Mango Industry Research Articles

Postharvest white light combined with different UV-B doses differently promotes anthocyanin accumulation and antioxidant capacity in mango peel

Fruit peel color is an important index of mango fruit quality. Therefore, increasing the anthocyanin accumulation and improving coloration in red mango are crucial for mango industry. The anthocyanin accumulation in mango is light-regulated. However, the effect of white light combined with different doses of UV-B on anthocyanin biosynthesis has not been clarified. Also lacking is a comprehensive analysis of responses of mango fruit peel to UV-B/white light treatments. In this study, green mature ‘Guifei’ mango fruits were subjected to white light combined with low (WL + UV-BL) or high dose UV-B (WL + UV-BH). Anthocyanin concentration, anthocyanin-related gene expression, reactive oxygen species (ROS), antioxidant, and plant hormone concentrations, and antioxidant enzyme activity were measured. The results showed that especially a WL + UV-BH regimen promoted anthocyanin formation in mango peel. Anthocyanin- and light signal-related gene expression, ROS content, antioxidant enzyme activity, antioxidant concentrations, and total antioxidant capacity were also increased by UV-B/white light. Such treatments led to higher concentrations of jasmonic acid and cytokinin, but decreased content of 1-aminocyclopropane-1-carboxylic acid and salicylic acid. Commercially, our findings may contribute to improving the commercial quality of mango. Scientifically, the present data sheds light on the mango fruit peel-specific molecular and physiological response network under UV-B/white light treatments.

Prediction of Thrips Damage Distribution in Mango Orchards Using a Novel Maximum Likelihood Classifier

Thrips constitute the primary pest responsible for reducing mango yield and quality every year in Asia. Therefore, the efficient monitoring of thrips damage across mango orchards on a large scale to aid farmers in devising rational pesticide application strategies poses a significant challenge within the current mango industry. This study designs a mango thrips damage inversion prediction method based on the maximum likelihood classifier (MLC). Initially, drone multispectral remote sensing technology is utilized to acquire multispectral data from mango orchards, which are then combined with ground hyperspectral information to identify sensitive bands indicative of mango leaf damage caused by thrips. Subsequently, correlation analysis is conducted on various vegetation indices, leading to the selection of the Greenness Normalized Difference Vegetation Index (GNDVI), which exhibits a strong correlation coefficient of 0.82, as the spectral characteristic parameter for the inversion prediction model. The construction of a remote sensing prediction model for thrips damage distribution in mango orchards is then undertaken based on the MLC. Acknowledging the bias-variance trade-off inherent in the MLC when processing spectral data and its potential limitations in feature extraction and robustness, this study proposes a modification wherein neighboring pixels are weighted differently to enhance the model’s feature extraction capabilities. Experimental results show that the novel MLC maintains stable estimation levels across various numbers of domain pixels, achieving an inversion accuracy of 91.23%. Through the reconstruction of the pixel matrix, the damage distribution of thrips in mango orchards can be swiftly and comprehensively visualized over extensive areas.

Non-destructive methods for mango ripening prediction: Visible and near-infrared spectroscopy (visNIRS) and laser Doppler vibrometry (LDV)

With up to 19% of mango fruit being lost during ripening, the need for non-destructive technologies to predict internal physiochemical traits is paramount. This study compared two non-destructive technologies, visible and near-infrared spectroscopy (visNIRS) and laser Doppler vibrometry (LDV), for predicting the ripeness of mango fruit in two cultivars, ‘Kent’ and ‘Keitt’. An internal quality index (IQI) in ‘Kent’ was predicted using visNIRS (RP2 = 0.729, RMSEP = 0.532) using partial least squares regression, which gave a single measure for ripeness incorporating firmness, sweetness, and pulp colour. This model was improved by using the sum of the individual sugar contents (glucose, sucrose, and fructose) over the conventional total soluble solids (TSS) measure. LDV provided poor predictions of firmness (R2 < 0.5) in both ‘Kent’ and ‘Keitt’ using least squares regression line. The resonant frequency, as measured by LDV, decreased linearly with time, while firmness quantified destructively (quasi-static) showed an exponential decrease, suggesting the vibrational and destructive firmness measure distinct characteristics, which would contribute to poor model performance. These results showed that LDV is not suitable for assessing mango ripening. While visNIRS models have been successful at predicting quality traits, our results suggested that using individual sugar content in place of TSS can improve the prediction of ripening. This understanding of the strengths and limitations of both visNIRS and LDV, and how they relate to destructive quality measurements, can be used to improve postharvest management practices whilst reducing commercial losses in the mango industry.

