Recent advances in the study of epitopes,allergens and immunologic cross-reactivity of edible mango

Mango(Mangifera indica L.)is a tropical fruit that is widely consumed as both fresh fruits and processed products around the world.The high incidence of mango allergy,on the other hand,has sparked widespread concern.Therefore,a summary and analysis of the current status and issues in mango allergen research can guide in-depth study on the mechanism of mango allergy and reveal effective desensitization methods.We described the incidence of fruit allergy,as well as the mechanism and clinical symptoms of mango allergy,in this review.We also looked into the structural properties of mango allergens,the effect of processing methods on mango allergens,prediction methods for mango allergen epitopes,and the current state of research on mango cross-reactive allergens and preventive measures.Finally,the research directions and ideas for the future are proposed and discussed.

Technical-Economic Performance, Carcass and Meat Quality of COBB500 Broilers Fed Rations Incorporating Mango By-Product Feeds in Ivory Coast (West Africa)

The study evaluated the growth performance and carcass quality of COBB500 broilers fed two experimental rations incorporating feed and mango fine ED10 for a batch of 83 birds, ED20 (batch of 83 birds) in comparison with a commercial control ration CCD (84 birds). For this purpose, 250 day-old chicks of this breed were purchased in Korhogo and transported to Tengréla in Ivory Coast for rearing. The results show that substituting mango provender ans and mango seed flour for maize resulted in rations with costs per kgMS of 215.35FCFA, 2016.93FCFA and 320FCFA for the ED10, ED20 and CCD rations respectively. The production costs per kg of chicken (FCPkgLW) of the CCD ration were significantly higher than those of the ED10 and ED20 (p 0.05). ADGs were significantly different and decreasing from CCD, ED20 to ED10 (p 0.05). Average weights at 42nd day for ED20 and CCD were homogeneous (p > 0.05) and significantly higher than for ED10 (p 0.05). By day 49th the average weight of ED20 had reached and exceeded that of CCD by day 42nd. PSLW, HCW and CCW were significantly different and decreasing from CCW, ED20 to ED10 (p 0.05). Average hot (HCY) and cooled (CCY) carcass yields of ED20 and CCD rations were comparable (p > 0.05) and significantly higher than those of ED10 ration (p = 0.009) and 0.003). Average drumstick and neck weights were significantly higher and lower for CCD, ED20 and ED10 (p 0.05). For all other parts of the cut, the average weights of the CCD ration were significantly higher (p 0.05) than those of the ED20 and ED10 rations, which were homogeneous (p 0.05). The incorporation of mango provender and mango seed flour in broiler rations offers the prospect of reduced production costs, less competition between man and animals over cereals, and lean meat production that is more appreciated than that of chickens fed conventional feed. As it stands, the ED20 ration can be recommended as a growth diet for broilers. It would be necessary to determine the levels of anti-nutritional substances in mango feeds and to assess the in vivo digestibility of mango ingredients and the diets incorporating them.

Study on Compound Stabilizer Formulation for Mango Juice with Skin

[Objectives]The effects of stabilizers such as sodium carboxymethyl cellulose,pectin,sodium alginate and xanthan gum on the stability of mango juice with skin were discussed using mango as the raw material.[Methods]The formula and stability of mango beverage with skin were studied using mango juice with skin as the raw material.Four stabilizers,including pectin,sodium alginate and sodium carboxymethyl cellulose,were added to improve the stability of the juice.Based on single factor experiments and a response surface experiment,the stability model of mango juice was established to determine the best compound stabilizer.[Results]According to an orthogonal experiment on the stability of mango juice with skin,the optimum technical parameters were as follows:sodium carboxymethyl cellulose 0.20%,xanthan gum 0.08%,sodium alginate 0.18%,and pectin 0.14%,with which the optimal suspension stability was 69.12%.The optimum technical parameters from the response surface experiment were as follows:sodium carboxymethyl cellulose 0.199%,pectin 0.1185%,sodium alginate 0.163%,and xanthan gum 0.077%,with which the suspension stability was 70.32%.It was found that the stability of mango juice with skin obtained by the response surface experiment was better than that by the orthogonal experiment,and the order of factors affecting the stability of mango was sodium alginate(C)>sodium carboxymethyl cellulose(A)>pectin(D)>xanthan gum(B).[Conclusions]The formula of compound stabilizer for mango juice was optimized by the orthogonal experiment and the response surface method,providing a theoretical basis for the actual production of mango juice with skin.

