Mango Leaf Research Articles

Sistem Filtering Berbahan Daun Mangga Untuk Emisi Partikulat Matter2,5

Abstract
 The annual growth of the vehicle industry sector has the potential to spur economic growth, but it can also harm the environment. The negative impact that can endanger human health is air pollution. Particulate Matter 2.5μm (PM2.5) is a very small air pollutant in size that can cause various diseases such as disorders of the respiratory tract if exposed to PM2.5 while exceeding the quality standard and continuously (55μg/m3 for daily quality standard and 15μg/m3 annual quality standard). This study aimed to see the effectiveness of the filtering system tool made from mango leaves and activated carbon to reduce PM2.5 emissions. This study was an pra-experimental research design with the one-group pre-post test design method. The population in this study is PM2.5 particulate emissions deriving from two motor vehicle emissions, emission source 1 (old two-wheeled motor vehicles) and emission source 2 (new two-wheeled motor vehicles). PM2.5 data were collected using the EVM-7 tool. The results showed a decrease in the concentration of PM2.5 before and after the mango leaf filter was installed on both emission sources. The average concentration of particulate matter decreases with the influence of different temperatures and humidity. It is recommended to continue this research to develop a filtering tool that can be used by the wider community to reduce air pollution, especially PM2.5.
 Keywords: PM2.5, Mango Leaf Filtering, Activated Carbon

Inhibitive effect of Irvingia Gabonensis leaf extract on the corrosion of mild steel in 1.0m hydrochloric acid

This investigation utilizes leaf extracts as corrosion inhibitors and studies the inhibitive effect of Irvingia gabonensis leafextracton mild steel immersed in 1.0M HCl acid at ambient conditions. The phytochemical constituents responsible for the corrosion inhibition were determined by standard phytochemical methods. The chemicals detected were alkaloids, flavonoids, saponins, and tanins. The study was carried out using eleven (11) experimental setups, which consisted of: 1.0M HCl (control 1), 10ml, 15ml, 20ml, and 25ml extracts in 1.0M HCl and distilled water (control 2). The experiment was conducted using the weight loss/corrosion rate measurement technique and the results showed that the extract concentration and exposure time had effects on the corrosion rate, whilst the 25ml extract inhibited the most in the acidic medium.The results of the experiment with the two-factor ANOVA without replication indicated that the extract concentration had a more significant effect on corrosion rate than the exposure time. Having this in mind, the inhibitive effect of Irvingnia gabonensis (Africa mango or ogbono) leaf extract as an organic "green" inhibitor on mild steel corrosion in an acidic medium can be said to depend on the concentration of the extract for better effectiveness and inhibition efficiency. Therefore, Irvingia gabonensis leaf extract, with an inhibition efficiency of 67.14% on mild steel in a moderate acidic environment, can be recommended for use in commercial and industrial environments where mild steel material is required in service.

Preparation of Low-cost Adsorbent Based on Mango Leaf (Mangefira Indica L) Biomass for Methylene Blue (MB) Adsorption

Preparation of leaf mango (Mangefira Indica L)-based adsorbent and its evaluation to reduce methylene blue (MB) concentration have been conducted. Two materials: ads-pristine and ads-CTAB which are referred as native leaf mango adsorbent and CTAB modified leaf mango have been prepared in this study. Cetyltrimethylammonium bromide (CTAB) is cationic surfactant usually used to modify and increase the surface area of the adsorbent for a specific purpose. The materials obtained were characterized by the Fourier Transform Infra-Red (FTIR) and the Scanning Electron Microscope (SEM) with general result, there were detected functional groups indicated the active sites on the adsorbent such as -OH, C-O, C=C. Ads-CTAB was specifically characterized with appearing of C-H aliphatic as the tail of CTAB molecule. SEM images show that both materials have roughness surface and irregular cavities. Additional of CTAB on the surface led the more regularly surface. The optimum pH was in basic region (8), while the optimum adsorbent mass and MB concentration are not clearly found due to the chart still increasing. However, the highest qe was found by 0.01 g of ads-pristine and ads-CTAB with the value 967.25 and 950.75 mg g-1 respectively. As the further evaluation, with the 0.5 adsorbent mass it may be applicated on the MB concentration at around 4000 mg L-1. Kinetics model of this adsorption was followed pseudo second order reactions.

