Harumanis Mango Research Articles

Influence of Soil Moisture on Soil Temperature of Harumanis Mango Trees Under Controlled Environment

Soil moisture and temperature plays an essential role in plant growth and development. They are the main environmental variables controlling soil respiration and photosynthesis. For Harumanis mango grown in a controlled environment, these two variables are important in regulating the overall condition to imitate the required condition, particularly during vegetative growth. In this study, we aimed to investigate the influence of soil moisture on soil temperature in the Harumanis mango tree greenhouse. Two types of sensors: soil moisture and soil temperature sensor, were installed at 15 cm depth to monitor the in-situ readings at three specific locations in the selected greenhouse. Soil moisture and soil temperature were monitored for 20 days continuously at 10-minutes intervals. The results of linear regression indicated that an increase in soil moisture decreases the soil temperature, although there is a variation in data regarding the sampling locations. This information could help growers plan the irrigation efficiently (i.e. water amount) to initiate preferable dry conditions to induce flowering of these mango trees

Harumanis Mango Classification and Grading System Based on Geometric Shape Extraction for Quality Assessment

In agricultural research, a fruit's look, which affects its market value, is the first and most crucial sensory evaluation. According to external criteria like shape, size, ripeness index, and flaws or internal criteria like sweetness, flavor, and nutrients, fruits can be categorized and rated. Due to the grading task's importance and difficulty in post-harvest management, there is a high standard for fruit quality that must constantly be met. Growing interest in various categorization and grading algorithms aims to use non-contact and novel measurements to lessen the subjectivity of visual examination. In this paper, the proposed system that uses fruit shape and size as feature parameters for evaluating fruit quality has been implemented. A morphological analysis, median filter, and multilevel threshold-based image processing technique were created to assess the geometric shape of the mango image, including its length, width, and area. These factors are required to compute the standard shape of the Harumanis mango's similarity index and divide its size into four mass grades: small (S), medium (M), large (L), and extra-large (XL). The test results show the suggested technique had an accuracy rate of 98% and 96% for grading the size based on mass estimation and was very successful for quality classification based on measurement of the similarity index for a standard shape.

Investigating the Effects of Bamboo Vinegar as An Organic Pesticide on Insect Pests and the Nutrient Content of Harumanis Mango (MA128), Mangifera indica L.

Chemical pesticides have been widely used in plantations, and their effects have more disadvantages to the environment as well as to humans. Therefore, this study tries to implement organic pesticides using bamboo vinegar. Bamboo vinegar is one of the organic pesticides to control insect pests in plantation crops. The role of this organic pesticide on the insect pests of Harumanis mango is still unknown. Hence, this study aims to determine the impact of applying bamboo vinegar on the insect pests, quality, and nutrient content of Harumanis mango (MA128). Bamboo vinegar was applied in February 2021 during the flowering phase at the Harumanis plot in the Plantation Unit, Universiti Teknologi MARA Perlis. This study used a randomized complete block design with three treatments (spraying intervals) and three replications: T1 (3-day interval), T2 (5-day interval), and T3 (no bamboo vinegar). Sticky traps were installed to determine the population of insect pests in Harumanis mango. Matured fruits have been harvested, and the standard procedure of Harumanis mango postharvest handling has been followed. Then, the fruits were determined for total phenolic content (TPC), total flavonoid content (TFC), vitamin C, and sugar content. Bamboo vinegar significantly reduced the abundance of insects in Harumanis mango. Additionally, the highest TPC was observed from a 3-day interval of bamboo vinegar application. A similar trend was indicated for improving TFC with bamboo vinegar application. Similarly, there was a significantly higher vitamin C and sugar content after bamboo vinegar application compared to the control group. In conclusion, applying bamboo vinegar to Harumanis mango reduced insect pests and increased the quality and nutrient content of the Harumanis mango.

Insights into the Pharmacognostic Elucidation of Harumanis Mango (Mangifera Indica Linn.) Leaves Extracts as Therapeutic Agent

