by 32.56% in the treated group (P＜0.05), compared with the control. The dry matter increased by 7.66% in the treated group. Therefore, the plasma treatment can be expected to effectively inhibit and then slow down the germination process of potato tuber. The finding can lay a foundation to reveal the inhibiting mechanism of plasma technology from potato tuber germination.

Essential oils extracted from natural plants can serve as safe food additives, compared with conventional chemical or synthetic additives. Essential oils have also been incorporated into food packaging materials to impart their bacteriostatic and antioxidant properties. Among them, thymol (THY), a monoterpene phenolic compound extracted from the thyme plant, has been used as a bacteriostatic agent in active packaging materials with functional properties, due to its significant bacteriostatic properties. However, the activity of highly volatile THY is easily affected by the packaging environment. Therefore, appropriate techniques are needed to incorporate the THY into polymer matrices, in order to improve its stability and utilization for controlled release. This study aims to prepare the potato starch films of active packaging, taking the mesoporous nano-silica (mobil composition of matter No. 41, MCM-41) as the controlled-release carrier of THY (THY-MCM-41), potato starch as the film-forming substrate, glycerol as the plasticizer, and calcium chloride as the cross-linking agent. Single-factor experiments were carried out to determine the suitable additive ranges of potato starch, glycerol, calcium chloride, and THY-MCM-41 mass concentration in the packaging film. The L9 (3⁴) orthogonal test was also implemented to investigate the interactive effects of potato starch, glycerol, calcium chloride, and THY-MCM-41 on the thickness, opacity, moisture absorption (M_A), water vapor permeability (W_VP), tensile strength (TS), and elongation at break (EB) of the packaging film. The optimal conditions were obtained to prepare the potato starch films of active packaging. A systematic investigation was made to clarify the THY release kinetics in the optimal combination of packaging film at different temperatures and relative humidity (RH) environments. A prediction model of THY release was constructed to optimize the THY. The results showed that the optimal properties of the prepared packaging film A were achieved in the TS, MA, WVP, oxygen permeability (OP) and opacity were 7.16 MPa, 89.23%, 1.42 × 10^-10 g/(m·s·Pa), 1.02 × 10^-15 cm²/s·Pa, and 1.16 mm^-1, respectively, when the mass concentrations of potato starch, glycerol, calcium chloride and THY-MCM-41 were 0.04, 0.015, 0.005, and 0.005 g/mL, respectively. Scanning electron microscope (SEM) and Fourier-transformed infrared (FTIR) spectroscopy confirmed that the denser and more uniform microstructure of packaging film was observed, where THY-MCM-41 was uniformly dispersed in the potato starch film, indicating better compatibility with potato starch. Thermogravimetric (TG) analysis showed that the encapsulation of MCM-41 improved the stability of THY in the potato starch film. In addition, the release kinetics of THY in the potato starch film of active packaging demonstrated that the initial explosive release was shifted to a subsequent sustained release under different temperature-RH environments. The active packaging film was prepared to effectively control the release rate of THY for the effective time of THY up to 10 d. The release pattern of THY was in accordance with the First-order release model (R² > 0.980), and the release index “n” was less than 0.5, indicating that the release behavior of THY followed Fickian diffusion law. This finding can also provide the theoretical foundation for the precise release of active substances in the development of active packaging films.