FARMER TO CONSUMER – AN ONLINE SUPPLY CHAIN PROCESS SYSTEM USING BLOCKCHAIN TECHNOLOGY

Globally, the mango industry is one of the largest industrial sectors – also considered the backbone industry of the country’s agriculture sector. This sector mobilizes key industrial activities of many economies, such as agriculture, production, handling, storage, logistics, certification, and packing of a variety of mangoes (e.g., with over 1,500 varieties, of which at least 30 are grown commercially in Pakistan). From local, regional, and national, to international levels, many businesses in this sector are involved in extensive mango supply networks fulfilling the demands of many consumers and markets (e.g., B2B, B2C, etc.) locally worldwide. Currently, 43% of total farmers in Pakistan are smallholder farmers, as they possess less than 2.6 hectares of land. Intermediaries dominate the entire supply chain in Pakistan, due to which small to average farmers face several challenges. This can be avoided by developing a user-friendly system to link farmers directly to the market or consumers. The proposed system identifies the gaps in the process model of Pakistan’s mango supply chain system. It creates a platform to link farmers directly to the market or consumers through a seamless online system using blockchain technology for performing reliable transactions using smart contracts. The proposed system is implemented through Ethereum, a permissioned blockchain network using Smart Contracts. It is a distributed ledger accessible to participants of the supply chain with permission to ensure the trust and authenticity of the information. By using this system, the farmers will attain increased profit through direct access to retailers, consumers, and the international market.

Application of heat pump drying technology to produce dried mango products from Tu Quy mango (Mangifera india L.), Vietnam, on a pilot scale

In this study, the heat pump drying technique was applied to develop the production process of dried mango from Tu Quy mango sources, Ben Tre province, Vietnam. The experiment was performed in three steps. First, mango slices were treated through the blanching process. Samples were pretreated with sizes from 6 to 12 mm at 80–95°C for 3–6 min, and then the mango slices were soaked in a syrup solution concentration range of 25–40°Bx, citric acid of 0.5–2%, and glycerol of 0.1–0.4% at 35–65°C for 90–180 min. Finally, the samples were dried using a pilot-scale heat pump dryer until the moisture content reached 14–16%. The results showed that the blanching and osmosis processes were carried out under optimal conditions to inactivate the Polyphenol oxidase (PPO) enzyme, obtain maximum polyphenol compounds, and conform to the product appearance. Additionally, the drying process was carried out at 30°C for 1,080 min with the polyphenol content retaining 11.71 mgGAE/gDW—This signifies a successful endeavor in developing production methodologies and expanding the range of mango-derived products. Employing innovative technological processes enhances both the quantity and quality of the products. Moreover, the manufacturing procedure was executed on a pilot device, streamlining the synchronization of large-scale production processes effortlessly. This advancement not only enhances economic value but also addresses the issue of congestion prevalent in the current state of the mango industry in Vietnam.

Characterization of Market and Labor Dynamics of the Local Mango Industry in Island Garden City of Samal (IGaCoS), Davao del Norte, Philippines

Understanding the inherent characteristics of a local agricultural industry is imperative in designing policies that are responsive to the context, needs, and challenges of its stakeholders. Grounded in this premise, this study unpacked the complexities of the mango industry in the Island Garden City of Samal, an agricultural city in the southern Philippines. Specifically, it aims to understand its labor dynamics and market arrangements using a qualitative approach. This study presents an overview of the mango production cycle in the garden city, which includes the corresponding labor requirements and market of the local mango industry. In terms of labor, aside from the quantity and quality of labor needed, this paper also presents the roles of men and women that are inherent in local mango production. Likewise, the study also enumerates the different issues and challenges faced by the local mango producers. These issues and challenges were concerns related to erratic prices, labor needs, and high production costs. Moreover, the study offers explanations for the existing labor dynamics in the garden city. This includes the interplay between the material nature of the commodity and the gender dynamics in the labor force. In addition, a discussion on the varying quality standards of different target markers is also provided. Finally, this study also explained the rationale behind the prevailing contractual arrangements within the local mango industry. The results presented in this paper offer insights into designing context-based programs and policies, which could further support the local mango industry.

