Tomato, as the vegetable queen, is cultivated worldwide due to its rich nutrient content and unique flavor. Nondestructive technology provides efficient and noninvasive solutions for the quality assessment of tomatoes. However, processing the substantial datasets to achieve a robust model and enhance detection performance for nondestructive technology is a great challenge until deep learning is developed. The aim of this paper is to provide a systematical overview of the principles and application for three categories of nondestructive detection techniques based on mechanical characterization, electromagnetic characterization, as well as electrochemical sensors. Tomato quality assessment is analyzed, and the characteristics of different nondestructive techniques are compared. Various data analysis methods based on deep learning are explored and the applications in tomato assessment using nondestructive techniques with deep learning are also summarized. Limitations and future expectations for the quality assessment of the tomato industry by nondestructive techniques along with deep learning are discussed. The ongoing advancements in optical equipment and deep learning methods lead to a promising outlook for the application in the tomato industry and agricultural engineering.

Light penetration depth, as a characteristic parameter reflecting light attenuation and transmission in biological tissues, has been applied in nondestructive detection of fruits and vegetables. Recently, with emergence of new optical detection technologies, researchers have begun to explore methods evaluating optical properties of double-layer or even multilayer fruit and vegetable tissues due to the differences between peel and pulp in the chemical composition and physical properties, which has gradually promoted studies on light penetration depth. A series of demonstrated research on light penetration depth could ensure the accuracy of the optical information obtained from each layer of tissue, which is beneficial to enhance detection accuracy for quality assessment of fruits and vegetables. Therefore, the aim of this review is to give detailed outlines about the theory and principle of light penetration depth based on several emerging optical detection technologies and to focus primarily on its applications in the field of quality evaluation of fruits and vegetables, its future applicability in fruits and vegetables and the challenges it may face in the future.

A variable velocity parallel four-bar cavitating mechanism for well-cellar can form the well-cellar cavitation which suits for well-cellar transplanting under a continuous operation. In order to improve the cavitating quality, this paper analyzed the structural composition and working principle of the cavitating mechanism and established the bidirectional coupling model of multi-body dynamics and the discrete element between the cavitating mechanism and soil through Recurdyn and EDEM software. Based on the model, a three-factor, five-level quadratic orthogonal rotational combination design test was conducted with the parameters of the cavitating mechanism as the experimental factors and the parameters of the cavitation as the response index to obtain the optimal parameter combination, and a virtual simulation test was conducted for the optimal parameter combination in order to study the cavitating law of the cavitating mechanism and soil. The test results showed that the depth of the cavitation was 188.6 mm, the vertical angle of the cavitation was 90.4°, the maximum diameter of the cavitation was 76.1 mm, the minimum diameter of the cavitation was 68.5 mm, and the variance in the diameters for the cavitation was 5.42 mm². The cavitating mechanism with optimal parameters based on the Recurdyn–EDEM bidirectional coupling mode could further improve the cavitating quality.

Aiming at key issues in harvesting film-covered potatoes in hilly and mountainous areas—incomplete residual film collection, poor potato–soil separation, and high damage from potato-collecting devices—this study developed a crawler self-propelled potato harvester suitable for these regions. This study first expounds the overall structure and working principle of the potato harvester and then conducts principal analysis and structural design for key components (film-collecting device, digging device, primary conveying and separating device, secondary conveying and separating device, and intelligent potato-collecting device) from the perspectives of material force and movement. Finally, field performance tests were carried out in Huangzhong County, Xining City, Qinghai Province. The test results show that the machine can achieve an operation effect with a potato harvest loss rate of 2.4%, a potato damage rate of 1.4%, an impurity content rate of 2.8%, a skin-breaking rate of 2.7%, and a residual film cleaning rate of 89.6%, meeting the potato harvesting needs of this region. The lightweight self-propelled crawler potato harvester designed in this paper can realize functions such as residual film collection, potato–soil vibration separation, manual auxiliary sorting, and intelligent potato boxing, providing technical and equipment references for the harvesting of film-covered potatoes in complex terrain areas.

To address the low clearance rate issue of the anti-blocking mechanism for maize no-till planters in the Huang-Huai-Hai Plain of China, experiments and simulations were conducted to analyze the individual and collective movements of straw under the action of the round roller-claw anti-blocking mechanism. A tracer-based measurement method for straw displacement was applied firstly. Experimental results showed that the straw forward displacement could be characterized by the average horizontal displacements of longitudinal and lateral tracers, while the straw side displacement could be characterized by the lateral displacement of the longitudinal tracer. The straw forward displacement was 58.95% greater than the side displacement. Forward, side, and total displacements of straw increased as the mechanism’s forward speed increased from 3 km/h to 7 km/h, with corresponding rates of increase at 233.98%, 43.20%, and 162.47%, respectively. Furthermore, a model of straw–soil–mechanism interaction was constructed in EDEM 2022 software. The relative error between experimental and simulated straw clearance rates was 11.20%, confirming the applicability of the simulation model for studying straw–soil–mechanism interaction. Based on the simulation model, three straw tracers of different lengths were selected to study the motion behavior of straw. It was inferred that despite differences in straw length, the movement behaviors of the three straw tracers under the influence of the anti-blocking mechanism were similar. Additionally, longer straws exhibited greater displacements in all directions. This paper serves as a reference for studying straw motion behavior influenced by anti-blocking mechanisms.

Mechanical-chemical synergy has been proven efficient in weed control. However, characterizing the state of the weed–soil complex after mechanical weeding and revealing its effects on subsequent herbicide application is still challenging, which restricts the implementation of this technology. This paper first presents a method to characterize the state of the weed–soil complex from the perspectives of the fragmentation and composite characteristics. The regrowth of the weed–soil complex and the effects of complemented herbicide-reduced spraying on weed control efficacy and crop yield were then investigated. The results showed that the typical diameters of the weed–soil complexes were 10.67 cm and 2.82 cm after inter-row hoe shovel and intra-row finger weeding, respectively. There were mainly two and four weed–soil complex states after inter-row and intra-row weeding, respectively. The regrowth rate corresponding to the weed–soil complex state with the largest component proportion after inter-row and intra-row weeding was 76.91% and 18.37%, respectively. The additional chemical herbicide sprayed on the weed–soil complex significantly improved the fresh weight control efficacy of 95.12% for the preposed inter-row mechanical weeding and 138.07% for the preposed intra-row mechanical weeding in the maize silking stage. The maize yield of inter-row mechanical–75% chemical application treatment was 9.27% higher than that of chemical treatment. Mechanical weeding creates a suitable weed–soil complex state for subsequent chemical application and improves the synergistic weeding effect.