Quality evaluation of mango using non-destructive approaches: A review

doi:10.37865/jafe.2020.0003

Cited by 5 publications

(7 citation statements)

References 47 publications

(50 reference statements)

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“…Quality inspection is the process of evaluating specific parameters of fruits and vegetables to ensure required quality standards ( Phey et al., 2020 ). The intention of quality inspection is to detect any internal or external characteristics that can aid in identifying both standard quality parameters and defects or non-conformities that can affect the safety of fruits and vegetables or their usability in particular functions such as diets, trade, and industrial chains ( Kirezieva et al., 2013 ).…”

Section: Quality Inspection Of Tropical Fruits and Vegetablesmentioning

confidence: 99%

Advancement of non-destructive spectral measurements for the quality of major tropical fruits and vegetables: a review

Aline,

Bhattacharya,

Faqeerzada

et al. 2023

Front. Plant Sci.

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The quality of tropical fruits and vegetables and the expanding global interest in eating healthy foods have resulted in the continual development of reliable, quick, and cost-effective quality assurance methods. The present review discusses the advancement of non-destructive spectral measurements for evaluating the quality of major tropical fruits and vegetables. Fourier transform infrared (FTIR), Near-infrared (NIR), Raman spectroscopy, and hyperspectral imaging (HSI) were used to monitor the external and internal parameters of papaya, pineapple, avocado, mango, and banana. The ability of HSI to detect both spectral and spatial dimensions proved its efficiency in measuring external qualities such as grading 516 bananas, and defects in 10 mangoes and 10 avocados with 98.45%, 97.95%, and 99.9%, respectively. All of the techniques effectively assessed internal characteristics such as total soluble solids (TSS), soluble solid content (SSC), and moisture content (MC), with the exception of NIR, which was found to have limited penetration depth for fruits and vegetables with thick rinds or skins, including avocado, pineapple, and banana. The appropriate selection of NIR optical geometry and wavelength range can help to improve the prediction accuracy of these crops. The advancement of spectral measurements combined with machine learning and deep learning technologies have increased the efficiency of estimating the six maturity stages of papaya fruit, from the unripe to the overripe stages, with F1 scores of up to 0.90 by feature concatenation of data developed by HSI and visible light. The presented findings in the technological advancements of non-destructive spectral measurements offer promising quality assurance for tropical fruits and vegetables.

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Section: Quality Inspection Of Tropical Fruits and Vegetablesmentioning

confidence: 99%

Advancement of non-destructive spectral measurements for the quality of major tropical fruits and vegetables: a review

Aline,

Bhattacharya,

Faqeerzada

et al. 2023

Front. Plant Sci.

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show abstract

“…This approach was generated using the near infrared (NIR) spectroscopy technology, and the data was collected for six days to know how the quality of the fruit had increased as it ripened. Zhen et al [20] introduced a novel grading approach for grading mangoes based on their external features and weight. Mangoes were graded into three grades in terms of length, width, defect, and weight features using the four machine learning models random forest (RF), linear discriminant analysis (LDA), support vector machine (SVM), and K-nearest neighbors (KNN) [21].…”

Section: Introductionmentioning

confidence: 99%

Identification of mango variety using near infrared spectroscopy

Tripathi,

Reddy,

Neelakantappa

et al. 2023

IJEECS

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<p>The structure of the proposed framework is separated into three stages: i) foundation deduction, ii) component extraction, and iii) preparing and characterization. At first, K-implies grouping methods were carried out for foundation de- duction. The second step applies color, texture, and shape-based feature extraction methods. Finally, a “merging” fusion feature is analyzed with a C4.5, support vector machine (SVM), and K-nearest neighbors (KNN). Overall, the recognition system produces an adequate performance accuracy with 97.89, 94.60, and 90.25 percent values by utilizing C4.5, SVM, and KNN, respectively. The experimentation points out that the proposed fusion scheme can significantly support accurately recognizing various fruits and vegetables.</p>

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“…After bananas, mangoes are the second most important tropical fruit plant in Asia [1,2] . It is known as the "king of fruits" because of its outstanding, distinctive flavor, lovely aroma, and plenty of nutritionally advantageous ingredients [3,4] . Because of their great nutritional value, mangoes are recognized as a rich source of calories, fibers, vitamins, and minerals in the human diet.…”

Section: Introductionmentioning

confidence: 99%

Assessment of mycotic diseases attack on indigenous old mango plants grown in Vatala park, Tehsil Bernala District Bhimber, Azad Kashmir

Hussain,

Khan,

Sikander

2023

Nat. Resour. Conserv. Res.

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The current research work was explored fungal attacks on different parts of mango (Mangifera indica L.) trees naturally grown in Tehsil Bernala, District Bhimber Azad Kashmir. Different symptoms were observed, like stem end rot, anthracnose dieback, and blossom blight, during field survey. The identification of mycotic diseases was confirmed by further direct microscopic examination of affected parts of mango trees. Then fungal diseases of mango trees were isolated by microculture and purification methods on different media. Some other parameters, like disease incidence and disease severity rates, were measured against each identified disease through a pathogenicity test under in vitro conditions. It was indicated that maximum disease incidence (DI) was 33.73% measured against dieback disease. The lowest incidence (30.98%) was measured against blossom blight disease. It was also found that disease severity (DS) was rated from 0 to 4 on a visual rating scale.

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Quality evaluation of mango using non-destructive approaches: A review

Cited by 5 publications

References 47 publications

Advancement of non-destructive spectral measurements for the quality of major tropical fruits and vegetables: a review

Advancement of non-destructive spectral measurements for the quality of major tropical fruits and vegetables: a review

Identification of mango variety using near infrared spectroscopy

Assessment of mycotic diseases attack on indigenous old mango plants grown in Vatala park, Tehsil Bernala District Bhimber, Azad Kashmir

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