Valorization potential of Egyptian mango kernel waste product as analyzed via GC/MS metabolites profiling from different cultivars and geographical origins

Increasing attention has been given to mango (Mangifera indica) fruits owing to their characteristic taste, and rich nutritional value. Mango kernels are typically discarded as a major waste product in mango industry, though of potential economic value. The present study aims to outline the first comparison of different mango kernel cvs. originated from different localities alongside Egypt, e.g., Sharqia, Suez, Ismailia, and Giza. Gas chromatography–mass spectroscopy (GC–MS) post silylation analysis revealed that sugars were the major class being detected at 3.5–290.9 µg/mg, with some kernels originating from Sharqia province being the richest amongst other cvs. In consistency with sugar results, sugar alcohols predominated in Sharqia cvs. at 1.3–38.1 µg/mg represented by ribitol, iditol, pinitol, and myo-inositol. No major variation was observed in the fatty acids profile either based on cv. type or localities, with butyl caprylate as a major component in most cvs. identified for the first time in mango. Regarding phenolics, Sedeeq cv. represented the highest level at 18.3 µg/mg and showing distinct variation among cvs. posing phenolics as better classification markers than sugars. Multivariate data analyses (MVA) confirmed that the premium cvs “Aweis and Fons” were less enriched in sugars, i.e., fructose, talose, and glucose compared to the other cvs. Moreover, MVA of Zabdeya cv. collected from three localities revealed clear segregation to be chemically distinct. Sharqia originated mango kernels were rich in sugars (e.g., glucose and fructose), whilst sarcosine esters predominated in other origins.

Climate Changes and Mango Production (Temperature)

The mango, known as the {king of fruits}, is commercially significant in many parts of the world. In addition to offering a delicious tropical flavor, mangoes are a great source of nourishment and can make eating a satisfying and healthy sensory experience. Even though mango farming is known to exist in more than 120 nations, just 15 of them are responsible for more than 1% of the world’s supply. More than 60% of the mangoes produced worldwide are grown in India, China, Thailand, Indonesia and Mexico. The effects of climate change on agriculture must take into account the increasing CO2 concentration, a significant contributor to climate change, as CO2 is essential to critical plant functions, including photosynthesis. The fluctuation of temperature represents another climatic factor that affects mango productivity. The primary challenge facing the mango industry is irregular cultivation. The mango flowering was negatively impacted by the erratic distribution of cold nights and relatively warm winters. Mango output is already being impacted by rising average maximum temperatures. Therefore, regardless of mango growers, geniuses, or consumers, rapid climate change should be a top priority. A benefit of selection and breeding operations to adapt to climatic change is the high genetic variety of mangoes.

Understanding the complexity of the Indonesian fresh mango industry in delivering quality to markets: A systems thinking approach

In response to anticipated export demand growth and the expansion of the modern domestic market, the Indonesian mango industry faces both opportunities and challenges in elevating the production of high-quality mangoes. This industry’s complexity, characterised by various actors with wide-ranging interests, poses a key challenge. We implemented a systems thinking approach in this study to comprehend this complex Indonesian mango value chain and identify deep-rooted issues that could obstruct high-quality mango production. Our research employed participatory group model building with primary actors and stakeholders, which disclosed that conventional agricultural management practices, inadequate postharvest handling, and a lack of coordinated quality standards are key drivers of low-quality mango production. By utilising system archetypes—interpretive tools capturing complex food system behaviour—we demonstrate that adopting clear market orientation through mutual contractual arrangements and fostering collaboration among key actors can significantly influence high-quality mango production. This study provides a nuanced understanding of the underlying factors affecting system behaviour over time, a component often overlooked in traditional value chain analysis. As a result, policy formulation can better address the root causes of Indonesia’s low production of high-quality mangoes.

Integrating Remote Sensing and Weather Variables for Mango Yield Prediction Using a Machine Learning Approach

