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Prior to dispatch from manufacturing facilities, seeders require rigorous performance evaluations for their seeding capabilities. Conventional manual inspection methods are notably less efficient. This study introduces a wheat seeding detection approach anchored in an enhanced YOLOv5s image-processing technique. Building upon the YOLOv5s framework, we integrated four CBAM attention mechanism modules into its model. Furthermore, the traditional upsampling technique in the neck layer was superseded by the CARAFE upsampling method. The augmented model achieved an mAP of 97.14%, illustrating its ability to elevate both the recognition precision and processing speed for wheat seeds while ensuring that the model remains lightweight. Leveraging this advanced model, we can effectively count and locate seed images, enabling the precise calculation and assessment of sowing uniformity, accuracy, and dispersion. We established a sowing test bench and conducted experiments to validate our model. The results showed that after the model was improved, the average accuracy of wheat recognition was above 97.55% under different sowing rates and travel speeds. This indicates that this method has high precision for the total number of seed particles. The sowing rate and sowing travel speed were consistent with manual measurements and did not significantly affect uniformity, accuracy, or dispersion. [ABSTRACT FROM AUTHOR]

This study aimed to assess the feasibility of a novel weeding and fertilization scheme, namely, mechanical weeding plus a one-time deep application of a reduced amount of slow-release fertilizer for rice cultivation. The effects of the weeding and fertilization method on rice yield and quality were investigated using a split plot test as the research method. Two weeding methods, namely, chemical weeding (CW) and mechanical weeding (MW), and four fertilization methods were tested, including the conventional fertilization method (quantitative split broadcast application of fast-release N fertilizer (CK)), the quantitative split broadcast application of 80% fast-release N fertilizer (LCK), the one-time base application of slow-release fertilizer (SR), and the one-time deep application of 80% slow-release fertilizer (LSR). The results showed that the rice yield under MW with LSR treatment can maintain a high level—higher than 9.2 t ha−1 per year. This was attributed to the slow-release fertilizer and deep fertilization, which increased the number of stems and tillers in the pre-fertility and spike rate, respectively, resulting in a high panicle number with a 20% reduction of N fertilizer. Furthermore, mechanical weeding improved the seed-setting rate, resulting in a higher number of grains per panicle, a higher panicle number, and an increased thousand-grain weight, thereby maintaining a high yield. At the same time, the quality of rice under MW with LSR treatment improved, specifically reflected in the significant improvement of the processing and appearance quality of rice, a slight increase in protein content, and a reduction in the amylose content, thereby improving its nutritional quality while maintaining good cooking quality. [ABSTRACT FROM AUTHOR]

This study focuses on a wheeled mobile robot used for detection, weeding and information monitoring in agriculture. However, it is difficult to reach satisfactory motion mode switching (MMS) performance. This paper aimed at exploring the optimal control parameters guaranteeing smooth MMS of four-wheel steering. Single factor tests were first conducted using a test-bench. A binary quadratic general rotation combination test was designed to obtain the optimal parameters. An entropy weight method was introduced to construct the four indexes as a comprehensive index. The optimal combination of the parameters was obtained, based on the regression equation. The results showed that the two factors and their interaction had a significant impact on the comprehensive index (p < 0.05). The best combinations of the speed of the stepper motor and locking voltage were 56 r·min−1 and 3.96 V for 15° steering, 72 r·min−1 and 4.35 V for 30°, and 107 r·min−1 and 5.50 V for 45°, respectively. A verification test was performed using the prototype of the robot chassis. The results demonstrated that the MMS process was smooth and stable, and the proposed method was effective. This study is a beneficial exploration of the experimental method concerning wheeled robots. [ABSTRACT FROM AUTHOR]