Three-dimensional (3D) information on crops and soil undulations is important for precision agriculture. Light detection and ranging (LiDAR) has previously been used to obtain highly accurate 3D information. However, with recent advancements in digital technology, photogrammetry, which does not require special sensors, has attracted considerable attention. In this study, models using these two 3D reconstruction methods are compared and their corresponding applications are summarized. The results show that the standard deviation of the height difference between the 3D models of the two methods is 4.1 cm in a 1.7 ha onion field. However, it is inferred that LiDAR is more suitable than photogrammetry for understanding the 3D growth information of slender upright onion plants.

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Anaerobic digestion of high-nitrogen wastes is inhibited by the presence of ammonia. We investigated a method to alleviate this inhibition by reducing free ammonia through pH control in the digester. The pH was reduced to a level lower than usual by adding acid. The results showed that the pH 6.8 could be controlled, without compromising methane production. Furthermore, low pH control enables operating the system under high nitrogen concentrations, up to a total ammonia nitrogen of 10,000 mg L⁻¹, while keeping a free ammonia at 100 mg L⁻¹ or less. This method can contribute to producing liquid fertilizers with high nitrogen concentration derived from highly nitrogenous wastes, and can be used as substitutes for both biomass energy and chemical fertilizers.

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To explore the relationship between agricultural carbon emission effect and food security in Anhui Province, the coupling coordination and spatio-temporal characteristics of agricultural carbon emission effects with food security from 2001 to 2022 were analyzed. The results showed: (1) Agricultural carbon neutrality increased from 2001 to 2022, and spatial distribution pattern was “higher in the north and lower in the south”; (2) Food security increased and spatial manifestation was high in the north and low in the south. Food security was high in the north and low in the south; (3) the coupling coordination degree (W) between agricultural carbon neutrality effect and food security production increased, and the coordination development shifted from basic non-coordination to coordination.

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This research designs and tests a novel microwave heating system to reduce energy consumption and harmful emissions in greenhouses. Unlike traditional methods, microwaves provide a chemical-free solution for air conditioning and soil disinfection, replacing fossil fuels. The project specifically focuses on applying dielectric heating to plants. Its goal was to create a cost-effective system with reasonable initial installation expenses. This paper details the entire process, including the design, simulation, and practical testing of a pilot microwave heater. Results demonstrate that the operational heating cost of this new solution is roughly half that of using common fossil fuels. A functional prototype was constructed and successfully evaluated in a pilot greenhouse. The developed product is now considered almost ready for full-scale industrialization.

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Intercepted light per plant canopy can be estimated using the Monsi–Saeki theory (MS) or spatial images (SI) and is useful for predicting total dry matter accumulation. This study aimed (1) to predict the total dry matter of strawberry (Fragaria × ananassa Duch. cv. “Benihoppe”) using MS, and (2) to develop a prediction model for total dry matter using SI based on MS. Strawberry plants were grown for 154 days, during which growth data and spatial images were collected. The results demonstrated that (1) MS application yielded accurate predictions of total dry matter (root mean square error [RMSE] = 12.1 g m⁻²), and (2) the model based on SI also provided appropriate predictions (RMSE = 20.5 g m⁻²).

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Remote sensing-based onion yield prediction is an effective method for stabilizing yield and streamlining work plans. Onion leaves are elongated and erect, resulting in low crop coverage in aerial images. Conventional methods make it difficult to obtain accurate growth information. To address this, we devised a method to reduce the effects of weeds and soil by implementing mask processing to exclude areas with Normalized Difference Vegetation Index (NDVI) values below 0.2 in NDVI images. Hence, high correlations were obtained between NDVI and biomass index, which was calculated by multiplying grass height and leaf sheath diameter. Furthermore, using high correlations between the biomass index and NDVI, we successfully developed a prediction model with an average RMS error of 816 kg/(10 a).

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Since 2016, the Thai government has promoted collaborative farming groups to enhance the agriculture of small-scale holders. This study examined these collaborative farming groups, focusing on their contribution to local agriculture through interviews with group leaders, questionnaire surveys of members, and analyses of datasets and statistics. The results revealed that farmers contract many mechanical tasks, regardless of the size of their farmland. Further, associations contribute to local agriculture by undertaking machinery work, offering lower prices than the general market, especially for combined harvesters. Additionally, we found that small farmland plots—which decrease the advantages of group-owned large machinery—and an insufficient ability to maintain and operate machinery reduce the capabilities of groups.

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This study evaluated the impact of soil compaction, expressed as bulk density (BD), on spring wheat using field trials with vibratory plate-compacted subplots (BD: 1.17–1.30 Mg/m³). Key soil properties, nutrient uptake, and yield were measured under varying BD. PLSR with cross-validation identified key predictors and was compared with MLR/LR for yield modeling. Moderate compaction (BD3: 1.24 Mg/m³) optimized nutrient utilization, producing 173.6 % more yield than highly compacted soil (BD1). The Control subplots (BD: 1.17 Mg/m³) yielded 143.4 % more than BD1. Spatial analysis showed that combined phosphorus–calcium–magnesium dynamics explained 97.2 % of yield variation (R² = 0.972). Nutrient maps supported precision fertilization planning, showing that soil compaction significantly affects wheat productivity through multiple pathways.

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