To investigate the effect of aerated irrigation on the soil environment and yield in the root zone of maize, and to provide a basis for the extension of aerated irrigation, a 2-year experiment (2020–2021) was conducted at the Zhanjiang National Soil Quality Observation Experiment Station, with two experimental observations per year (spring-summer and fall-winter) to investigate the effects of aerated irrigation (AI) and non-aerated irrigation (CK) on soil respiration rate, soil temperature, water content, oxygen content, soil bacterial biomass and root biomass. We used partial least square regression analysis (PLSR) to establish the regression equations of soil respiration rate, soil temperature, water content, oxygen content, soil bacterial biomass and root biomass under the two treatments, and the screening of the main soil environmental factors affecting changes in soil respiration rate under aerated irrigation technology. The results showed that, compared with CK, the AI treatment significantly increased the soil respiration rate and soil oxygen content (15.38~17.87% and 18.94~25.17%, respectively), as well as the root biomass and soil bacterial biomass (14.99~19.09% and 35.10~45.59%, respectively), and reduced the soil water content by 5.33~12.71% (p < 0.05). The effects of different treatments on soil temperature were not significant. The mean fruit yield with AI treatment was also 7.16~20.51% higher (p < 0.05) than that with CK, and the stem thickness and leaf area of maize plants were significantly increased (9.31~17.06% and 8.68~15.20%, respectively (p < 0.05)). The regression fitting results showed that the soil respiration rate is quadratic polynomial negatively correlated with soil temperature, water content and soil oxygen, and the power function is positively correlated with root biomass and bacterial biomass under the two treatments. The variable importance for projection (VIP) values of the PLSR model showed a soil temperature VIP = 1.51, soil oxygen content VIP = 1.42 and root biomass VIP = 1.40, demonstrating that aerated irrigation technology can drive soil respiration rate by changing soil oxygen content and root biomass. Furthermore, the improvements in soil aeration conditions and respiration with AI appeared to facilitate the improvement in fruit yields, which also suggests the economic benefits of AI.

In order to solve the problems of existing spiral fertilizer apparatuses, such as the variation in cavity filling rate with rotational speed, fluctuation of fertilizer discharge flow, and inability to discharge fertilizer precisely, a triple-head gradually reducing spiral fertilizer apparatus is designed, which gradually compresses fertilizer particles through the triple-head reducing fertilizer spiral structure to achieve complete cavity filling and uniform fertilizer discharge. The main factors that affect the particle motion state and the structural size of the spiral fertilizer through theoretical analysis are determined, and its theoretical fertilizer discharge amount and rotational speed are calculated. Using EDEM (Discrete Element Method Software 2022) to establish a simulation model of a single-head gradually reducing fertilizer apparatus, the spiral lead reduction percentage x₁, spiral diameter reduction percentage x₂, and rotational speed x₃ are determined as experimental factors, and the filling rate μ and spiral torque Y_average are used as experimental indicators to conduct a simulation study on the secondary universal rotation combination design experiment. The results show that when the rotational speed is 95 r/min, the spiral lead reduction percentage is 60.00~73.21%, the spiral diameter reduction percentage is 86.55~97.05%, the filling rate μ is greater than 95%, and the spiral torque Y_average is less than 16 N·m. In order to further improve the uniformity of fertilizer discharge and ensure the controllable accuracy of fertilizer discharge, comparative verification experiments are conducted on single-, double-, and triple-head gradually reducing spiral fertilizer discharge devices and ordinary spiral fertilizer discharge devices. The results show that the precision of the gradually reducing spiral fertilizer apparatus is better than that of the ordinary spiral fertilizer apparatus. Moreover, it is determined that the three-head style performed best. The triple-head gradually reducing spiral fertilizer apparatus is also validated by randomly adjusting six rotational speeds. The experiment results show that the average deviation of the fertilizer discharge flow rate of the fertilizer apparatus from the preset value is 3.16%. The two have a minor deviation, and the fertilizer precision is high. Precise control of the amount of fertilizer discharged can be achieved by adjusting the rotational speed, and the research can provide a specific reference for the improved design and precise control of the spiral fertilizer apparatus.