An Application of Machine Learning Methods to Detect Mango Varieties

The mango, a fruit of immense economic and dietary significance in numerous tropical and subtropical regions, plays a pivotal role in our agricultural landscape. Accurate identification is not just a necessity, but a crucial step for effective classification, sorting, and marketing. This study delves into the potential of machine learning for this task, comparing the performance of four models: MobileNetV2, Xception, VGG16, and ResNet50V2. These models were trained on a dataset of annotated mango images, and their performance was evaluated using precision, accuracy, F1 score, and recall, which are standard metrics for image classification. The Xception model, with its exceptional performance, outshone the other models on all performance indicators. It achieved a staggering accuracy of 99.47%, an F1 score of 99.43%, and a recall of 99.43%, showcasing its remarkable ability to accurately identify mango varieties. MobileNetV2 followed closely with performances of 98.95% accuracy, 98.85% F1 score, and 98.86% recall. ResNet50V2 also delivered satisfactory results with 97.39% accuracy, 97.08% F1 score, and 97.17% recall. VGG16, however, was the least effective, with a precision rate of 83.25%, an F1 score of 83.25%, and a recall of 85.47%. These results confirm the superiority of the Xception model in detecting mango varieties. Its advanced architecture allows it to capture more distinguishing features of mango images, leading to greater precision and reliability. Xception’s robustness in identifying true positives is another advantage, minimizing false positives and contributing to more accurate classification. This study highlights the promising potential of machine learning, particularly the Xception model, for accurately identifying mango varieties.

Hexavalent Chromium Cr (VI) Removal from Water by Mango Kernel Powder

Metal trace elements (MTE) are among the most harmful micropollutants of natural waters. Eliminating them helps improve the quality and safety of drinking water and protect human health. In this work, we used mango kernel powder (MKP) as bioadsorbent material for removal of Cr (VI) from water. Uv-visible spectroscopy was used to monitor and quantify Cr (VI) during processing using the Beer-Lambert formula. Some parameters such as pH, mango powder, mass and contact time were optimized to determine adsorption capacity and chromium removal rate. Adsorption kinetics, equilibrium, isotherms and thermodynamic parameters such as ΔG˚, ΔH˚, and ΔS˚, as well as FTIR were studied to better understand the Cr (VI) removal process by MKP. The adsorption capacity reached 94.87 mg/g, for an optimal contact time of 30 min at 298 K. The obtained results are in accordance with a pseudo-second order Freundlich adsorption isotherm model. Finally FTIR was used to monitor the evolution of absorption bands, while Scanning Electron Microscopy (SEM) and Energy Dispersive X-ray Spectroscopy (EDS) were used to evaluate surface properties and morphology of the adsorbent.

Integrated Approaches of Mechanical Barrier, Insecticide and Botanicals against Mango Mealybug (Drosicha mangiferae)

An experiment was conducted to test the efficacy of a mechanical barrier around the tree trunk with one spray of Cypermethrin @ 1 ml/l and turmeric powder extract @ 15 g/500ml of water applied in integrated approaches against mango mealybug on mango tree. There were 7 treatments including a control. The treatments were Mechanical barrier, Cypermethrin spray @ 1 ml/l, Turmeric powder spray @ 15 g/500ml of water, Cypermethrin spray + Turmeric spray, Cypermethrin spray + Mechanical barrier, Turmeric + Mechanical barrier and untreated control. Three-year-old mango plants grafted from a 5-year-old mango tree (Variety Amropali) and planted in pots were used in the experiment. The treatment, Cypermethrin spray + Mechanical barrier gave the highest reduction of mango mealybug population 87.06% to 93.90% followed by Turmeric spray + Mechanical barrier and showed 81.13% to 86.04% and Mechanical barrier alone showed 81.13% to 84.59% population reduction. Turmeric powder extract showed only (8.42% to 23.77%) population reduction of mango mealybug which was lowest compared to other treatments.

