Automatic Classification of the Ripeness Stage of Mango Fruit Using Machine a Learning Approach

Most mango farms classify the maturity stage manually by trained workers using external indicators such as size, shape, and skin color, which can lead to human error or inconsistencies. We developed four common machine learning (ML) classifiers, the k-mean, naïve Bayes, support vector machine, and feed-forward artificial neural network (FANN), all of which were aimed at classifying the ripeness stage of mangoes at harvest. The ML classifiers were trained on biochemical data and then tested on physical and electrical data.The performance of the ML models was compared using fourfold cross validation. The FANN classifier performed the best, with a mean accuracy of 89.6% for unripe, ripe, and overripe classes, when compared to the other classifiers.

Transcriptome Analysis Reveals the Inducing Effect of Bacillus siamensis on Disease Resistance in Postharvest Mango Fruit

Postharvest anthracnose, caused by the fungus Colletotrichum gloeosporioides, is one of the most important postharvest diseases of mangoes worldwide. Bacillus siamensis (B. siamensis), as a biocontrol bacteria, has significant effects on inhibiting disease and improving the quality of fruits and vegetables. In this study, pre-storage application of B. siamensis significantly induced disease resistance and decreased disease index (DI) of stored mango fruit. To investigate the induction mechanisms of B. siamensis, comparative transcriptome analysis of mango fruit samples during the storage were established. In total, 234,808 unique transcripts were assembled and 56,704 differentially expressed genes (DEGs) were identified by comparative transcriptome analysis. Gene ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of DEGs showed that most of the DEGs involved in plant-pathogen interaction, plant hormone signal transduction, and biosynthesis of resistant substances were enriched. Fourteen DEGs related to disease-resistance were validated by qRT-PCR, which well corresponded to the FPKM value obtained from the transcriptome data. These results indicate that B. siamensis treatment may act to induce disease resistance of mango fruit by affecting multiple pathways. These findings not only reveal the transcriptional regulatory mechanisms that govern postharvest disease, but also develop a biological strategy to maintain quality of post-harvest mango fruit.

A detergent for mango fruit sap-induced injury

This study determined the optimum concentration of, and duration of immersion in a local detergent (“awabla”) that protected fruit skin of Kent and Keitt mango varieties from mango fruit sap-induced injury (sap-burn) at harvest.The resultant skin/peel colour, pulp colour, and total soluble solids content was also evaluated for fruit quality. Randomized Complete Block Design and Completely Randomized Design with four replications in each case were used for field and laboratory experiments respectively. For each of the two varieties, ten mango trees were sampled at random in each of the four replications of a mango plantation.On each sample tree, twenty panicles all initiating fruit-set were identified and tagged. The number of days from fruit-set to physiological maturity were monitored and harvested for the experiments. Concentrations of 0.25,0.50, and 0.75% of “awabla” solution for 25,30,and35 minutes immersion period in all combinations were established as appropriate and recommended for management of Kent and Keitt mango fruit sap-induced injury. The detergent (“awabla”) had a proven efficacy in the range of 87-94 % for Kent and 90-93 % for Keitt. The resultant peel colour, pulp colour, and total soluble solids content of Kent and Keitt mango fruit samples were not significantly influenced by the treatments at p>0.05.

Mango Leaf Disease Recognition and Classification Using Novel Segmentation and Vein Pattern Technique

Mango fruit is in high demand. So, the timely control of mango plant diseases is necessary to gain high returns. Automated recognition of mango plant leaf diseases is still a challenge as manual disease detection is not a feasible choice in this computerized era due to its high cost and the non-availability of mango experts and the variations in the symptoms. Amongst all the challenges, the segmentation of diseased parts is a big issue, being the pre-requisite for correct recognition and identification. For this purpose, a novel segmentation approach is proposed in this study to segment the diseased part by considering the vein pattern of the leaf. This leaf vein-seg approach segments the vein pattern of the leaf. Afterward, features are extracted and fused using canonical correlation analysis (CCA)-based fusion. As a final identification step, a cubic support vector machine (SVM) is implemented to validate the results. The highest accuracy achieved by this proposed model is 95.5%, which proves that the proposed model is very helpful to mango plant growers for the timely recognition and identification of diseases.

