Review: Some common disease in mango

Rosman, N. F.; Asli, N. A.; Abdullah, Sidrat; Rusop, M.

doi:10.1063/1.5124649

Cited by 5 publications

(5 citation statements)

References 2 publications

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“…The panicles and open flowers also develop tiny black spots that eventually grow and kill the plant. Flowers affected by anthracnose are dry and dark brown to black in hue ( Rosman et al, 2019 ). It is estimated that the disease causes 30–60% damage economically, which can climb to 100% in fruits produced during humid seasons or at the commencement of rains ( Kamle and Kumar, 2016 ).…”

Section: Symptoms Of Mango Anthracnosementioning

confidence: 99%

Mango anthracnose disease: the current situation and direction for future research

Dofuor,

Quartey,

Osabutey

et al. 2023

Front. Microbiol.

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Mango anthracnose disease (MAD) is a destructive disease of mangoes, with estimated yield losses of up to 100% in unmanaged plantations. Several strains that constitute Colletotrichum complexes are implicated in MAD worldwide. All mangoes grown for commercial purposes are susceptible, and a resistant cultivar for all strains is not presently available on the market. The infection can widely spread before being detected since the disease is invincible until after a protracted latent period. The detection of multiple strains of the pathogen in Mexico, Brazil, and China has prompted a significant increase in research on the disease. Synthetic pesticide application is the primary management technique used to manage the disease. However, newly observed declines in anthracnose susceptibility to many fungicides highlight the need for more environmentally friendly approaches. Recent progress in understanding the host range, molecular and phenotypic characterization, and susceptibility of the disease in several mango cultivars is discussed in this review. It provides updates on the mode of transmission, infection biology and contemporary management strategies. We suggest an integrated and ecologically sound approach to managing MAD.

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Section: Symptoms Of Mango Anthracnosementioning

confidence: 99%

Mango anthracnose disease: the current situation and direction for future research

Dofuor,

Quartey,

Osabutey

et al. 2023

Front. Microbiol.

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“…These problems are caused by pests and diseases witch kill about 30% -40% of the crop [2]. Mango diseases are caused by a number of pathogens like bacteria, fungi, virus, algae and insect which attack all the parts of the plant, such as trunk, brunch, leaf, twig, petiole, flower and fruit [1] [2] [8]. The causes of these diseases can also be of climatic origin or unfavorable environmental conditions [9] [10].…”

Section: A Review Of the Most Common Mango Diseasesmentioning

confidence: 99%

“…Mango (Magnifera Indica L.) is a lucrative fruit widely grown in tropical countries. This fruit belongs to the anacardiaceous family [1]. It contains significant amounts of vitamin A and vitamin C [2].…”

Section: Introductionmentioning

confidence: 99%

“…It contains significant amounts of vitamin A and vitamin C [2]. It is called the "King of fruits" because of its alluring aroma, flavorful pulp and high nutritional value that attract many mango lovers from around the world [1] [3]. In 2021, mango was the third most traded tropical fruit after pineapple and avocado in terms of quantities exported.…”

Section: Introductionmentioning

confidence: 99%

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Mango Diseases Classification Solutions Using Machine Learning or Deep Learning: A Review

Faye¹,

Diop²,

Dione³

2022

JCC

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The mango crop suffers from several diseases that reduce both the production and the quality of the mangoes. This also reduces its price on the international market. Diagnosis of these diseases remains difficult in many countries due to poverty and lack of infrastructure. Plant pathologists use several techniques to identify these diseases. But these techniques are time consuming and relatively expensive for mango growers and the solutions proposed are often not very accurate and sometimes biased. In the last decade, researchers have proposed several solutions in the field of automatic diagnosis of mango diseases. Such solutions are based on Machine Learning (ML) and Deep Learning (DL) algorithms. In this paper, we divided these solutions into two groups: solutions based on classical ML algorithms, and those based on DL. In recent years, DL, especially Convolutional Neural Network (CNN) has become the most widely used method by researchers because of its impressive performance. The critical analysis of the proposed solutions has allowed us to identify their limits and potential challenges in mango disease automatic diagnosis.

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“…Although a large number of diseases affect mango orchards, only some of them are causing great loss to the economy of the country. A few of the more common diseases [8] include powdery mildew, sooty mold, anthracnose and apical necrosis, as shown in Figure 1. In the current era, computer scientists are aiming to devise computer-based solutions to identify the diseases in their initial phase.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2021

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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.

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Review: Some common disease in mango

Cited by 5 publications

References 2 publications

Mango anthracnose disease: the current situation and direction for future research

Mango anthracnose disease: the current situation and direction for future research

Mango Diseases Classification Solutions Using Machine Learning or Deep Learning: A Review

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

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