Deep Convolutional Neural Networks for South Indian Mango Leaf Disease Detection and Classification

The South Indian mango industry is confronting severe threats due to various leaf diseases,which significantly impact the yield and quality of the crop.The management and prevention of these diseases depend mainly on their early identification and accurate classification.The central objective of this research is to propose and examine the application of Deep Convolutional Neural Networks(CNNs)as a potential solution for the precise detection and categorization of diseases impacting the leaves of South Indian mango trees.Our study collected a rich dataset of leaf images representing different disease classes,including Anthracnose,Powdery Mildew,and Leaf Blight.To maintain image quality and consistency,pre-processing techniques were employed.We then used a customized deep CNN architecture to analyze the accuracy of South Indian mango leaf disease detection and classification.This proposed CNN model was trained and evaluated using our collected dataset.The customized deep CNN model demonstrated high performance in experiments,achieving an impressive 93.34%classification accuracy.This result outperformed traditional CNN algorithms,indicating the potential of customized deep CNN as a dependable tool for disease diagnosis.Our proposed model showed superior accuracy and computational efficiency performance compared to other basic CNN models.Our research underscores the practical benefits of customized deep CNNs for automated leaf disease detection and classification in South Indian mango trees.These findings support deep CNN as a valuable tool for real-time interventions and improving crop management practices,thereby mitigating the issues currently facing the South Indian mango industry.

Influence of Various Hydrocolloids on Suspension Stability of Chia Seeds (Salvia hispanica L.) in Mango Beverage and Mango Flavored Beverage

With the developing of juices and beverages industry, the processors need to bring new nutritional fortified products to capture the market as per the demand of the consumer who needs healthier product. Thus, this study aimed to the production of mango beverage and mango flavored beverage fortified with chia seeds;evaluate the chemical properties of chia seeds and study the effect of adding carboxymethyl cellulose, xanthan gum and low acyl gellan gum at the concentrations of 0.05% and 0.1% on the stability of suspension chia seeds in beverage during storage at ambient temperature for six months. Viscosity, color, zeta potential, suspension of seeds and organoleptic properties were evaluated. Results showed that chia seeds were rich in protein, omega-3 fatty acids and dietary fiber. The addition of 0.05% gellan gum led to improved appearance attributes and the highest stability of suspension of chia seeds for six months, and was the sample which scored highest for overall acceptability compared to the other samples of beverages. Results indicated that using chia seeds with the addition of 0.05% low acyl gellan gum led to the production of fortified mango beverage and mango flavored beverage with high stability for six months.

Mango Pest Detection Using Entropy-ELM with Whale Optimization Algorithm

Image processing,agricultural production,andfield monitoring are essential studies in the researchfield.Plant diseases have an impact on agricultural production and quality.Agricultural disease detection at a preliminary phase reduces economic losses and improves the quality of crops.Manually identifying the agricultural pests is usually evident in plants;also,it takes more time and is an expensive technique.A drone system has been developed to gather photographs over enormous regions such as farm areas and plantations.An atmosphere generates vast amounts of data as it is monitored closely;the evaluation of this big data would increase the production of agricultural production.This paper aims to identify pests in mango trees such as hoppers,mealybugs,inflorescence midges,fruitflies,and stem borers.Because of the massive volumes of large-scale high-dimensional big data collected,it is necessary to reduce the dimensionality of the input for classify-ing images.The community-based cumulative algorithm was used to classify the pests in the existing system.The proposed method uses the Entropy-ELM method with Whale Optimization to improve the classification in detecting pests in agricul-ture.The Entropy-ELM method with the Whale Optimization Algorithm(WOA)is used for feature selection,enhancing mango pests’classification accuracy.Support Vector Machines(SVMs)are especially effective for classifying while users get var-ious classes in which they are interested.They are created as suitable classifiers to categorize any dataset in Big Data effectively.The proposed Entropy-ELM-WOA is more capable compared to the existing systems.

Melatonin treatment alleviates chilling injury in mango fruit 'Keitt' by modulating proline metabolism under chilling stress

Mangoes often suffer from low temperature-induced chilling injury (CI) during postharvest cold storage.Therefore,advanced techniques are crucial and in high demand to solve the chilling stress of mango fruit for a higher value.This study addresses chilling stress modulation by investigating the effects of melatonin treatment on CI,proline metabolism,and related gene expressions of ‘Keitt’ mango during cold storage after dipped in 0 (control),0.1 (MT1),and 0.2 mmol L^(-1)(MT2) melatonin solution for 30 min.The results revealed that melatonin treatment in MT1 significantly reduced CI development and increased proline content in mango fruit during cold storage compared to the control.These changes were along with increases in the activity of critical enzymes as well as the expression of encoding genes involved in proline biosynthesis,such as pyrroline-5-carboxylate synthetase (P5CS),pyrroline-5-carboxylate reductase (P5CR),ornithine D-aminotransferase (OAT),P5CS2,P5CR2,and OAT3.Additionally,proline dehydrogenase (PDH) activity and the expression of the PDH3 gene associated with proline dehydrogenation were lower in MT1-treated mangoes than the controlled group.Thus,melatonin treatment has regulated proline metabolism resulting in the accumulation of proline,subsequently contributing to enhancing the chilling tolerance of‘Keitt’mango fruit.

