This paper proposes a method to estimate leaf area from spinach cultivation images using image processing techniques. The proposed method was evaluated, and the results demonstrate that the leaf area can be estimated by interpolating the area of overlapping parts using the ellipse fitting method under dense planting conditions, e.g., the harvest season. Furthermore, the correlation coefficient between the estimated leaf area obtained by the ellipse fitting method and the measured fresh weight was greater than 0.9 in some cases. Additionally, the results suggest that estimating maximum leaf area using this method is an effective way to estimate the fresh weight of the crop.

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This study investigated the comprehensibility of eight safety signs for agricultural machinery. An open-ended questionnaire was provided to 36 agricultural machinery professionals, and closed-ended questionnaires to 40 native users of agricultural machinery, and 26 Vietnamese intern trainees. The percentage of participants who had never seen a certain sign varied from 56.6 % to 81.1 %, averaging 67.9 %. The percentage of professionals who responded accurately varied with the sign from 16.7 % to 91.1 %, averaging 63.9 %. Among the remaining participants, it varied from 38.6 % to 90.0 %, averaging 70.2 %. The native users comprehended the signs better than the trainees. Additional measures like training, or warning devices should be considered to effectively communicate safety messages to users.

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