Introduction: In order to improve the fertilizer-discharging uniformity of the traditional spiral fertilizer distributor and achieve precise and controllable fertilization, based on the agronomic characteristics of fertilization in pineapple orchards, a notched-blade spiral fertilizer discharger with the mechanism of discontinuous-blade sliding-cutting and pushing-pore fertilization is innovatively designed.Methods: Based on parametric modelling and determining the volume of fertilizer accommodation of the spiral, the theoretical fertilizer-discharging amount of the fertilizer discharger is determined in combination with theoretical analysis. The main factors influencing the fertilization performance of the spiral fertilizer discharger are analyzed using theoretical calculation formulas. The discrete element method is used to simulate the fertilizer-discharging process. By comparing simulation experiments, it is determined that the notched-blade spiral fertilizer discharger has better uniformity than the traditional one. The effects of the number and shape of periodic notched blades on the fertilizer-discharging uniformity are analyzed through single-factor experiments. The L₉ (3⁴) orthogonal table is adopted for conducting orthogonal simulation tests.Results: The test results show that the primary and secondary order of the influence of test factors on test indexes is blade notch shape and periodic blade notch number. When the blade notch is a sector, and the periodic blade has three notches, the fluctuation coefficient of fertilizer discharge uniformity is 27.01%. The results of the bench test show that the uniformity fluctuation coefficient of the notched blade spiral fertilizer discharger is 27.42% when the rotating speed is 60r/min. The experimental and simulation values are consistent. Moreover, the fluctuation coefficient of the spiral fertilizer discharger is reduced by 64.86 percentage points compared with that of the spiral fertilizer discharger under the same conditions. Moreover, the fluctuation coefficient of the notched blade spiral is 64.86% lower than that of the spiral fertilizer discharger under the same conditions. Based on different rotational speeds, the fitting curve of fertilizer discharge is y = 2.02x + 23.02.Conclusion: The fertilizer discharge can be controlled by adjusting the rotating speed. It improves the controlled accuracy and uniformity of fertilizer application and achieves the goal of green and sustainable development of the pineapple industry in the tropics. The research results can provide a reference for designing and optimizing spiral fertilizer dischargers.

The agriculture field is one of the most important fields where computational techniques play an imperative role for decision-making whether it is the automation of watering of plants, controlling of humidity levels, and detection of plant diseases and growth of plants. There are problems in the conventional methods where newer computational techniques and image processing methods are not used to keep track of growth of plants. The traditional image capturing and processing models have problems of large image segmentation error, excessive feature extraction time, and poor recognition output. In order to overcome the problems in the traditional plant growth methods based on image processing automations, computer image processing with computational method has been proposed to analyze the plant growth by utilizing state recognition method for corn and rice crops. An image acquisition platform is established on the basis of CMOS image sensor for crop image acquisition. The binary processing is performed, and then the images are segmented to reduce error of segmentation results in the traditional methods. To extract image features of corn and rice crops, convolution neural network (CNN) with newer architecture is used. According to contour information of images, the block wavelet transform method is used for feature adaptive matching. The binary tree structure is used to divide the growth period of corn and rice crops. The fuzzy mathematical model is also devised to identify the characteristics of crops in different growth periods and to complete the identification of growth state. Experimental results show that the proposed method effectively improves problems of traditional methods with better image recognition effect and reduces the time of feature recognition. The time to extract features by the proposed method is 1.4 seconds, whereas comparative methods such as random forest (RF) take 3.8s and other traditional techniques take 4.9s. Segmentation result error of the recognition method is also reduced significantly.

In view of the lack of considering index weight and less nutritional status classification in maize crop’s nutritional status identification, an identification method of maize crop’s nutritional status based on index weight is studied. Based on the five aspects of Agronomic and soil properties, 15 identification indexes such as plant height and soil available phosphorus content are selected to construct the identification index system of maize crop’s nutritional status. Through the evidence fusion process, the subjective weight calculation method is combined with the objective weight calculation method to calculate each identification index system. The nutritional status of maize crops is divided into nine grades: extreme poor nutrition to extreme severe eutrophication. Samples are generated by random interpolation between the values of grade standard domain. The probabilistic neural network recognition model is constructed, and the randomly generated samples are used to train and test the model to obtain the recognition model architecture that meets the accuracy requirements. The weight of each index and the normalized sample index matrix are calculated and input into the trained recognition model to obtain the recognition results of nutritional status of corn crop samples. The test results show that the index weight obtained by this method has higher reliability and can meet the application needs of maize crop’s nutritional status identification.

The existing fertilizer spreader has suboptimal performance in terms of fertilizer uniformity, lack of controllability of fertilizer spreading width, low utilization rate, and inability to meet the requirements of hills, mountains, and other complex terrains. In response to these shortcomings, we have developed a rotary tube fertilizer spreader for mountainous terrain. This device uses a fertilizer trajectory based on the drop distribution of overlapping prolate cycloids, which enables uniform fertilizer application in both the transversal and longitudinal directions. Based on an analysis of the structure and operating principles of the device, Table L₉ (3⁴) was selected for orthogonal array testing, and the results showed that the transversal fertilizer distribution uniformity (Y₁) and the longitudinal fertilizer distribution uniformity (Y₂) were 14.24% and 12.75%, respectively, when the number of rotating tubes was Z = 3, the angle θ of the rotating tubes with respect to the vertical was 50°, and the length of the rotating tubes was L = 100. The results of the simulation experiments were validated through bench experiments, and the relative errors of the coefficients of variation of traversal and longitudinal fertilizer distribution uniformity in the bench verification experiments were 11.45% and 2.8%, respectively. This demonstrated that the results of the simulation experiments were reliable. A mathematical model was constructed through bench experiments, in which the width of transversal fertilizer spreading (y) was regulated by operating parameters such as the rotational speed of the rotary tube (n) and the height of the tube mouth from the ground (h). The fitting results showed a corrected coefficient of determination of 0.9906. The experimental results were in agreement with the fitted results, thus adapting to crops with 40 cm to 160 cm spacing between rows. This study offers a theoretical foundation for the design of a rotary tube strip fertilizer spreader.