Production of Vinegar Mango Using Acetobacter tropicalis CRSBAN-BVA1 and CRSBAN-BVK2 Isolated from Burkina Faso

Production and quality of vinegar from mango juice was evaluated using a two steps production procedure. The first step of fermentation was done using Saccharomyces cerevisae KVL013 for 7 days. The second step, an acetic fermentation was realized using two acetic acid bacteria: A. tropicalis CRSBAN-BVA1 and A. tropicalis CRSBAN-BVK2 for 21 days. Several parameters of the vinegar produced such as physico-chemical and sensory properties were determined. Microbial density during each step was monitored. Results showed that pH, alcoholic and acetic acid contents of vinegar were respectively 2.97%, 7% and 4.54% g/ml respectively by using A. tropicalis CRSBAN-BVA1 and 3.02%, 7% and 4.32% g/ml with A. tropicalis CRSBAN-BVK2. Sensory evaluation revealed that the vinegar was acceptable to the panellists. Results of microbial density showed that the maximum concentration of cell biomass produced was 4.32 × 108 and 4.25 × 108 CFU/ml respectively for CRSBAN-BVA1 and CRSBAN-BVK2.

Phytosanitary Practices and Pesticide Levels in Fresh and Dried Mangoes Produced in Burkina Faso

Pesticides are used to control fruit flies and other potential crop pests, particularly mango in Burkina Faso. Pesticides are a potential health hazard for users and consumers and are a major constraint to the export and commercialization of mangoes. The objective of this study was to evaluate phytosanitary practices in orchards and pesticide residue levels in four varieties of fresh and dried mangoes (Amelie, Brooks, Kents and Lippens) produced in four localities in Burkina Faso in order to determine their health impact on consumers. Surveys on pesticide use and monitoring of phytosanitary practices were carried out among 16 orchard owners in the localities of Bobo-Dioulasso, Orodara, Toussiana and Banfora, a high mango production area. Also, a total of 120 samples, including 60 samples of fresh mangoes and dried 60 samples of dried mango were collected. A multi-residue method was developed to detect pesticide levels in the collected samples by gas chromatography with a micro-electron capture detector. The study revealed the use of unauthorized pesticides, often specifically for other crops, and a monitoring trapping network in the orchards against insects. 34 chemical pesticides were detected in 120 samples of all mango varieties collected. Pesticide residues were detected in 72% of the samples, and of the positive samples, 48.52% contained concentrations above the maximum residue limit permissibility. Organochlorine pesticide residues were present in fresh mangoes (60.5%) and a total of fifteen active compounds were detected in dried mangoes. The very poor management and use of pesticides found in these orchards could pose a threat to the productivity of natural ecosystems and the health of producers, processors and consumers. Awareness raising and training of producers on the knowledge of the risks linked to the use of pesticides and good practices are necessary to preserve the health of all.

Influence of Sorbent Type on Drying Efficiency, Production Costs and Nutritional Values of Mango By-Products Feeds for Livestock

The aim of the study was to determine the best food absorbents between wheat, rice and maize bran and palm kernel cake, from a technical and economic point of view, in order to make a better recommandation for their use in the production process of food based on mango by-products (peels, peels + pulp). To this end, series of 18 kg of fresh feed were prepared and spread out in a stall for sun-drying using a randomized Fisher system. Preparations were made using either mango peels (75%) + absorbent (25%) or pulp + mango peels (67%) + sorbent (33%). The results show that mango Peel feed loses more water (WL) with lover production yields (PY), higher mango incorporation rates into dry feed (MRI), longer drying times (UDT) and lower production costs (CPkgPD) than mango peel + pulp. The average DM, MAT, ADF and NDF fiber contents were almost equal to those of mango peels + pulp feed. The average Crude Fiber (CF) (25.13%) and DEp (2839 kcal/kgDM) contents were higher for mango skin feed than for mango skin + pulp feed, at 8.59% and 2536 for MAT and DEp respectively. Mango peels + wheat bran (PSB25) and whole mango (MESB33) feeds recorded the highest and almost equal levels of TCP, NDF and MM. Production costs per kg of feed dry mater (CPkgDM) for feed produced at 25% were on average 33% higher than for whole mango (WM) feed. Excluding mango raw material, palm kernel meal (PK), rice bran (RB), maize bran (MB) and wheat bran (WB) can be ranked 1st, 2nd, 3rd and 4th in terms of cumulative performance of production parameters. Producers can then choose the type of sorbent they wish to use according to this ranking and the local availability of the sorbent. These feeds can be used for both ruminants and monogastrics, but are better suited to ruminant feeding due to their high fiber content.

