2020
DOI: 10.37865/jafe.2020.0011
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An overview of non-destructive approaches for quality determination in pineapples

Abstract: Pineapple is one of the healthful and popular tropical fruits in the world. The quality determination of pineapples was mostly evaluated by human inspection which is inconsistent and subjective. The increasing demand for pineapples creates more opportunities for the advancement of rapid and non-destructive approaches to seek quality evaluation of the fruit. This review gives an overview of the non-destructive approaches on the quality determination of pineapples including computer vision, imaging-based approac… Show more

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Cited by 3 publications
(3 citation statements)
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References 39 publications
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“…Contrastingly, trained or supervised learning approaches categorize unknown samples based on traits of known samples or collections of samples with known attributes that are often kept in a reference library and reviewed throughout the analysis. (Alia et al, 2020;Sanaeifar et al, 2017;Shi et al, 2019). The parametric method can be considered based on the probability density function (PDF) and alternately in the non-parametric method, where the PDF is not applicable, the pattern recognition system can regularly be directed with other vehicles such as principal component analysis (PCA), linear discriminate analysis (LDA), partial least square analysis (PLS), functional discriminate analysis (FDA), learning vector quantization (LVQ), and artificial neural network (ANN).…”
Section: Data Acquisition and Pattern Recognitionmentioning
confidence: 99%
“…Contrastingly, trained or supervised learning approaches categorize unknown samples based on traits of known samples or collections of samples with known attributes that are often kept in a reference library and reviewed throughout the analysis. (Alia et al, 2020;Sanaeifar et al, 2017;Shi et al, 2019). The parametric method can be considered based on the probability density function (PDF) and alternately in the non-parametric method, where the PDF is not applicable, the pattern recognition system can regularly be directed with other vehicles such as principal component analysis (PCA), linear discriminate analysis (LDA), partial least square analysis (PLS), functional discriminate analysis (FDA), learning vector quantization (LVQ), and artificial neural network (ANN).…”
Section: Data Acquisition and Pattern Recognitionmentioning
confidence: 99%
“…For example, image processing is used to identify and classify mangoes based on specific grades (Sahu & Dewangan, 2017;Mulani et al, 2017) or extract their physical parameters (Venkatesh et al, 2015;Chauhan et al, 2018). Image processing has also been utilized to assess the ripeness of bananas (Prabha & Kumar, 2015;Sandra et al, 2020), the quality of pineapples (Ali et al, 2020), and estimate the total soluble solids content of mangoes (Shamili, 2019). Saputra et al (2022) developed a method to estimate the amylose content of rice grains based on their color intensity.…”
Section: Introductionmentioning
confidence: 99%
“…Visual inspections are usually conducted by well-trained workers. Such human inspections are inconsistent and subjective [3]. As production volumes grow, the number of cases in which visual inspections are performed inaccurately may increase as well.…”
Section: Introductionmentioning
confidence: 99%