Effect of Irradiation process on mango

Mango (Mangifera indica L.) is one of the choicest tropical fruit of the world and rightly designated as "King" of all fruits. It is a nutritionally important fruit being a good source of vitamin A, B and C and minerals. Post-harvest losses in mangoes have been estimated in the range of 25 to 40% from harvesting to consumption stage. Improved practices and preservation have a great impact on retaining mango fruit quality and on the supply chain. Nowadays food irradiation process is an engrained technology for the preservation of foods and food products. Three different kinds of ionizing radiation are applicable for food irradiation processes (Gamma-rays which is emitted from the radio-isotopes Cobalt-60 and Caesium-137, or electron beams and X-rays). Food irradiation can be considered an evolving technique that is capable of increasing the shelf-life, deferring the ripening and senescence of fruits, and thwart of microorganism activity along with insect infestation. Irradiated food is save for human health. This review article is focusing on irradiation effects on mango and the adoption of improved practices by the farmer for export besides that of food safety.

The Effect of Gaseous Ozone and Moringa Leaf–Carboxymethyl Cellulose Edible Coating on Antioxidant Activity and Biochemical Properties of ‘Keitt’ Mango Fruit

This study evaluated the effect of edible coating and gaseous ozone on the antioxidant activities and biochemical properties of mango fruit. Mango fruit (cv. Keitt) were coated with moringa leaf extract and carboxymethyl cellulose (EC) before exposure to ozone (0.25 ppm). Gaseous ozone (O3) was administered intermittently for 24 or 36 h, and the control fruit were untreated. The fruit were stored at 10 °C for twenty-one days, then ripened at ambient temperature for seven days. The parameters measured were ascorbic acid, lipid peroxidation, phenolic content, total sugars, and antioxidant capacity (FRAP and DPPH). At the end of storage, the EC + O3 (36 h) had high phenolic content: 175.02 µg GEA/g DM compared to 151.87 µg GEA/g DM and 138.98 µg GEA/g DM for the O3 (24 h) and untreated fruit, respectively. Moreover, the combination of the EC and O3 (36 h) had a higher effect (p < 0.05) on preserving the antioxidant capacity of the mangoes. The EC + O3 (24 h) and EC significantly delayed fruit softening and maintained membrane integrity. Furthermore, the fruit treated with the EC reduced the accumulation of reducing (7.61 mg/mL) and total sugars (8.81 mg/mL) compared to the control treatment, which had a concentration of 12.74 mg/mL and 13.78 mg/mL, respectively. These findings demonstrate that EC combined with gaseous O3 enhanced the antioxidants of mango fruit during storage.

Synergistic Effect of Methyl Cellulose and Carvacrol Coating on Physicochemical and Microbial Attributes of Mango (Mangifera indica) Fruit in Postharvest Storage

Decay on mango (Mangifera indica) fruit mostly derived from a fungal disease which was caused by anthracnose invasion and infestation. The falling quality of mango fruit during postharvest preservation was commonly associated with weight loss, softening, vitamin C degradation and decay. This research evaluated the synergistic effect of methyl cellulose (MC) and carvacrol (Car) in the preparation of the edible coating on the physicochemical and microbial characteristics of mango fruit during 28 days of storage at 18°C. Five groups of coating treatments were prepared as follows: A (4% MC), B (4% MC + 0.5% Car), C (4% MC + 0.75% Car), D (4% MC + 1.0% Car), E (4% MC + 1.25% Car). These coating solutions were set 40°C for mango dipping. Mango fruits were individually dipped in the respected MC-Car solutions for 15 s and left out to air-condition for 30 min to create the coating film. These mango fruits were then kept at 18°C for 28 days. In 7 day-interval, experimental fruits were sampled to estimate weight loss, firmness, ascorbic acid content, decay index. Mango fruit pre-coated by 4% MC + 1.0% Car showed the least weight loss (1.61±0.03 %) and decay index (2.19±0.03 mark) while the highest retention of firmness (47.13±0.23 N) and ascorbic acid (25.60±0.13 mg/100 g) at the end of 28 days of storage. Results showed that incorporation of 1.0% carvacrol into 4% methyl cellulose-based edible coating would extend the shelf-life of mango fruit for 28 days of preservation. The edible coating would be a promising and green alternative with minimal environmental pollution.