Effectiveness of Four Integrated Pest Management Approaches in the Control of Fruit Flies (Diptera: Tephritidae) in Mango Agro-Ecosystems in the South-Sudanian Zone of Burkina Faso

This study evaluated the effectiveness of four Integrated Pest Management (IPM) approaches in the control of Bactrocera dorsalis (Hendel) [Diptera: Tephritidae] and Ceratitis cosyra (Walker) [Diptera: Tephritidae] during two consecutive mango fruiting seasons (2018 and 2019) in the south-Sudanian zone of Burkina Faso. These approaches, including sanitation + M3 bait station (SM), sanitation + protein GF-120 bait (SG), sanitation + Timaye + M3 bait station (STM) and sanitation + Timaye + GF-120 bait (STG), were implemented in 12 mango orchards in three provinces of the country. In each province, one mango orchard was used as control. Flies per trap per week (FTW) and damage indices were assessed in treated orchards compared to the control orchards. The efficacy rate of each IPM approach in protecting mango against fruit fly attacks was also determined. The STG approach was the most effective in reducing both B. dorsalis and C. cosyra FTW with the best efficacy rate. Further research should emphasize indigenous and affordable attract-and-kill tools for resource poor farmers.

Effect of Alternate Bearing Phenomenon and Boron Foliar Application on Nitrogen-15 Uptake,Translocation and Distribution in Mango Tree(cv.Zebda)

The objectives of this investigation are to study nitrogen uptake,translocation,accumulation and distribution in mango tree organs using labeled nitrogen(^(15)N)and to understand the mechanism of boron action in increasing fruit yield in the off-year.A field experiment was conducted using fifteen-year-old mango trees(cv.Zebda)grown at Al Malak Valley Farm,El-Sharkeya Governorate-Egypt.Treatments included the application of(^(15)NH4)2SO4,“in the on-year”,at a rate of 50 g nitrogen/tree through the stem injection technique.While boron was sprayed on the same trees“in the off-year”at the following rates:0.0(control),250 and 500 mg·L^(-1).The authors hypothesize that boron and nitrogen act synergistically to increase mango fruit yield in the off-year.Results indicated that the highest ^(15)N uptake and accumulation in the on and off-years was observed in the upper(young leaves).When boron was applied at 250 mg·L^(-1),in the off-year,the upper(young leaves)recorded the highest ^(15)N uptake and accumulation(%^(15)Ndff=13.93)relative to the other two leaf categories and those of the on-year.In the on-year fruit accumulated higher ^(15)N than leaf or bud.In the off-year,bud exhibited the highest ^(15)N accumulation without boron application,while leaves exhibited the highest ^(15)N with boron application.The highest%^(15)Ndff in all tree organs was observed at 250 mg·L^(-1) boron rate.Boron increased nitrogen uptake,translocation and accumulation in mango tree organs.A synergistic relationship was observed between boron and nitrogen which led to an increase in fruit yield in the off-year.

Mango轻烃参数在塔里木原油分类中的应用

根据Ｍａｎｇｏ稳态催化动力学轻烃成因模式所得到的参数可作为塔里木盆地原油分类的有效指标。不同成因原油之间Ｋ２［Ｐ３／（Ｐ２＋Ｎ２）］值有明显的变化，在海相油中其平均值（０．２０～０．２３）较低，陆相油中（０．２９～０．３６）较高，表明该参数与源岩的有机质类型及沉积环境性质有关。Ｎ１６／Ｎ１５和（Ｎ１６＋Ｎ１５）／（Ｐ２＋Ｐ３＋Ｎ２）等不同结构类型轻烃化合物的比值能区分海、陆原油。不同成因原油的Ｃ７轻烃组成反映出不同的碳环优势（ＲＰ），海相原油轻烃富含二甲基环戊烷（５ＲＰ），而陆相原油以甲基环已烷占优势（６ＲＰ）。

天然气伴生凝析油Mango参数的成因内涵——以渤海湾盆地上古生界为例

研究表明,渤海湾盆地石炭—二叠系煤成天然气伴生凝析油和第三系天然气伴生凝析油之间,K1、K2、P2与N2/P3等轻烃Mango参数存在较明显不同的变化规律,这表明Mango参数与源岩有机质类型密切相关,可用于不同成因类型天然气的判识。

