Protected cultivation systems such as greenhouses are becoming increasingly popular globally and have been adopted because of unpredictable climatic conditions and their ability to easily control micro- and macroenvironments. However, limitations such as hazardous work environments and shortages in labor are major concerns for agricultural production using these structures. This has led to the development and adoption of robotic systems. For the efficient use of robots in protected cultivation systems, we formulate the work efficiency problem and model a three-dimensional standard strawberry greenhouse to analyze the effectiveness of a strawberry-harvesting robot compared to different levels of human workforce (experienced, average, and beginner). Simulations are conducted using Quest software to compare the efficiency of different scenarios of robotics to humans. Different methods of improvement from battery capacity and charge rate to harvesting speed are investigated and optimal conditions are recommended. The average hourly production of the robot is about five times lower than that of skilled workers. However, robots are more productive due to their ability to work around the clock. Comparative analyses show that a reduction in harvesting time per strawberry from 3 to 1 s would result in an increase in daily production from 347.93 to 1021.30 kg. This would lead to a five-fold increase in comparison to present daily production. A 10% improvement in battery charge time would result in the battery capacity gaining two extra hours from the current 10 h and would cut the current 2 h needed for charge to 1 h. This paper proposes an operation process and suggestions for changes needed for improving the work efficiency of robots in a greenhouse. This could be extended to other crops and greenhouses.

Hot peppers are well known for being spicy and also have a high nutrient content. Human resources have formerly been used to harvest hot peppers; however, a high level of musculoskeletal risk to the human workforce has been reported. Therefore, to reduce the risk to farmers and replace the human workforce, the mechanical harvesting of hot pepper and steps to improve the harvesting efficiency of farmers were conducted. To achieve this, the effect of planting distance on the mechanical harvesting of hot peppers was analyzed at three planting distances (30, 40, and 50 cm) with several cultivars. Subsequently, machine-harvested hot peppers were classified into five groups (marketable, damaged, lost, unharvested, and twigged hot pepper), depending on their postharvest status. The average weight ratio of each group was then calculated, after which statistical analyses were conducted. The effect of planting distance on mechanical harvesting was then analyzed by comparing the differences between each group’s average weight ratio and the total weight of hot pepper, which was simultaneously harvested mechanically at each planting distance. Results showed that the average weight ratio of marketable, unharvested, and twigged hot pepper improved as the planting distance increased. However, no effect on the average weight ratio of damaged and lost hot pepper was observed. The highest yield of marketable hot pepper was found at a planting distance of 40 cm, and the average weight ratio to the whole was lower than at 50 cm of planting distance. Thus, the most suitable planting distance for mechanical harvesting was 40 cm.

Overturning accidents in agriculture offroad vehicles have been reported annually around the world. Safety structures, such as rollover prevention, have been adopted to mitigate these accidents. Despite this, accidents remain persistent but less fatal. This study investigated the safe driving boundary for a multi-purpose platform with attachments (cargo, pepper harvester). Mathematical formulations of the roll and pitch motions for multi-purpose platforms were created. The critical overturning angle, at five load levels for each machine (0, 50, 100, 150, 200 kg), was determined using Recurdyn, a dynamic analysis software. Regression analysis of each coordinate of the center of gravity was conducted to verify the most critical coordinate against gaining loads. The critical overturning angle for the X and Y directions was found. The cargo and pepper harvester had 28.64° and 21.04° of critical overturning angles in the Y direction, respectively, with a full loading state while climbing a steep hill. The regression model of the X, Y, and Z coordinates of CoG suggested that the most critical coordinate of the CoG against the loads was in the Y coordinate for the pepper harvester and the X direction for cargo. This study could be applied to develop an awareness safety system that warns the operator of the risk of a fatal accident.

Hydrogen tractors are being developed, necessitating consideration of the variation in the center of gravity depending on the arrangement of components such as power packs and cooling modules that replace traditional engines. This study analyzes the effects of component arrangement on stability and rollover angle in hydrogen tractors through simulations and proposes an optimal configuration. Stability is evaluated by analyzing rollover angles in various directions with rotations around the tractor’s midpoint. Based on the analysis of rollover angles for Type 1, Type 2, and Type 3 hydrogen tractors, Type 2 demonstrates superior stability compared to the other types. Specifically, when comparing lateral rollover angles at 0° rotation, Type 2 exhibits a 2% increase over Type 3. Upon rotations at 90° and 180°, Type 2 consistently displays the highest rollover angles, with differences ranging from approximately 6% to 12% compared to the other types. These results indicate that Type 2, with its specific component arrangement, offers the most stable configuration among the three types of tractors. It is confirmed that the rollover angle changes based on component arrangement, with a lower center of gravity resulting in greater stability. These findings serve as a crucial foundation for enhancing stability in the future design and manufacturing phases of hydrogen tractors.

In the food industry, meeting food quality demands is challenging. The quality of wheat flour, one of the most commonly used ingredients, depends on the extent of debranning done to remove the aleurone layer before milling. Therefore, the end product management can be simplified by predicting the properties of wheat flour during the debranning stage. Therefore, the chemical and rheological properties of grains were analyzed at different debranning durations (0, 30, 60 s). Then the images of wheat grain were taken to develop a regression model for predicting the chemical quality (i.e., ash, starch, fat, and protein contents) of the wheat flour. The resulting regression model comprises a convolutional neural network and is evaluated using the coefficient of determination (R ²), root-mean-square error, and mean absolute error as metrics. The results demonstrated that wheat flour contained more fat and protein and less ash with increasing debranning time. The model proved reliable in terms of root-mean-square error, mean absolute error, and R ² for predicting ash content but not starch, fat, or protein contents, which can be attributed to the lack of features in the collected images of wheat kernels during debranning. In addition, the selected method, debranning, was beneficial to the rheological characteristics of wheat flour. The proportion of fine particles increased with the debranning time. The study experimentally revealed that the end product diversity for wheat flour can be controlled to provide selectable ingredients to customers.

As the development of electric tractors progresses, battery systems have become a key component, accounting for a significant portion of the vehicle’s total weight. With rollover accidents remaining a leading cause of fatal injuries in agricultural machinery, the stability of electric tractors is drawing increasing attention. In particular, battery placement may critically affect the overall mass distribution and rollover behavior, highlighting the need for safety-focused design optimization. This study evaluates the static rollover stability of a 55 kW electric tractor by analyzing the effect of battery mounting position and comparing it with a conventional tractor. Three tractor models were considered: an electric tractor with a front-mounted battery, one with a center-mounted battery, and a conventional tractor. Multibody dynamic simulations were conducted using RecurDyn, and a total of 24 orientations, at 15° intervals, were simulated to determine the tipping angles in all directions. The results revealed that battery placement had a significant impact on rollover stability. The front-mounted battery type exhibited up to 30% higher tipping angles than the conventional tractor in the forward pitch direction near 90°, indicating improved stability. In contrast, the center-mounted battery type showed a tipping angle distribution generally similar to that of the conventional tractor, with smaller variations across directions. These findings demonstrate the influence of mass distribution on rollover safety and provide valuable insight for structural design of electric tractors.