Feature Selection Approach for Oil Palm Fruit Grading Expert System

Patkar, Gaurang S.; Morajkar, Sweta C.

doi:10.1109/rteict52294.2021.9573633

Cited by 3 publications

(1 citation statement)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In addition to colour features, spikes texture can be useful for describing the maturity of FFBs, as the size and number of spikes change as the fruit ripens. Furthermore, texture features could be used to investigate the percentage of detached fruit, where Patkar et al (2021) stated that the empty socket feature can improve the accuracy of classifying ripe and overripe fruits.…”

Section: Discussionmentioning

confidence: 99%

A Picture of Ripeness: Investigating Image-Based Techniques for Oil Palm Fruit Grading

ROSBI

2024

JOPR

View full text Add to dashboard Cite

Oil palm is a highly efficient crop that can produce more oil per unit of land than any other type of oil seed. Palm oil it is in high demand, and its production can significantly contribute to a country's economic growth. However, the traditional method of grading palm fruit is still prevalent in Malaysia, which requires skilled workers to classify the harvested fruit according to its ripeness. This approach can be costly and labour-intensive. Therefore, several studies have investigated automated palm fruit classification techniques that could reduce costs and labour in the industry. This paper provides a review of these studies, with a specific focus on vision-based classification techniques. The article discusses approaches based on image processing encompassing pre-processing, feature extraction and classification steps. The survey's resultsindicate that there is a lack of technique to effectively address outdoor images, such as colour correction methods. Therefore, further research is necessary to develop a better segmentation and colour correction procedures. Overall, the findings of this study could help improve the efficiency and sustainability of palm oil production, thereby contributing to economic growth and environmental conservation.

show abstract

Section: Discussionmentioning

confidence: 99%

A Picture of Ripeness: Investigating Image-Based Techniques for Oil Palm Fruit Grading

ROSBI

2024

JOPR

View full text Add to dashboard Cite

show abstract

Artificial Intelligence in Horticultural Crop Improvement

Ghosh

2024

Advances in Plant Breeding Strategies

View full text Add to dashboard Cite

Oil Palm Fresh Fruit Bunch Ripeness Detection Methods: A Systematic Review

et al. 2023

View full text Add to dashboard Cite

The increasing severity of the labour shortage problem in the Malaysian palm oil industry has created a need to explore other avenues for harvesting oil palm fresh fruit bunches (FFBs) such as through autonomous robots’ deployment. However, the first step in using an autonomous system to harvest FFBs is to identify which FFBs have become ripe and are ready to be harvested. In this work, we reviewed previous and current methods of identifying the maturity of fresh fruit bunches as found in the literature. The different methods were then compared in terms of the types of sample data used, sensor modalities, and types of classifiers used with a particular focus on the feasibility of each method for on-field application. From the 51 papers reviewed, which include a total of 11 unique approaches, it was found that the most feasible method for detecting ripe FFBs in the field is a combination of computer vision and deep learning. This system has the advantages of being a noncontact approach that is low cost while also being able to operate in real time with high accuracy.

show abstract

Feature Selection Approach for Oil Palm Fruit Grading Expert System

Cited by 3 publications

References 29 publications

A Picture of Ripeness: Investigating Image-Based Techniques for Oil Palm Fruit Grading

A Picture of Ripeness: Investigating Image-Based Techniques for Oil Palm Fruit Grading

Artificial Intelligence in Horticultural Crop Improvement

Oil Palm Fresh Fruit Bunch Ripeness Detection Methods: A Systematic Review

Contact Info

Product

Resources

About