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Ascertaining the safe sowing date of double-cropping early rice and the change rules of spring climate resources is an important basis for improving use efficiency of spring climate resources and agricultural production efficiency. Based on the daily average temperature data of 79 national meteorological stations in Jiangxi from February 1st to April 30th during the past 30 years (1992-2021), the distribution of safe sowing dates with 50% and 80% guarantee rates of double-cropping early rice with different seedling raising methods in Jiangxi under climate warming were systematically analyzed. The results showed that both average temperature and average pentad temperature increased significantly from 1992 to 2021, the climatic trend rates of average temperature was 0.055 °C·y-1, the most significant periods of climatic mean temperature increase were mainly concentrated in the 5th and 6th pentads in February, the 4th, 5th and 6th pentads in March and the 1st pentad in April, all above 1.5°C. The safe sowing dates of film-mulching dry seedlings, film-mulching wet seedlings, and direct seeding all shown a significant trend in advance, and the advance range from large to small is film-mulching dry seedlings> film-mulching wet seedling> direct seeding. Compared with the traditional sowing time, the safe sowing date of film-mulching dry seedlings in northern and central Jiangxi can be advanced to the end of early March, and which can be advanced to early March in the southern Jiangxi; the time of film-mulching wet seedlings in northern Jiangxi can maintain the traditional sowing date or be advanced to the early of late March, and in the central and southern Jiangxi this time can be advanced to the end of middle March; the time of direct seeding in northern and central Jiangxi can be advanced to 2-3 days before Qingming festival, and in the southern Jiangxi this time can be advanced to the end of late March. [ABSTRACT FROM AUTHOR]

In the 3D reconstruction of plant seedings, factors such as the occlusion between leaves and the camera’s limited field of view often lead to the incomplete of the plant point cloud, which affects the accuracy of plant phenotype analysis. In this study, a plant point cloud completion network based on Multi-scale Geometry-Aware Point Transformer (MGA-PT) was proposed, which adapted to the characteristics of plant point clouds. Firstly, the down-sampling feature extraction module was used to map the raw three-dimensional coordinates to high-dimensional features with the Farthest Point Sampling (FPS) and k-Nearest Neighbour (KNN) algorithm. Not only can this module enhance the feature representation by aggregating local features to reduce the resolution, but also prevent too many input points and reduce the computational burden of the network model. Secondly, a multi-scale geometric-aware module was added in the basic Transformer, which combined semantic features and multi-scale geometric features to form a fusion expression with local information. Multi-head attention mechanism and Feed Forward Network (FFN) were used to extract the semantic features of the plant point cloud, and KNN modules of different scales was used to construct directed local neighbourhood graphs with different resolutions so as to capture various local geometric features and retain geometric relationship information layer by layer. The MGA-PT module promoted the network to have more targeted learning capabilities for different organs such as the leaves and stems of the plants. Then, the dual-path dense point cloud generation module was used to process the input part and the missing part separately. The global features of the plant point cloud were obtained from the encoder, and the missing part of the sparse point cloud and its global features were obtained from the decoder. The sparse three-dimensional coordinates were spliced with the 1 024-dimensional global vector and the two-dimensional grid to facilitate the representation of spatial deformation. The offset of each point was obtained by a folding-based method, so as to expand the point set. It avoided the loss of input point cloud features, and guaranteed a dense point set with realistic distribution. Finally, a dense and complete plant point cloud was obtained by merging the input part and the missing part. The dataset was collected through three-dimensional reconstruction using a low-cost method based on the Structure from Motion (SFM), and the partial point clouds of datasets were obtained by rotation and fixed viewpoint removal. Compared with other models, the method proposed in this study performed well on the plant seedings data. Its average Chamfer Distance (CD) was 0.79×10-4 cm, the Earth Mover’s Distance (EMD) was 0.11 cm, and the F1-score was 70.77%. Moreover, it could complete the seedings point cloud of different plant phenotypic traits and missing proportions, which reflected the stability and robustness of the method. It was also effective for missing point cloud completion under actual occlusion. This model can achieve good results in the completion of leaf plants, and this finding can provide a new idea for the completion of plant point clouds. [ABSTRACT FROM AUTHOR]

In order to determine the effects of lateral deep application of slow-release fertilizer for direct seeding rapeseed in red soil paddy field, 2 a(2018－2020) field experiments covering two winter rapeseed(late-maturity varieties“Dadi 199” and early-maturity varieties“Zhongyou 607”) were conducted with 3 treatments, including no fertilization(F0), broadcast fertilization on soil surface (F1) and lateral deep application fertilizer(F2). The slow-release fertilizer (N 25%, P2O5 7% and K2O 8%) was used with application rate of 750 kg/hm² for late-maturity rapeseed and 600 kg/hm² for early-maturity rapeseed, respectively. At the same time, conventional fertilization experiments were carried out on two rapeseed varieties from 2019 to 2020, and the application levels of slow-release fertilizer were 0, 300, 450, 600, 750 and 900 kg/hm², respectively. Each treatment was repeated 3 times and arranged in random blocks with a plot area of 10 m × 4 m. During the experiments, the air temperature and precipitation were measured. The harveting density, dry matter, seed yield and yield components were mearued. The absorption, agronomic efficiency, partial factor productivity and contribution rate of N, P and K were calculated. The results showed that the yield and fertilizer use efficiency of rapeseed in red-soil paddyfield were significantly affected by fertilizing methods. Moreover, the differences were more significant (P<0.05) for late-maturity varieties and rainy season(2018-2019) than for early-maturity varieties and drought season (2019－2020). Compared with F1, F2 treatment promoted the yield formation and increased the fertilizer use efficiency significantly (P<0.05). Specifically, the technique of synchronous drilling sowing with side deep fertilizing could improve dry matter production during the whole growth period of rapeseed, especially from anthesis to maturity, and with a corresponding rise of dry matter accumulation of both underground and aboveground after anthesis. At the same time, compared to the conventional cultivation, the technique of synchronous drilling sowing with side deep fertilizing increased the absorption of nutrients(N, P and K), effective harvesting density and maintained sufficient pod numbers, and thus improved the yield and fertilizer use efficiency of rapeseed. The optimal quantity of slow-release fertilizer for late-maturity rapeseed and early-maturity rapeseed were 715.39 and 586.39 kg/hm² to target yield of 2 438.94 and 1 708.22 kg/hm², respectively. The study indicated that lateral deep application of appropriate slow-release fertilizer has the potential of improving rapeseed productivity in red-soil paddyfield of southern China and should be suggested to applicate according to the local conditions. [ABSTRACT FROM AUTHOR]

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