Mangifera indica L. (mango) of the Anacardiaceae family is a fruit with many phytochemicals that are extensively used in various traditional systems of medicine to prevent and treat various diseases. In Malaysia, harumanis is a local variety of mango widely cultivated in the northern region, namely Perlis. However, the drawback of this harumanis variety of mango is that research and information on its therapeutics are scarce and limited. Therefore, localized harumanis leaves were introduced to a series of pharmacognostic studies to provide critical details explaining harumanis as a potential therapeutic agent. Initially, the harumanis leaves were introduced to quality analysis tests, unveiling that the raw material used abided by proper post-harvesting protocols. Then, the harumanis leaves were extracted using ultrasonic aided extraction (UAE) with 100% methanol (13.73±0.24 %), 50% methanol (14.47±0.19 %), 100% ethanol (10.35±0.19 %), 50% ethanol (12.61±0.26 %), and distilled water (8.09±0.21 %). Next, the initial phytochemical screening revealed the presence of flavonoids, tannins, and saponins in all extracts. Subsequently, the phenolic and flavonoid content were quantified with the 50% methanol extracts recorded the highest total phenolic content (5.76 ± 0.02 mg/g), 50% ethanol extracts had the highest total flavonoid content (4.38 ± 0.04 mg/g). Fingerprinting analysis via FTIR spectroscopy was used to identify phytochemicals confirming the presence of flavonoids and phenolics compounds in all extracts. The extracts were then introduced to a DPPH inhibition assay with the highest IC50 value obtained from 50% methanol with 75.2 ± 0.22 microgram per milliliter. Next, the antimicrobial capabilities were tested using a disc diffusion study on E. coli, B. subtilis, and Face normal flora showing that the methanolic extract has superior abilities in microbial inhibitions with the value recorded at 13mm, 22mm, and 14mm respectively. Overall, we obtained valuable pharmacognostic data on the harumanis leaves extracts as potential antioxidant and antimicrobial agents.

Multiple-Criteria Decision Analysis for Effect of Shoot Growth at Difference Combination Nutrient Fertiliser NPK for Harumanis Mango

It is vital to have the correct fertiliser arrangement for effective tree development, fruit yield, and essential fruit quality. The amount of fertiliser suggested with adequate nutrition will be maintained in the soil to supply the needs of the trees as they grow throughout the various growth stages. This study evaluated the effect of different combinations of Nitrogen(N), Phosphorus(P), and Potassium(K) on the vegetative flush physiology of Harumanis mango (Mangifera Indica. L). Single and combinations of N (511g), P(511g), and K(255g) fertilisers were used, which were N, P, NP, and NPK throughout May 2021. The results revealed that the minimum number of mature green leaves and a higher number of healthy panicles were observed in the NPK-treated plants. Moreover, NPK treatment showed the lowest malformation intensity percentage compared to other fertiliser treatments. The data were analysed to obtain the best regrowth pattern of shoots using Multiple-Criteria Decision Analysis (MCDA) techniques. The results on the pattern of regrowth after pruning when federalised with NPK fertiliser showed that the maximum percentage of total vegetative flush was 87.5% and the remaining 12.5% did not reach a satisfactory level according to the MCDA analysis.

Analysis of Soil Nutrient (NPK) Test Value – Relative yield Relationship for Harumanis Mango using Modification Arcsine-Log Calibration Curve.

The cultivation of Harumanis mango (Mangifera indica) is of significant agricultural importance, especially in tropical regions like Malaysia, where it is renowned for its exceptional taste and quality. Maximizing mango yield and maintaining fruit quality are vital aspects of successful cultivation, relying on optimal soil nutrient management, particularly nitrogen (N), phosphorus (P), and potassium (K). In this research, the soil nutrient test value – relative yield relationship for Harumanis mango is investigated using a modification arcsine-log calibration curve. Traditional linear calibration curves may not fully capture the nonlinearities observed in crop responses, potentially leading to inaccurate nutrient requirements for optimal yield. By employing the innovative modification arcsine-log calibration curve, a more precise and robust relationship between soil nutrient test values and relative mango yield is established. Soil samples are collected from mango orchards, and NPK levels are measured using standardized laboratory techniques, alongside corresponding relative mango yields. This study advances precision agriculture by offering precise soil nutrient recommendations for mango farmers. Utilizing calibrated curves improves mango yield, minimizes nutrient waste, and encourages sustainable farming. In conclusion, the modified arcsine-log calibration curve reveals vital insights for optimal Harumanis mango production, benefiting the industry and sustainability.

Nutrient Requirements and Growth Response of Harumanis Mango (Mangiferaindica L.) during Vegetative Shoot Growth Stages: A Mitscherlich Law Analysis

This study investigates the nutrient requirements of Harumanis mango (Mangifera indica L) during different vegetative shoot growth stages by analyzing the soil nutrient test value-relative growth relationships. The research utilizes the Mitscherlich Law to model the response of mango yield in relation to varying nutrient levels. The data came from experimental plots, and the results show the asymptotic behavior of mango yield for three essential nutrients: nitrogen (N), phosphorus (P), and potassium (K). For vegetative shoot growth1, the asymptotic yield was estimated at 665.5 with a decline rate of -3.39 concerning N, -2.17 concerning P, and -1.35 concerning K. The coefficient of determination (R2) was 0.934, indicating a high goodness of fit for the model. Similar trends were observed for vegetative shoot growth2 and 3, where the asymptotic yields and nutrient decline rates varied accordingly. This study provides crucial insights into Harumanis mango nutrient needs across growth stages, aiding orchard management for sustainable yields. Applying the Mitscherlich Law enhances our understanding of how nutrients affect mango growth. These findings support targeted fertilization, boosting productivity and orchard efficiency. Future research can explore more growth factors and long-term nutrient impacts.

