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Vibration harvesting is a promising method for walnut production owing to its low cost and high efficiency. However, current research focuses on simulation analysis and lacks a theoretical model explaining the walnuts' specific vibration response. This affects the design of the input vibration parameters during harvesting and thus reduces the harvesting efficiency. In this paper, a novel theoretical model of walnuts during vibration harvesting was established to analyze the vibration response, including the motion morphology (motion trajectory and dropping position) and detachment force. A field test was then carried out to verify the theoretical model. The theoretical and experimental results showed that the motion trajectory of the walnuts during vibration harvesting is similar to an ellipse, and the dropping position is at either of the two end points of the trajectory. The detachment force was found to be proportional to the vibration amplitude and the square of the vibration frequency theoretically. This paper provides a theoretical reference for designing the optimal input vibration parameters of a harvesting device to improve the harvesting rate of walnuts. [ABSTRACT FROM AUTHOR]

Walnuts with their shells are a popular agricultural product in China. However, mildew from growth can sometimes be processed into foods. It is difficult to visually determine which walnuts have mildew without breaking the shells. A non-destructive method for detecting walnuts with mildew was studied by combining spectral data with image information. A total of 120 "Lüling" walnuts with shells were used for the mildew experiment. The characteristics of the spectral data from six surfaces of all samples were collected in the range of 370–1042 nm on days 0, 15, and 30. The spectrum was pretreated using SNV, and the feature bands were extracted using PCA and modeled using a support vector machine (SVM). The results show that the overall classification accuracy was 93%, with an of accuracy of 100% for INEN walnuts (normal internally and externally). The accuracy for IMEM walnuts (mildew internally and externally) reached 87.29%. There was an accuracy of 78.6% for IMEN walnuts (mildew internally and normal externally). The non-destructive detection of mildewed walnuts can be undertaken using hyperspectral imaging technology, which provides a new technique for exploring the mechanisms of walnuts with mildew. [ABSTRACT FROM AUTHOR]

To address concerns regarding walnut shell damage and inadequate sorting precision during the mechanized sorting of walnuts, a walnut automatic sorting machine was designed based on deep learning and experimental research. Initially, the rationality of the design was verified through experiment. Then, three deep learning semantic segmentation algorithms, namely PSPnet, U-net, and Deeplabv3+, were selected to train walnut detection models. Results indicated that the U-net algorithm proved to be the most effective, achieving a Mean Intersection over Union of 96.71% and a Mean Pixel Accuracy value of 98.52%. Finally, performance tests were conducted on the prototype machine, yielding results with an average sorting efficiency of 51.70 kg/h, an average loss rate of 6.50%, and an average accuracy of sorting walnuts of 92.98%. The findings can provide insights for future structural improvements and operational parameter optimization of walnut automatic sorting machines. • Design of the walnut automatic sorting machine and experiment of key component. • Excellent prediction ability of walnut detection model by U-net algorithm. • Good sorting efficiency, walnut loss rate and sorting walnuts accuracy of the prototype. [ABSTRACT FROM AUTHOR]

Clarifying the low-frequency vibration transfer law of fruit trees is an important prerequisite for studying the intelligent harvesting operation of a low-frequency shaker. Through a vibration transmission test involving vibration parameters, tree parameters, and proportional acceleration, this study found that vibration frequency, amplitude, pre-tension, and rope length were the most significant influencing factors of proportional acceleration. Among them, amplitude and pre-tension have positive effects on proportional acceleration, vibration frequency and rope length have negative effects on proportional acceleration, and the interaction between amplitude and vibration frequency has significant effects on proportional acceleration. The proportional acceleration has a maximum response of 8.12 m/s2 when the vibration frequency is 6.86 Hz, the amplitude is 64.92 mm, the pre-tension is 1007.02 N, and the rope length is 6 m. The results of the study can guide research on and development of a low-frequency intelligent shaking machine as well as its field operation. [Display omitted] • Analyze the response laws of vibration parameters and tree parameters. • Explore the importance of each factor in depth. • Determine the interaction response between the factors. • Optimize the best response value for vibration transmission. [ABSTRACT FROM AUTHOR]

Walnut (Juglans regia L.) is a highly valuable crop and is widely used as a food, medicine, and industrial product. Studying walnut detachment force is an important prerequisite for bed harvesting through low-frequency shaking. In this study, the stalk–branch and stalk–fruit kinetic models were analyzed under different vibration modes by establishing a local vibration model. A platform was built to conduct tests of static separation force separately for different modes. The inertial force and static separation force of the vibration response were analyzed by combining each vibration parameter with the local fruit–stalk–branch vibration model, and the separation ratios were derived under different vibration parameters. In the vibration response with a frequency of 10 Hz and amplitude of 80 mm, the maximum separation ratios of inertial tensions at connection points between the branch and stalk, stalk and tail fruit, and stalk and side fruit were 0, 25.5%, and 26.3%, respectively; the maximum separation ratios of the inertial bending moment were 86.4%, 96%, and 83%, respectively; and the detachment difficulty coefficient of the motion mode generating inertial bending moments was much lower than that of the mode generating inertial tensions. The relationship between the separation force and biological characteristics was analyzed, and field vibration tests were conducted to verify the separation force tests. The results of the study can guide development and adjustment of vibration parameters of a vibrating device for harvesting and help further study of the effect of excitation mode on fruit shedding. [Display omitted] • A test method for static separation force is proposed. • The effect of the laws of motion on inertial forces was studied. • The separation ratios were obtained for different vibration parameters. • Changing the vibration pattern can effectively improve the shedding rate. [ABSTRACT FROM AUTHOR]