The number of foreign workers in Japan’s agricultural sector has increased, and the use of agricultural machinery has increased considerably over the past decade. This cross-sectional survey investigated the use of agricultural machinery by foreign farm workers, highlighting work-related accidents. Managers of 1,103 farms accredited as “Good Agricultural Practice” were asked to complete a mailed questionnaire between August and October 2020. Results revealed 1,245 foreign workers across 133 farms, with 59.4 % of farms reporting the use of agricultural machinery by these workers. Of the 23 accidents reported involving foreign workers, seven (30.4 %) were related to agricultural machinery. Stakeholders in agricultural occupational safety should recognize the vulnerability of this workforce and develop appropriate preventive measures.

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Combining micro wet milling (MWM) and spray drying (SD) to powder white button mushroom (WBM) is a promising technique to give a higher quality product. The objectives were to determine the optimal number of passes in MWM process and to investigate the effect of different inlet temperatures in combination of MWM and SD process on the physical and chemical properties of WBM powders. The inlet temperature of SD was set to 160, 170, 180, 190 °C. The result showed 3 passes were sufficient to reduce the particle size and there was no significant difference between different inlet temperatures on physical properties of WBM powder, except for the color. MWM and SD process with inlet temperature 180 °C was proposed for powdering WBM.

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Research and development efforts have aimed to achieve a digital transformation in agriculture, with many focusing on large-scale agriculture. Small-scale agriculture constitutes the majority of Japanese farming and remains a crucial area of research field. In this study, a platform for general-purpose small agricultural robots consisting of an application unit and a base unit is proposed. The application unit allows users to customize the functions of the robot according to their specific tasks. Harvesting and monitoring robots were developed, and experiments in various environments verified the performance of each function. These experiments demonstrate the effectiveness of the platform, showing that it can provide functionality with minimal alterations.

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Avocado oil content varies significantly during maturation, complicating harvest timing due to the lack of external indicators. Current oil content measurements rely on destructive methods that are time-consuming, costly, and require toxic solvents. This study explores fluorescence properties of avocado skin wax as a non-destructive maturity indicator. Using excitation-emission matrix (EEM) analysis, two fluorescence peaks associated with phenolic compounds were identified, both decreasing in intensity as the fruit matured. A strong negative correlation (r = −0.86) was observed between fluorescence intensity and oil content. These findings suggest that UV-excited surface fluorescence could enable rapid, non-invasive oil content estimation, paving the way for fluorescence-based imaging systems to enhance harvest management in avocado production.

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