Modeling the Dynamics of Soil Organic Matter Accumulation from Leaf Litterfall as Affected by Tillage Practices in Mango Orchard

This study was undertaken to determine long-term soil organic matter (SOM) accumulation dynamics from added mango leaf litter (MLL) into tilled (MT) and non-tilled soil (MnT) through integrated field experiment (bio-physico-chemical edaphic properties) and system dynamics modeling. Field data shows that the coarse (Lf) and fine (Fn) fractions of SOM have no significant difference (p > 0.05) between MT and MnT during the dry season. In contrast, there is a significant difference (p < 0.01) in the Fn fraction between MT and MnT during the wet season. The total N, available P, exchangeable K, as well as the collembola, bacteria, and fungi in the soil were also assessed. Of these parameters, the available P and exchangeable K have a significant difference between the MnT and MT during the dry season. In comparison, the total N and collembola significantly differed during the wet season. The results of the field experiment were used in the parametrization to build the SOM accumulation model. The 20-year simulation showed that the incorporation of MLL into the soil through tillage increased SOM from 3.09% to 3.13%, with an average of 2.78 ± 0.018%. In the non-tilled orchard, SOM also increased from 3.09% to 4.23%, with an average of 3.59 ± 0.035%. This SOM level can sustain the fertility and productivity of the mango agroecosystem. The increase in SOM is accounted for by the coarse fraction both in tilled and non-tilled plots. Given the foregoing, with minimum tillage, mango orchards can be developed into crop-based systems.

Determining the Glycemic Index of Mango Leaf Powder Incorporated Health Mix

Medicinal plants serve as an alternative medicine to allopathy as they are cheaper and have no side effects. In Ayurveda research, mango tree and its parts have many medicinal properties. Mango tree and its leaves and fruits has properties like anti-diabetic, anti-oxidant, anti-viral and anti-inflammatory. Phenolic constituents like caffeic acid, polyphenols like mangiferr in and gallic acid, flavonoids and volatile compounds are present in mango leaves. The objectives of the study are to develop and standardize mango leaves incorporated health mix, analyze the nutrient content and determine the glycemic index. The ingredients selected for health mix were wheat, barley, foxtail millet, green gram dhal, roasted Bengal gram dhal, groundnut and almonds. Five variations of health mix were prepared and it was made as porridge and evaluated. Fresh mango leaves was washed, dried and powdered. The powder was incorporated into the health mix at 10, 20 and 30 per cent level. Porridge was prepared with three variations and it was evaluated for its acceptability. Health mix incorporated with mango leaves powder at 10 and 20 per cent was highly acceptable while 30 per cent incorporation had a bitter taste and not acceptable. Nutrient analysis was carried out for the standard and the acceptable health mix. Glycemic index of the health mix and mango leaf powder incorporated health mix was determined. Due to the presence of fibre in mango leaf incorporated health mix, glycemic index was low when compared to standard health mix.

Mango leaf disease identification and classification using a CNN architecture optimized by crossover-based levy flight distribution algorithm

Mango leaf disease identification and classification using a CNN architecture optimized by crossover-based levy flight distribution algorithm

MANGO STEM BORER: A SERIOUS PEST AND MANAGEMENT STRATEGIES

Different insect infect mango like mango hopper, mango mealy bug, mango shoot gall maker, mango fruit fly, mango stone weevil etc. and minor insect like mango leaf webber, mango leaf-gall maker, red ant etc. Among the different pests in the mango, Mango Stem Borer(Batocera rufomaculata) is also one of the chief pest attacking mango in Terai region of Nepal. B. rufomacacuata, for example, has been causing concern in mango orchards. This paper delves into the detail review of information about the mango stem borer, it’s nature of damage, biological cycle and management strategies.

Comparison of convolutional neural networks architectures for mango leaf classification

Comparison of convolutional neural networks architectures for mango leaf classification

Potential Therapeutic Activity of Mango (Mangifera indica L.) Leaves on Excess Consumption of Fructose in Rats

