Abstract Tomato is a fruit that undergoes rapid ripening process. Classification of tomatoes based on the level ripeness very important during distribution process in various regions. In general, farmers classify color, because this easy to do. Generally, classification done manually by looking directly with eyes and color fruit. The problem is, identifying still has many shortcomings results a...

• Thermal imaging was used to predict quality attributes of durians. Classification accuracy is higher than 93 % for each classification model. Feature extraction based on thermal images were selected durian classification. The detection ripeness using an essential study geared towards improving the current analytical methods which rely heavily routine analysis and human labour skills. investig...

Coffee ripeness monitoring is a key indicator for defining the moment of starting harvest, especially because coffee quality related to fruit degree. The most used method define start harvesting by visual inspection, which time-consuming, labor-intensive, and does not provide information on entire area. There lack new techniques or alternative methodologies faster measurements that can support ...

The increasing severity of the labour shortage problem in Malaysian palm oil industry has created a need to explore other avenues for harvesting fresh fruit bunches (FFBs) such as through autonomous robots’ deployment. However, first step using an system harvest FFBs is identify which have become ripe and are ready be harvested. In this work, we reviewed previous current methods identifying mat...