Accurate pre-harvest yield forecasting of mango is essential to the industry as it supports better decision making around harvesting logistics and forward selling, thus optimizing productivity and reducing food waste. Current methods for yield forecasting such as manually counting 2–3% of the orchard can be accurate but are very time inefficient and labour intensive. More recent evaluations of technological solutions such as remote (satellite) and proximal (on ground) sensing have provided very encouraging results, but they still require infield in-season sampling for calibration, the technology comes at a significant cost, and commercial availability is limited, especially for vehicle-mounted sensors. This study presents the first evaluation of a ”time series”—based remote sensing method for yield forecasting of mango, a method that does not require infield fruit counts and utilizes freely available satellite imagery. Historic yield data from 2015 to 2022 were sourced from 51 individual orchard blocks from two farms (AH and MK) in the Northern Territory of Australia. Time series measures of the canopy reflectance properties of the blocks were obtained from Landsat 7 and 8 satellite data for the 2015–2022 growing seasons. From the imagery, the following vegetation indices (VIs) were derived: EVI, GNDVI, NDVI, and LSWI, whilst corresponding weather variables (rainfall (Prec), temperature (Tmin/Tmax), evapotranspiration (ETo), solar radiation (Rad), and vapor pressure deficit (vpd)) were also sourced from SILO data. To determine the relationships among weather and remotely sensed measures of canopy throughout the growing season and the yield achieved (at the block level and the farm level), six machine learning (ML) algorithms, namely random forest (RF), support vector regression (SVR), eXtreme gradient boosting (XGBOOST), RIDGE, LASSO and partial least square regression (PLSR), were trialed. The EVI/GNDVI and Prec/Tmin were found to be the best RS and weather predictors, respectively. The block-level combined RS/weather-based RF model for 2021 produced the best result (MAE = 2.9 t/ha), marginally better than the RS only RF model (MAE = 3.4 t/ha). The farm-level model error (FLEM) was generally lower than the block-level model error, for both the combined RS/weather-based RF model (farm = 3.7%, block (NMAE) = 33.6% for 2021) and the RS-based model (farm = 4.3%, block = 38.4% for 2021). Further testing of the RS/weather-based RF models over six additional orchards (other than AH and MK) produced errors ranging between 24% and 39% from 2016 to 2020. Although accuracies of prediction did vary at both the block level and the farm level, this preliminary study demonstrates the potential of a ”time series” RS method for predicting mango yields. The benefits to the mango industry are that it utilizes freely available imagery, requires no infield calibration, and provides predictions several months before the commercial harvest. Therefore, this outcome not only presents a more adoptable option for the industry, but also better supports automation and scalability in terms of block-, farm-, regional, and national level forecasting.

Fresh-Cut Mango Best Management Practices Manual

The National Mango Board (NMB), an instrumentality of the US Department of Agriculture, commissioned this work to assist the mango industry. Every effort has been made to ensure the accuracy and completeness of the information. However, NMB makes no warranties, expressed or implied, regarding errors or omissions and assumes no legal liability or responsibility for loss or damage resulting from the use of information contained in this document. Mention of a trademark or proprietary product is for identification only and does not imply a guarantee or warranty of the product by the US Department of Agriculture. The US Department of Agriculture prohibits discrimination in all its programs and activities on the basis of race, color, national origin, gender, religion, age, disability, political beliefs, sexual orientation, and marital or family status.

Food Traceability in Agriculture Value Chain: Evidence from Pakistani Mango Growers

Several incidents, including food adulteration, misinterpretation of food characteristics, and, most recently, the spread of the Covid-19 disease, have stunned consumer confidence and bolstered the need for creating traceability in the Food Supply Chain. This study aims to assess the knowledge level of mango growers food traceability and assess factors influencing their intention toward a scientific traceable value chain in Multan, Pakistan. The study also examines the perceived challenges in implementing a traceable value chain in the mango industry. However, 40 mango growers were purposively selected. Data were collected through interview schedules using structured and unstructured questionnaires. The empirical results show that respondents had a low level of knowledge regarding the mango traceable value chain. Also, the results from multiple regression analysis revealed that knowledge and attitude have a statistically significant positive impact on growers' intention toward the mango traceable value chain. However, the study highlighted a lack of awareness, skills, and resources as challenges preventing growers from implementing a scientifically traceable mango value chain. The findings provide valuable inputs for policymakers to design an effective training program to develop the culture of traceability practices among mango growers and other stakeholders in the industry in Pakistan.

A CASE STUDY ON THE TRADE OF MANGOES IN NEPAL

Given the country’s advantageous agro-climatic conditions that promote the development of premium mango types, Nepal’s mango industry has attracted a lot of interest. To examine the trade dynamics of Nepalese mangoes, this study will look at production trends, varietal diversity, post-harvest procedures, and problems with market access. The complex regulatory system that governs mango exports and the numerous difficulties that mango growers and exporters face are given special attention. These difficulties include market access difficulties, logistical bottlenecks, infrastructure constraints, and the unavoidable requirement for conformity with international quality standards. The tremendous prospects that still exist for increasing mango exports from Nepal are also highlighted by this study. These include taking advantage of nearby markets like India, broadening product lines with value-added mango products, and taking advantage of the rising demand for organic and exotic fruits around the world. The report also emphasizes how crucial government support programs and public-private partnerships have been in promoting the expansion of the mango trade.