Background and Objective: High fructose consumption has increased worldwide. It causes various metabolic, genetic and histologic alterations. Alternative medicine, primarily herbal plants, has been proposed to alleviate the negative effects of high fructose consumption. The main objective of this study was to explore the efficacy of supplementation or treatment with mango leaves against high fructose induced alterations in male rats.
 Methodology: Mango leaves nutritional and active components were determined. A total of sixty male adult rats were used in this study. Fifteen rats were kept as healthy (negative control group; rats fed on balanced diet) while in others metabolic alterations were induced by consumption of high fructose diet ad libitum. Rats fed on high fructose diet were splited into 3 groups (15 rats in each), one group set as positive control group; rats fed on high fructose diet only and the other 2 groups; mango treated group; rats fed on high fructose diet until induction of hyperglycemia (one month and half) then fed on high fructose diet with replacement of fiber with 5% mango leaves and mango supplemented group; rats fed on high fructose diet with 5% mango leaves replacing fiber.
 Results: Mango leaves contain significant amounts of crude protein, crude fat, carbohydrates, crude fiber, ash, total flavonoids and polyphenols that controlled and corrected the following high fructose consumption results. Consumption of high fructose diet significantly (p≤0.05) increased final body weight (FBW), body weight gain (BWG), abdominal circumference (AC), Lee index and body mass index (BMI). High fructose also significantly (p≤0.05) increased levels of systolic blood pressure (SBP), serum triacylglycerol (TAG), total cholesterol (TC), fasting blood glucose, insulin, homeostasis model assessment-insulin resistance (HOMA-IR), serum tumor necrosis factor-α (TNF-α), leptin, malondialdehyde (MDA), advanced glycation end products (AGEs) and adipocyte size as well as blood histone deacetylase (HDAC) enzyme activity. High fructose consumption contrarily caused significant decrease (p≤0.05) in levels of quantitative insulin check index of insulin sensitivity (QUICKI), adiponectin, muscular insulin receptor substrate-1 (IRS-1) and glucose transporter-4 (GLUT-4) gene expression as well as blood reduced glutathione (GSH). Furthermore, microscopic examinations of the pancreatic and adipose tissues corroborated the biochemical findings.
 Conclusion: Mango leaves are a cheap source of macro and micronutrients as well as active constituents. By limiting metabolic and genetic abnormalities caused by high fructose consumption, either mango leaf supplementation or therapy improved and ameliorated all biochemical and microscopic data. The mango leaves supplemented group showed the most improvement.

Evaluation of the Bioactivities of Natural Phenolics from Mango (Mangifera indica Linn) Leaves for Cosmetic Industry Applications

Mango is one of the most important crops in the Philippines but there had been no local study on the possible utilization of its non-food parts such as the barks and leaves, which were reported to be rich in compounds with biological activities that are of significance in the development of cosmetic products (Masibo and He 2008; DA 2018). In this study, aqueous acetone extracts from leaves of the Philippine mango cultivars (“carabao,” “pico,” “apple mango, “sinaging,” and “sipsipin”) were investigated for their total phenolics content (TPC), phenolics composition, and biological activities – specifically, antioxidant as well as tyrosinase and elastase inhibitory properties. Results show that all mango leaf extracts had significant levels of TPC. Phenolic compounds such as mangiferin, gallic acid, quercetin 3-β-D-glucopyranoside, and kaempferol were all found to be present in the extracts with mangiferin as the predominant compound. All the extracts exhibited greater antioxidant capacity than the standard ascorbic acid, implying greater protection against skin damages due to free radicals. Also, all extracts exhibited greater inhibition on elastase than tocopherol, suggesting a greater anti-aging property. While only some extracts showed greater inhibition on tyrosinase than ascorbic acid, it did not surpass but gave comparable inhibitory activity with that of kojic acid. This implies that the extracts and kojic acid have comparable whitening capacities. Overall, the results affirm the great potential of the extracts of the local mango leaves as a cosmetic active ingredient

Intelligent system for leaf disease detection using capsule networks for horticulture

Horticulture crops take a crucial part of the Indian economy by creating employment, supplying raw materials to different food processing industries. Mangoes are one of the major crops in horticulture. General Infections in Mango trees are common by various climatic and fungal infections, which became a cause for reducing the quality and quantity of the mangos. The most common diseases with bacterial infection are anthracnose and Powdery Mildew. In recent years, it has been perceived that different variants of deep learning architectures are proposed for detecting and classifying the problems in the agricultural domain. The Convolutional Neural Network (CNN) based architectures have performed amazingly well for disease detection in plants but at the same time lacks rotational or spatial invariance. A relatively new neural organization called Capsule Network (CapsNet) addresses these limitations of CNN architectures. Hence, in this work, a variant of CapsNet called Multilevel CapsNet is introduced to characterize the mango leaves tainted by the anthracnose and powdery mildew diseases. The proposed architecture of this work is validated on a dataset of mango leaves collected in the natural environment. The dataset comprises both healthy and contaminated leaf pictures. The test results approved the undeniable level of exactness of the proposed framework for the characterization of mango leaf diseases with an accuracy of 98.5%. The outcomes conceive the higher-order precision of the proposed Multi-level CapsNet model when contrasted with the other classification algorithms such as Support Vector Machine (SVM) and CNNs.

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.

