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Conservation tillage is a technology regarding sustainable agricultural development, which features less or no tillage and crop stubble covering and has brought significant economic, environmental, and social benefits to China’s agricultural production. As agricultural production in China develops toward the directions of large scale, high efficiency, and intelligence, promoting the development of conservation tillage becomes conducive to cultivated land protection, grain supply security, and agricultural technology improvement. This study reviews the development process of conservation tillage in China from the aspects of research and development of conservation tillage technologies and equipment, demonstration and ability construction, and utilization of black soil in Northeast China. It also summarizes the development status of conservation tillage technologies and equipment in China, involving representative technical models and key machines for surface straw and stubble treatment, shallow soil tillage, and no- or less-tillage sowing. The major factors that affect the development of conservation tillage in China are analyzed, including suitable model and equipment, support of laws and policies, and drive of large-scale planting households. Furthermore, suggestions are proposed to promote the rapid and stable development of conservation tillage in China. First, a national science and technology innovation platform should be built and high-standard demonstration projects should be implemented by counties. Second, national action plans on conservation tillage should be implemented to strengthen policy guidance. Third, publicity of conservation tillage should be further strengthened.

Objective To investigate the mechanisms of 1, 25(OH)2D3 on joint inflammation and bone destruction in a mouse model of collagen-induced arthritis (CIA). Methods Thirty DBA/1J mice were equally allocated into control, CIA and intervention (VD) groups. The CIA model was established in the mice in the CIA group and VD group, meanwhile the VD group was treated with 1, 25(OH)2D3. The thickness of the hindfoot paws was measured with vernier caliper. Micro-CT scanning was used to measure bone mineral density (BMD) of the hindfoot paw, ELISA was employed to detect the serum levels of 1, 25(OH)2D3 and proinflammatory cytokines (IL-1β, IL-6, TNF-α), and flow cytometry was performed to calculate the ratio of Th17 to Treg cells in the spleen. The pathological changes of the knee joint were observed with HE staining. Western blotting was applied to detect the expression levels of osteoprotegerin (OPG), receptor activator of nuclear factor-κB ligand (RANKL), NF-κB, and vitamin D receptor (VDR) in mouse ankle joints. Results 1, 25(OH)2D3 did not reduce the incidence of CIA in the of mice in the VD group, but significantly reduced joint inflammation. Obviously decreased thickness of the hindfoot paw, arthritis score, and knee histological synovitis score (HSS) were observed in the VD group than the CIA group (all P < 0.05). The CIA group presented more serious bone destruction and lower BMD and bone volume fraction (BV/TV) when compared with the VD group (both P < 0.05). The serum levels of IL-1β, IL-6 and TNF-α and ratio of Th17/Treg cells in the VD group were statistically lower than those in the CIA group (all P < 0.05). Compared with the CIA group, the VD group had notably higher protein levels of VDR and OPG, lower levels of NF-κB and RANKL, and reduced RANKL/OPG ratio in the ankle joint (all P < 0.05). Conclusion 1, 25(OH)2D3 may alleviate arthritic inflammation and suppress bone destruction in the mouse CIA model via regulating the Th17/Treg ratio and the RANKL/OPG axis.

The mode transformation of agricultural production is a common concern for China and worldwide. Currently, the level of mechanization has been significantly promoted for the agriculture sector in China and smart production becomes an inevitable trend for modern agriculture. Smart agriculture regards data, knowledge, and intelligent equipment as the core elements and integrates modern science and technology with agriculture to realize digital perception, intelligent decision-making, precise operation, and smart management in the entire process of agricultural production, thereby greatly improving labor productivity, resource utilization rate, and land output rate. This article presents the current status of agricultural production in China using rice production as an example, and analyzes the necessity, opportunities, challenges, directions, and route for the intelligent transformation of China’s agriculture. Furthermore, we propose policy suggestions to promote the intelligent development of China’s agricultural production, including (1) strengthening the research and innovation system for agricultural machinery, (2) improving the agricultural machinery promotion system, (3) optimizing the socialized service system for agricultural machinery, and (4) accelerating the construction of smart agriculture demonstration zones.