Location of seed spoilage in mango fruit using X-ray imaging and convolutional neural networks

Detection of the internal damage and insect infestation on intact mango fruit during harvesting, storage, and exportation is particularly challenging. Visual comparison of infestation by spot detection has proven unreliable in determining the presence of insects in seeds and the extent of spoilage in the fruit. The study aimed toward identifying a non-destructive, rapid, and correct method for detecting spoilage in mango seeds. Ninety-eight (98) mature green mango fruits were harvested from a farm (Kintampo, Ghana) for the experiment. The mangoes were numbered for photographic and X-ray imaging. The images were visually examined and classified based on morphology into mango fruit with good seed and bad seed. The dataset was then augmented into 8000 images and split into train (4000) and test (4000) sets. A VGG16 Deep Convolutional Neural Network (DCNN) model was trained, tested, cross-validated (five-fold), and evaluated by saliency maps on visualization algorithm, Grad-weighted Class Activation Mapping, Grad-CAM, and the Confusion matrix to ascertain its capacity to identify bad seed from good seed. The model achieved an accuracy rate of 97.66% and 0.988 area under the receiver operations characteristics curve. Further application of this model in the mango industry could promote non-destructive early detection of seed deterioration on the field and enhance the quality of products throughout the postharvest supply chain.

Research Progress on Mango Post-Harvest Ripening Physiology and the Regulatory Technologies

Mango (Mangifera indica L.) is an important tropical fruit with a delicate taste, pleasant aroma, and high nutritional value. In recent years, with the promotion of the rural revitalization strategy and the development of the poverty alleviation industry, China has gradually become an important mango producer. However, the short shelf life of mango fruit, the difficulty in regulating the postharvest quality, and the lack of preservation technology are the main problems that need to be solved in China's mango industry. In this paper, the physiological changes and mechanisms of mango during postharvest ripening were summarized, including sugar and acid changes, pigment synthesis and accumulation, and aroma formation and accumulation. The physical, chemical, and biological technologies (such as endogenous phytohormones, temperature, light, chemical preservatives, and edible coatings) commonly used in the regulation of mango postharvest ripening and their action principles were emphatically expounded. The shortcomings of the existing mango postharvest ripening regulation technology and physiological mechanism research were analyzed in order to provide a reference for the industrial application and development of mango postharvest.

Characterization of Soil-Plant Leaf Nutrient Elements and Key Factors Affecting Mangoes in Karst Areas of Southwest China

Baise city is one of the largest producers of mangoes, with this agricultural industry located in the karst region of Southwest China. However, calcium-rich and alkaline soils, severe soil fragmentation, and poor water and fertilizer retention capacity contribute to low mango yields and are key issues that limit the development of the mango industry in karst areas. Our study objectives were to identify the soil factors that limit mango growth and yield in the karst region of Southwest China, and to determine how these growth- and production-limiting conditions vary between landscape positions. This study analyzed the differences in soil nutrient and element contents in mango leaves, and used a Random Forest algorithm to calculate the eigenvalues of the mango leaf and soil elemental indices in the different geomorphic parts (slopes, transition zone, passes, high-yielding depressions, and low-yielding depressions) of the karst peak-cluster depressions. The key factors affecting the mango leaves and soil were screened based on the diagnostic results and the eigenvalues. The results showed that for the elemental contents of Fe, Mg, Ca, and Mn in the mango leaves in the different geomorphic parts of the karst, the peak-cluster depressions were generally deficient and varied significantly. The contents of available B (AB), soil organic matter (SOM), pH, total nitrogen, available Fe, available Mn, alkaline hydrolysis nitrogen, exchangeable Ca (Caex), exchangeable Mg, and other indices in the soils differed significantly, and AB, available Zn, and available K (AK) showed low or very low content levels. In addition, the key soil factors limiting mango yield in the karst areas were AB, fulvic acid, SOM, Fe, Mn, Caex, soil water, and AK; and the key mango leaf factors were Ca, Mn, Fe, Zn, and Mg. Consequently, the characteristics of soil water content, pH, and soil organic matter may be the main drivers affecting the differences in the mango yield and the elemental characteristics. These findings suggest that the addition of organic fertilizer could improve the quality and yield of mangoes in karst areas.