The chemical treatments combined with antagonistic yeast control anthracnose and maintain the quality of postharvest mango fruit

During the storage and transportation of the mango fruit, the major source of disease is anthracnose, caused by the fungus Colletotrichum gloeosporioides. The objective of this study is to find an appropriate method that not only reduces mango decay but also maintains its postharvest quality. The effects of chemicals, the use of the yeast species Metschnikowia pulcherrima and their combination on storage quality, focusing on the enzyme activity related to disease of Tainong mangos was studied. By immersing the mangoes in M. pulcherrima suspension(1.0×10~8 cfu mL^(–1)), salicylic acid(SA) solution(50 mg L^(–1)) or calcium chloride(CaCl_2) solution(1.0 g L^(–1)), the lesion expansion and decay of the mango fruit caused by C. gloeosporioides could be significantly delayed. These treatments also delayed the changes in quality traits(a~* value, firmness, contents of total soluble solids(TSS) and vitamin C(Vc), while the activities of anti-disease enzymes such as polyphenol oxidase(PPO), phenylalanine ammonia lyase(PAL), chitinase(CHT) and β-1,3-glucanase(GUN) were enhanced as compared to the control treatment. Furthermore, the combination of SA solution, CaCl_2 solution and M. pulcherrima suspension presented an additive effect, increasing the efficacy in controlling the disease and maintaining the storage quality of mango fruits. Taken together, our data suggest that the integration of chemical treatments combined with M. pulcherrima could be an alternative to the use of fungicides in postharvest treatment of the mango fruit, specifically for improving storage quality as well as the control of the anthracnose.

Protective effects of lupeol and mango extract against androgen induced oxidative stress in Swiss albino mice

Aim： To investigate antioxidant potential of lupeol/mango pulp extract （MPE） in testosterone induced oxidative stress in prostate of male Swiss albino mice. Methods： Oral treatment of lupeol （1 mg/animal） and MPE （1 mL [20% w/v]/ animal） was given separately to animals along with subcutaneous injection of testosterone （5 mg/kg body weight） consecutively for 15 days. At the end of the study period, the prostate was dissected out for the determination of reactive oxygen species （ROS） levels, lipid peroxidation and antioxidant enzymes status （catalase, superoxide dismutase, glutathione reductase, glutathione-S-transferase）. Results： In testosterone treated animals, increased ROS resulted in depletion of antioxidant enzymes and increase in lipid peroxidation in mouse prostate. However, lupeol/MPE treatment resulted in a decrease in ROS levels with restoration in the levels of lipid peroxidation and antioxidant enzymes. Conclusion： The results of the present study demonstrate that lupeol/MPE are effective in combating oxidative stress-induced cellular injury of mouse prostate. Mango and its constituents, therefore, deserve study as a potential chemopreventive agent against prostate cancer. （Asian J Androl 2008 Mar; 10： 313-318）

Comparison of machine learning algorithms for mapping mango plantations based on Gaofen-1 imagery

Mango is a commercial crop on Hainan Island,China,that is cultivated to develop the tropical rural economy.The development of accurate and up-to-date maps of the spatial distribution of mango plantations is necessary for agricultural monitoring and decision management by the local government.Pixel-based and object-oriented image analysis methods for mapping mango plantations were compared using two machine learning algorithms(support vector machine(SVM)and Random Forest(RF))based on Chinese high-resolution Gaofen-1(GF-1)imagery in parts of Hainan Island.To assess the importance of different features on classification accuracy,a combined layer of four original bands,32 gray-level co-occurrence(GLCM)texture indices,and 10 vegetation indices were used as input features.Then five different sets of variables(5,10,20,and 30 input variables and all 46 variables)were classified with the two machine learning algorithms at object-based level.Results of the feature optimization suggested that homogeneity and variance were very important variables for distinguishing mango plantations patches.The object-based classifiers could significantly improve overall accuracy between 2–7%when compared to pixel-based classifiers.When there were 5 and 10 input variables,SVM showed higher classification accuracy than RF,and when the input variables exceeded 20,RF showed better performances.After the accuracy achieved saturation points,there were only slightly classification accuracy improvements along with the numbers of feature increases for both of SVM and RF classifiers.The results indicated that GF-1 imagery can be successfully applied to mango plantation mapping in tropical regions,which would provide a useful framework for accurate tropical agriculture land management.