Characteristics of Mango Leaf Photosynthetic Inhibition by Enhanced UV-B Radiation

To investigate the photosynthetic change characteristics of mango leaves under enhanced UV-B radiation, adult ‘Tainong No. 1′ mango (Mangifera indica) trees were treated (N = nine individuals) with simulated enhanced UV-B radiation [24 and 96 kJ/(m2·d)] in the field, and the photochemical reactions, activities of key enzymes in carbon assimilation, and the expression of genes were observed. The results showed that compared with the control, there was a decrease in tree yield, soluble sugar, sugar–acid ratio, and vitamin C of the fruits under the 96 kJ/(m2·d) treatment, while no significant changes were observed under 24 kJ/(m2·d). After 20 or 40 days, the leaves’ net photosynthetic rate (Pn), stomatal conductance (Sc), transpiration rate (Tr), intercellular CO2 concentration (Ci), and chlorophyll a/b under exposure to 96 kJ/(m2·d) of UV-B were significantly lower than in the control, whereas chlorophyll a, chlorophyll b, carotenoids, Hill reaction activity, photochemical quenching coefficient (qP), and Rubisco activities were significantly higher. In contrast, the Hill activity and Rubisco activity under 24 kJ/(m2·d) were significantly higher than the control, and increased by 350% and 30.8%, respectively, while Pn, Sc, Tr, Ci, and the content of photosynthetic pigments were similar to the control. The expression of gene coding the Rubisco big subunit (rbcL) was inhibited by the 96 kJ/(m2·d) treatment. We conclude that stomatal limitation was directly induced by 96 kJ/(m2·d), resulting in the inhibition of photosynthesis and the reduction in yield and deterioration of the quality of mango.

Bioactive exopolysaccharide from endophytic Bacillus thuringiensis SMJR inhibits food borne pathogens and enhances the shelf life of foods

In recent times, the use of microbial exopolysaccharides as food preservative has gained significant industrial applications. Accordingly, in this study, EPS producing bacteria was isolated from mango leaf. The isolated bacteria were identified as B. thuringiensis strain SMJR by morphological characteristics and 16s rDNA sequencing. The 16s rDNA gene sequences were submitted to GenBank database under accession number MZ049561. The isolated B. thuringiensis strain SMJR strain was subjected to EPS production using basal salt medium. EPS was recovered and purified by ethanol precipitation. The anthrone test showed that EPS is a polysaccharide composed mainly of glucose. EPS was characterized by UV–Vis spectra and FTIR. UV–Vis spectra showed an absorbance peak at 230 nm indicating the presence of polysaccharides. FTIR revealed the presence of various functional groups stretching between 4000 and 200 cm-1. The antibacterial activity demonstrates that both the crude EPS and pellet possessed inhibitory activities against the tested food borne pathogens (E. coli and K. pneumoniae). The crude EPS showed greater antibacterial effects against the tested food borne bacteria when compared to the pellet. Furthermore, EPS has enhanced the shelf life of grape juice by preventing the growth of pathogenic bacteria. This study concludes that the EPS from B. thuringiensis strain SMJR could be used as a potential preservative to prevent the spoilage of food and emergence of food borne diseases.

Classification of mango plants based on leaf shape using GLCM and K-nearest neighbor methods

Objective: Apply the GLCM method to select mango leaf feature extraction and determine the accuracy level obtained from the K-Nearest Neighbor classification results.Design/method/approach: Using GLCM and K-Nearest Neighbor(KNN) methods. System development using the Prototype method.Results: The test results have been carried out using as many as 60 mango leaves compared to training data and 80:20 test data, with different accuracy. The highest accuracy is at K = 3 by 81% using 6 features, K = 6 by 78% using 5 features, and K = 7 by 74% using 4 features.Authenticity/state of the art: The difference between this research and previous research is the pre-processing method, the type of features used, and the classification method. In this method, the mango leaf image is converted to grayscale, and a feature extraction process is carried out. Then the results of feature extraction will be classified using the K-Nearest Neighbor method. The output of this system is the result of the image classification of mango leaves, such as Kweni, Lalijowo, and Madu.