Cutting-edge detection is a critical step in mechanized rice harvesting. Through visual cutting-edge detection, an algorithm can sense in real-time whether the rice harvesting process is along the cutting-edge, reducing loss and improving the efficiency of mechanized harvest. Although convolutional neural network-based models, which have strong local feature acquisition ability, have been widely used in rice production, these models involve large receptive fields only in the deep network. Besides, a self-attention-based Transformer can effectively provide global features to complement the disadvantages of CNNs. Hence, to quickly and accurately complete the task of cutting-edge detection in a complex rice harvesting environment, this article develops a Transformer Convolution Network (TCNet). This cutting-edge detection algorithm combines the Transformer with a CNN. Specifically, the Transformer realizes a patch embedding through a 3 × 3 convolution, and the output is employed as the input of the Transformer module. Additionally, the multi-head attention in the Transformer module undergoes dimensionality reduction to reduce overall network computation. In the Feed-forward network, a 7 × 7 convolution operation is used to realize the position-coding of different patches. Moreover, CNN uses depth-separable convolutions to extract local features from the images. The global features extracted by the Transformer and the local features extracted by the CNN are integrated into the fusion module. The test results demonstrated that TCNet could segment 97.88% of the Intersection over Union and 98.95% of the Accuracy in the unharvested region, and the number of parameters is only 10.796M. Cutting-edge detection is better than common lightweight backbone networks, achieving the detection effect of deep convolutional networks (ResNet-50) with fewer parameters. The proposed TCNet shows the advantages of a Transformer combined with a CNN and provides real-time and reliable reference information for the subsequent operation of rice harvesting. [ABSTRACT FROM AUTHOR]

Pineapple harvesting is a key step in pineapple field production. At present, pineapple fruits are usually picked manually. With decreasing labor resources and increasing production costs, machines have been used instead of manual picking approaches in the modern pineapple industry. This paper briefly describes the basic situation of pineapple planting worldwide. Based on the degree of automation of mechanized pineapple harvesting equipment, the main structural forms, core technologies, and operation modes of semi-automatic, automatic, and intelligent pineapple harvesting equipment are summarized. The research status and existing problems of key pineapple fruit picking robots, such as fruit recognition, maturity classification, positioning, and separation of pineapple fruits, are analyzed. Considering the problems of pineapple harvesting equipment, such as difficulty entering the ground, low harvesting efficiency, low picking success rate, and fruit damage, innovative future research directions for mechanized pineapple harvesting technology are proposed, such as combining agricultural machinery and agronomical principles, integrating mechanized, automated, and intelligent technology, and developing modular designs and generalized approaches. [ABSTRACT FROM AUTHOR]

Mechanical hill wet-seeded rice machine is beneficial for establishing and growing uniform rows of seedlings. However, there is limited knowledge regarding the effects of the establishment of furrows on growth, lodging and yield, and their relationships with root traits. In this study, field experiments were conducted during 2012 and 2013 using two super rice varieties (hybrid rice Peizataifeng and inbred rice Yuxiangyouzhan) under three furrow establishment treatments (T1, both water and seed furrows were established by the machine; T2, only seed furrows were established by the machine; and T3, neither water nor seed furrows were established by the machine). Lodging index, lodging-related traits, grain yield, above-ground dry weight and root traits were measured. The results showed that the lodging index was significantly affected by the treatments with furrows (T1 and T2). The strongest lodging resistance was detected in the mechanical hill wet-seeded rice with furrow treatment (T1) in both 2012 and 2013. Lodging resistance was strongly related to the breaking resistance. No significant difference was found in grain yield or dry weight of the mechanical hill wet-seeded rice. Therefore, the mechanical hill wet-seeded rice with furrow treatment increased rice lodging resistance, which was related to root traits.

In order to enhance the efficiency of agricultural machinery in orchard rows and minimize harm to personnel caused by pesticide spraying, this study developed a GNSS-based (Global Navigation Satellite System) automatic navigation driving system for tracked orchard sprayers. The tracked sprayer was used as a platform for this research. We constructed both a crawler hydraulic platform and spraying working parts based on orchard operation requirements. Additionally, we designed the hydraulic and electrical sub-control process of the crawler platform. By utilizing the motion model of the tracked mobile platform, we designed a linear path tracking control method using position deviation and heading deviation as state quantities. This allows the research platform to automatically initiate and terminate, travel in a straight line between rows, and complete spraying operations. Experimental verification confirmed that the tracked sprayer designed in this study successfully achieves automatic driving. The best automatic driving performance is achieved at a speed of 1.0 m/s. When the sprayer's speed is 1.2 m/s, the maximum value of the straight-line path tracking accuracy of the platform's automatic driving is better than 5.6 cm, with a standard deviation of 2.8 cm. This system effectively meets the requirements of automatic operation for an automatic spraying machine, thereby establishing a foundation for the implementation of automatic spraying operations in orchards. [ABSTRACT FROM AUTHOR]