Development of Harumanis Mango Insidious Fruit Rot (IFR) Detection by Utilising Vibration-Based Sensors and PCA with Random Forest

Utilising single or multiple modalities systems, non-destructive techniques have been used to assess and determine the quality of mango (magnifera indica L.). It is challenging to anticipate and varies by cultivar at what harvest maturity stage will result in the optimum postharvest quality. Insidious Fruit Rot (IFR) is a disease that affects mangoes. When infected with Insidious Fruit Rot (IFR), the mango variety Harumanis does not exhibit exterior mutilation at the time of harvest or during the mature stage. However, a lack of density in the sinus area can occasionally be detected. Traditional ways of locating the diseases or pests living in the mango are useless for the commercialization of the product. This research presents the investigation done on IFR infection detection using piezoelectric vibration sensors and electret microphones. Data derived by the sensors were processed using the PCA and Random Forest methods to determine the non-IFR and the mango afflicted with IFR. The proposed approach achieved correct classification and is expected to be useful for planters in detecting IFR correctly before Harumanis mangoes were marketed.

Corrosion Inhibition Efficiency of Steel by Mango Peel Extract in Hydrochloric Acid at Different Temperature

Nowadays, researchers are interested in exploring the possibility of replacing harmful inorganic chemicals with green organic substances derived from natural sources. This study focuses on accessing the potential of a green corrosion inhibitor for mild steel, using plant extracts from local mango peel. The Harumanis mango peel leftover was extracted using solvent extraction techniques and the chemical compounds were characterized through Fourier Transform Infra-Red (FTIR) and UV-visible spectroscopy. The analysis showed that the crude extract of Harumanis mango peel (HMPE) contained active functional groups for corrosion inhibitory properties such as -OH, -COOH, -C=O and aromatic ring structure. The presence of mangiferin and other flavonols, likely acid gallic, was also detected. The efficiency of HMPE as a corrosion inhibitor for mild steel was investigated through a conventional corrosion test. The immersion test was carried out in different temperatures at 30, 40, 50 and 60 ⁰C with and without the addition of the 50 to 350 ppm HMPE inhibitor in 1 M hydrochloric acid, HCl. The result showed that the corrosion inhibition efficiency for mild steel in acidic medium increased as the concentration of the Harumanis mango peel increased. The maximum inhibition efficiency of 85 % was obtained at 30 ⁰C for 300 ppm. The adsorption of the Harumanis mango peel corrosion inhibitor obeys Langmuir isotherm model. The adsorption of HMPE on mild steel showed comprehensive (mixed) types as revealed by thermodynamic studies. Favourable adsorption was more dominant for 30 and 40 ºC inhibitors system, whereas at high temperatures the adsorption showed weak and unfavourable interaction between HMPE and the mild steel surface. Surface analysis showed the mild steel surface was free from pits and uniform corrosion as it was inhibited by the HMPE in low temperature solution.

Fabrication of active food packaging based on PLA/Chitosan/CNC-containing Coleus aromaticus essential oil: application to Harumanis mango

Fabrication of active food packaging based on PLA/Chitosan/CNC-containing Coleus aromaticus essential oil: application to Harumanis mango

Influence of Type and Concentration of Plasticizers on the Properties of Harumanis Mango Dregs Fruit Leather

ABSTRACT Mango dregs are a by-product that can be used as raw material for fruit leather because of their sufficient fiber and sugar content. The plasticizer forms the desired fruit leather texture that is not brittle and can be rolled up. This study determined the effect of the type and concentration of plasticizer on the physicochemical characteristics of mango dregs fruit leather. This research consisted of four treatments (mango dregs + 3% glycerol (G3); mango dregs + 5% glycerol (G5); mango dregs + 3% sorbitol (S3); mango dregs + 5% sorbitol (S5)) and control (mango dregs). Based on moisture content, hygroscopicity, and hardness results S3 produced the lowest moisture content i.e. 12.89%, hygroscopicity, i.e. 4.8 × 10−3 ±0.16 × 10−3 g H2O/g solid/hour, and hardness i.e. 3456.35 g. Fruit leather with the lowest water activity, reducing sugar, and total sugar was obtained by G5 i.e. 0.426 ± 0.004; 33.82%; and 53.60%, in order. Based on tensile strength, elongation, and Young’s modulus results G3 produced the lowest tensile strength i.e 3.89 MPa, highest elongation i.e. 43.73% and lowest Young’s modulus i.e. 8.88 MPa compared by control sample. Color characteristics show that G3 produced the best characteristics i.e. 57.15 ± 3.747 (L*), 15.33 ± 0.148 (a*), and 48.43 ± 5.765 (b*). Morphological properties by SEM showed that all treated samples exhibited compact, homogeneous, slightly spotted and have layers. The hedonic-quality organoleptic test showed that the mango dregs fruit leathers had a yellow (3.0), slightly strong taste (>2.5), smooth texture (2.8–3.0), and soft (3.0).