Potato is the fourth largest grain crop in China. Mechanization operation is also ever-increasing with the largest area under potato cultivation in recent years. Among them, potato bagging has been one of the most important steps in the subsequent storage, transport, and sale during production. However, manual segmentation cannot fully meet the large-scale production needs in the potato industry, due to the low quality and efficiency of current bagging machines. In this study, an automatic packaging machine was designed to integrate the agricultural machinery using plastic woven bags. A series of operations were adopted, such as bag feeding, opening, lifting, covering, and bagging. Four modules were developed as the feeding with an upper pressure roller, the opening with a suction cup, and the lifting and bagging device. Specifically, the forward conveying of the woven bag was realized in the bag feeding device with an upper pressure roller. The openings were separated on both sides of the woven bag using a bag-opening device with suction cups. The woven bags were inserted and then lifted to the position below the hopper. Ultimately, the potato dropping was realized under the clamp bagging device. In addition, the photoelectric sensor was equipped to detect the forward position of the woven bag. A switch sensor of metal proximity was also utilized to detect the position of the bagging arm. A PLC was then used to control each mechanism for the automatic potato bagging. The potato bagging rate and bagging efficiency were improved in the machine. Then, the influencing parameters of key components were determined to combine with the technical requirements of plastic woven bags. With the upper roller pressure, suction cup adsorption height, and adsorption time as test factors, while the bag opening rate and bagging efficiency as evaluation indexes, a three-factor, three-level orthogonal experiment was carried out using Box-Behnken neutral combination design function in Design-Expert. Variance analysis was also performed to clarify the impact of the various experimental factors on the evaluation indicators using the response surface method (RSM). The working parameters were optimized to determine the optimal combination of parameters under the actual operations. The test results show that the bag opening rate of the woven bag was 98.36%, and the bagging efficiency was 68 bags/min when the wheel pressure was 71.0 N, the adsorption height of the suction cup was 80.0 mm, and the adsorption time of suction cup was 1.6 s. There was a stable coordination among the various parts of the bagging machine during operation. The performance indexes fully met the actual working requirements. The findings can also provide a strong reference developing and optimizing the bagging equipment in the potato industry.

Grading has been one of the most important procedures in potato harvesting. However, manual grading has suffered from low efficiency, high subjectivity, high cost, and insufficient accuracy. High precision of detection is then required to fully meet the demands of large-scale production in recent years. Alternatively, several challenges still remain in the detection of potato surface defects. Firstly, simple image processing cannot concurrently recognize the variety of defects, such as disease spots, pest damage, and mechanical injuries, together with their diverse morphologies. Secondly, the high resolution of detection can further be confined to the complex environmental factors in agricultural settings, such as lighting and soil coverage. Moreover, the real-time operation has also failed to be realized on resource-constrained devices using most existing models with large parameter sizes and high computation. In this study, a lightweight algorithm (DATW-YOLOv8) was proposed to detect potato surface defects using an improved YOLOv8n model. The bottleneck module in the C2f was replaced with the Dilation-wise Residual (DWR) module. Dilated Reparam Block (DRB) was then introduced to optimize the extraction of the features for the high accuracy of detection. Additionally, a lightweight adaptive downsampling (ADOWN) convolution module was integrated to reduce the dimensionality for high processing efficiency. The detection head was upgraded to a Task Align Dynamic Detection Head (TADDH). As such, the high accuracy of defection was obtained to predict the boundary. The real-time detection was then realized to focus precisely on the key regions of surface defects. Finally, the Wise-EIoU was adopted as the bounding box regression loss function, in order to increase the attention to the difficult samples, thereby enhancing the boundary regression accuracy and model robustness. Experimental results show that the improved DATW-YOLOv8 model was achieved in the detection accuracy, recall, and mean average precision (mAP) of 95.8%, 88.1%, and 94.3%, respectively. The parameter size and weight size were 1.5 M and 3.6 MB, respectively, which were 50.0% and 42.9% smaller than those of the original YOLOv8n model. Additionally, the accuracy, recall, and mAP were improved by 2.8, 1.6, and 1.4, respectively. The better performance of defect detection was achieved in the ADOWN downsampling, compared with the YOLOv7 E-ELAN, SPDConv, WaveletPool, and Light-weight Context Guided DownSample, with the mAP improvements of 0.8, 1.3, 1.4, and 1.7 percentage points, respectively, while reducing parameter counts by 11.8, 60.5, 6.3, and 48.3 percentage points, respectively. The Wise-EIoU was also achieved in the lowest loss value, the fastest convergence, and the smallest fluctuation among various bounding box loss functions. The DATW-YOLOv8 also outperformed the YOLOv5Lite-g, YOLOv8n, YOLOv10n, and Mobilenetv2-SSD, in terms of the accuracy, recall, and mAP@0.5, particularly with the lower model weight. Specifically, the model weight of DATW-YOLOv8 was only one-third of that of YOLOv7tiny. The superior performance was then confirmed after multiple evaluations. Furthermore, the improved DATW-YOLOv8 model was deployed on an online detection of potato surface defects. A sorting test of online detection was conducted on the different potato varieties and conveyor speeds. The maximum sorting accuracy reached 95.8%, fully meeting the real-time detection requirements of potato surface defects in practical production. Overall, this finding can also provide a valuable technical reference for online detection of potato surface defects and model deployment on mobile devices.