Profitability and cost estimates for producing Mango (Mangifera Indica L.) in south Florida

This publication provides an estimate of the costs and returns associated with an established mango orchard in south Florida. It demonstrates that mangos are a profitable alternative for growers in south Florida, with growers earning on average $4,487/acre/year or $0.24/pound, which is larger than many other tropical fruits. Information in this publication will be useful to current and future mango growers, wholesalers, and processors interested in expanding the mango industry in south Florida.

Mango Industry Development Status of China in 2020

China has been the second largest mango cultivation country in the world in 2020.Mango has become the main source of income for mango farmers in some southern provinces and regions such as Guangxi, Yunnan, Hainan and Sichuan. At present, there are more than 40 different varieties cultivated in China. Through the combination of varieties and different climatic regions, and the adoption of comprehensive technical measures such as moving the harvest time forward and postponing the harvest time, China has become the only country in the world that can produce mango annually. At the same time, China has widely adopted a series of technical measures, such as topworking, bagging, integrated disease and pest control, water and fertilizer integration, intercropping cultivation and so on, which has significantly improved the quality of mango fruit, increased its market competitiveness，which can not only meet the domestic market, but also export to foreign countries. In the future, China will further improve the quality of fresh mango fruits, increase the proportion of processed products, and increase the income of mango practitioners.

Analysis of Nutritional Components and Flavor Substances of Different Varieties of Mangoes

In this thesis, four varieties of mangoes (Dahuang mango, Daqing mango, eagle-mouth mango, Tai mango), which were all out put in Panzhihua, were investigated as the research objects. The comprehensive evaluation of the four varieties of mangoes was carried out by measuring their various nutritional components combined with their volatile aroma components. In the meantime, the principal component analysis (PCA) was established on the nutritional components. The results showed that there were obvious differences in the quality of the four varieties of mangoes. The highest sugar-acid ratio and β-carotene content belonged to Dahuang mango, which were 16.47 and 4.06 mg/100 g, respectively. The highest water content, content of soluble sugar, titratable acid and total phenols belonged to eagle-mouth mango, which were 82.96%, 21.22%, 2.03% and 0.73 mg/g, respectively. The highest soluble protein content belonged to Tai mango, which was 7.83 mg/g, respectively. Principal component analysis (PCA) results showed that the mango evaluation system can be characterized by two principal components. The highest comprehensive score was eagle-mouth mango, the second was Tai mango, the third was Dahuang mango, and the fourth was Daqing mango. The proportions of terpenoids in the four varieties of mangoes from high to low were Dahuang mango, eagle-mouth mango, Tai mango and Daqing mango. This research provided a theoretical basis for the development of Panzhihua mango industry.

Characterization of five Indonesian mangoes using gas chromatography–mass spectrometry-based metabolic profiling and sensory evaluation

Indonesia is one of the world's leading mango producers and grows many cultivars. However, only a few cultivars have been commercialized, perhaps because of limited information on consumer preferences that meet the market demands. Here, non-targeted gas chromatography-mass spectrometry (GC-MS)-based metabolome analysis was used to characterize five Indonesian mango cultivars considering their taste characteristics. A total of 95 components (47 annotated and 48 unknown metabolites) were identified. Cultivars with a higher general impression score (Arumanis 143 and Gedong) in principal component analysis (PCA) accumulated more sugars and sweetening components, such as glycine and lyxose. Meanwhile, cultivars with a lower general impression score in PCA (Lalijiwo and Cengkir Indramayu) accumulated more aspartic acid, isocitric acid, and citric acid, which increase sourness; methionine, which is a precursor of sulfur-containing volatile aroma components; and phenylalanine, which contributes to bitterness. Furthermore, orthogonal projection to latent structures discriminant analysis revealed that nicotinic acid, glutamic acid, aspartic acid, glycine, and ribose characterized higher or lower general impression cultivars. In addition, metabolic profiling of eight mango cultivars, including five Indonesian and three overseas cultivars, suggested that taste was more influential than differences in cultivars, production areas, and cultivation conditions by its hydrophilic primary metabolomics. These findings will serve as fundamental data for future mango industry development considering the association between the unique taste of each cultivar and its metabolites as well as the consumer preferences for Indonesian mango.