Removal of chromium(VI) from aqueous solutions using mango leaf powder : Process optimization with Response Surface Methodology

Removal of chromium(VI) from aqueous solutions using mango leaf powder : Process optimization with Response Surface Methodology

Harumanis Mango Leaves Image Segmentation based on Wavelet Transformation with Phansalkar and Sauvola Thresholding

Harumanis mango is one of the economic sources of the Perlis state. It has a sweeter taste compared to other mangoes. However, the Harumanis mango tree required specific weather, soil nutrient contents and pH level. This makes the farmer does not know the health condition of their Harumanis mango tree. Therefore, this project aims to provide the best method of leaves detection to the farmer. The leaves image samples are collecting from the orchard and undergo pre-processing. Then the input image was converted into grayscale with principal component analysis (PCA). Wavelet transformation was implemented to increase the discriminability of the segmentation technique for separating the leaf and background. The leaf segmentation is done by using Phansalkar and Sauvola thresholding techniques. After that, fill hole and area opening techniques are implementing to reduce noise in the image. These two thresholding techniques are comparing and discuss with their segmentation performance. Overall, Phansalkar thresholding has produced better performance in segmenting healthy and unhealthy Harumanis mango leaves with sensitivity, specificity and accuracy of 92.05%, 81.37% and 83.51%, respectively.

Development of Aqueous Formulation Containing the Extracted Mangiferin

Mangiferin, a polyphenol of C-glycosylxanthone, exhibits various bioactivities with poor aqueous solubility. It is known as a potent antioxidant, which leads to remarkable UV protection and anti-aging properties. Mangiferin can be found in many plant species, among which the mango leaf is one of the primary sources. From our study, the extraction yield of mangifein obtained from the leaves of Mangifera indica L. variety Nam Doc Mai was 3.17% with 95.02% ± 0.064 purity (HPTLC analysis). The solubility of mangiferin in the studied pure solvents arranging in descending order were ethoxydiglycol, dimethyl isosorbide, polyethylene glycol 400, polyethylene glycol 600, propylene glycol, dipropylene glycol, glycerin, isopentyldiol, methanol, ethanol and water, whereas the addition of the solvent in water could increase the aqueous solubility of mangiferin. In several cases, the solubility was apparently higher than that dissolved in its pure solvent state. The log-linear solubility model for the cosolvent system was used to calculate the volume fractions of the selected solvents needed to solubilize mangiferin content at the twenty times of the IC50 against DPPH radicals. In conclusion, the developed aqueous formulation contained 0.5% w/v of mangiferin and 20% w/v of polyethylene glycol 600 or dipropylene glycol as a solubilizer in water.

Mango leaf and synthetic additives in broiler diet: impact on growth, caecal microbiota, immunity, blood chemistry, and meat quality

Abstract This study assessed the influence of dietary supplementation of Mango leaf (ML), antibiotic (70% oxytetracycline + 30% neomycin) and tert-Butylhydroxyanisole on growth, immune indices, blood chemistry, caecal microbiota and meat quality in broilers. One day old Ross 308 chicks (n = 280) were randomly allotted to either F-1, basal diet (BD) without additive, F-2, BD + 0.4 g/kg antibiotic + 0.12 g/kg tert-Butylhydroxyanisole; F-3, BD + 2.5 g/kg ML; or F-4, BD + 5 g/kg ML for 42 d. At the starter phase, body weight gain (BWG) in F-3 and F-4 was higher (P 0.05) by dietary treatments. Caecal E. coli and Salmonella counts, serum immunoglobulin A and immunoglobulin M were higher (P

Allelopathic effects of Mangifera indica leaves on the growth performance of Brassica rapa ‘Chinensis’ (Pak choi)

Mangoes are a popular home garden crop in Brunei Darussalam, and their leaf litter is often used as compost, which is an environmentally friendly approach to manage organic waste. This study was conducted in 2018 at Universiti Brunei Darussalam to investigate the allelopathic effects of mango leaves on the growth of a leafy vegetable, Pak choi. Powdered and aqueous extract of mango leaves at various mango leaf concentrations (0–30%) were prepared and mixed with potted soils. Seedling survival, number of leaves and relative growth rates (based on stem diameter and shoot height) of Pak choi was not significantly affected by mango leaf treatment types and concentrations. Irrespective of mango leaf treatment types (powder vs. aqueous extract), biomass allocations to leaves (LMR) and roots (RMR), but not stems (SMR), were significantly inhibited at 10% and 20% mango leaf concentrations, respectively. However, stimulation in LMR and RMR of Pak choi was significantly observed in the opposite mango leaf concentrations. The aqueous mango leaf extract significantly stimulated specific leaf area (SLA) of Pak choi, suggesting that it probably contain less potent allelochemicals compared to the leaf powder, which inhibited SLA by almost 100%. Number of leaves and relative growth rates of Pak choi were not significantly affected by mango leaves. The findings suggest that aqueous mango leaf extracts at 20% could possibly be used in a sustainable organic leafy vegetable farming due to its growth stimulation in LMR and SLA. However, further research on other leafy vegetables and in field conditions are necessary due to the inhibitory allelopathic potentials of mango leaves.