@article{MAKHILLIJSSCEA202114628836,
    title = {Nondestructive Determination of Maturity of the Durian by Mel-Frequency Cepstral
Coefficients (MFCCs)},
    journal = {International Journal of System Signal Control and Engineering Application},
    volume = {14},
    number = {6},
    pages = {72-76},
    year = {2021},
    issn = {1997-5422},
    doi = {ijssceapp.2021.72.76},
    url = {https://makhillpublications.co/view-article.php?issn=1997-5422&doi=ijssceapp.2021.72.76},
    author = {Peerapol},
    keywords = {Mel Frequency Cepstral Coefficient (MFCC),neural network,signal processing,pattern recognition},
    abstract = {The challenging for buyers around the globe to
identify good quality of Durian. For several kinds of
Durian, it may be difficult for buyers to determine the
Durian quality by appearance. The ability to select only
good quality Durian without cutting or cleaving is useful
because buyers will not waste money ordering undesirable
Durian. This study proposes a nondestructive technique to
determine the stages of maturity of durian fruits. The
presented methodology utilizes the concept of pattern
matching. We used the local knocking equipment to
knock the durian for knocked-sound. After that the
knocked-sound was analyzed and generated to
Mel-Frequency Cepstral Coefficients (MFCCs) that is
used to train data for the classifier. Feed-forward neural
network was used for the classifier and can effectively
classification the stages of maturity of durian fruits with
accuracy rate >82%.}
    }