Measurement of leaf chlorophyll content in Harumanis mango cultivated in a greenhouse using SPAD meter

The Soil and Vegetation Analysis Development (SPAD) value was correlated to the actual value of chlorophyll content in the Harumanis mango leaf using a developed regression model. Distribution of chlorophyll content in Harumanis mango leaves were mapped using Geospatial Analyst in the ArcGIS. Total chlorophyll content and SPAD value were well established with the polynomial regression model with coefficient of determination (R2) of 0.925. The results show that the measured SPAD value in the morning were comparable to those value made in the evening and the Harumanis leaves located in the middle of the greenhouse have 25–31.3% lower chlorophyll content compared to other parts of the greenhouse.

Assessments of Nutrients Content in Soil and Leaves of Harumanis Mangoes and Its Relationship with the Yield

Crop yield can determine the health of a tree based on the nutrient content applied by the farmers. Soil nutrients are essential for plant production. This research aims to study the relationship between the yields of Harumanis mango and the nutrient content in soil and leaves. Three (3) primary objectives are highlighted, namely: (1) to study the distribution of nutrients content in the soil; (2) to determine the relationship between the yields of Harumanis mango and nutrient content in soil and leaves; and (3) to identify the significant factors affecting the yields of Harumanis mango. The study area is in the UiTM Perlis branch. Overall, 25 samples have been collected with information on the coordinate position, crop yield and nutrient content; nitrogen (N), phosphorus (P), potassium (K) and calcium (Ca). The Kriging method interpolated the distribution of nutrient content in the soil. Pearson correlation and multiple linear regression analysis were used to study the relationship between yield and nutrient content in soil and leaves to determine which nutrients influenced the yield of Harumanis mango. The result shows only K and Ca in the leaves significantly contribute to the yield of Harumanis mango. The multiple linear regression model for the predicted yield of Harumanis mango is 347.974 – 51.426 (N% in leaves) – 550.225 (K% in leaves) + 86.672 (Ca% in leaves).

Potential of Near-Infrared (NIR) spectroscopy technique for early detection of Insidious Fruit Rot (IFR) disease in Harumanis mango

Harumanis mango ‘Insidious Fruit Rot’(IFR), is one of the common issues that hampered the fruit quality and consequently lowered the premium value of Harumanis Mango. Physically and visually the affected fruit does not show any attributes that indicates the presence of IFR on any part of the fruit until it has been cut open. This paper investigates the feasibility of a non-destructive method to screen the Harumanis mango from IFR using near-infra red light and artificial neural network. A common NIR light emitting diodes of 1000nm wavelength was used as the light source to emit NIR light while a photodiode was used to measure the intensity of the reflected NIR light from Harumanis mango. Early detection of IFR were done manually by local expert using acoustic method by flicking fingers to detect any abnormality inside the fruit. Sample data on NIR Spectroscopy reflectance results of 120 samples were used to classify the presence of IFR using neural network. Mean value of NIR reflectance of RBG for Harumanis mango with an incidence of Insidious Fruit Rot are R=0.651, G=0.465 and B=0.458, while without IFR are R = 0.211, G=0.15 and B=0.146. Using MATLAB’s neural network training tool, a training set regression was obtained with an accuracy value of 0.9805 for prediction of IFR, thus this value is very high in accuracy.

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.

Fuzzy logic based prediction of micronutrients demand for harumanis mango growth cycles

Harumanis is a famous green eating mango cultivar that has been commercially cultivated in Malaysia’s state of Perlis. A variety of nutrients are found in soil, all of which are necessary for plant growth. Micronutrients such as Nitrogen (N), Phosphorus (P), and Potassium (K) are essential for Harumanis mango (Mangifera Indica) to growth. The importance of soil fertility in achieving high plant productivity and quality cannot be overstated. It should be used in a moderate amount and in a balanced manner. Predicting appropriate nutrients and the right timing to satisfy the tree’s demands is critical. The aim of this study is to create for Harumanis mango a fuzzy logic-based system to analyse the results of soil tests for nitrogen (N), phosphorus (P), and potassium (K) in the Harumanis mango orchard. The interpreted data are used to estimate N-P-K nutrient levels and indicate the optimal fertilizer solution and application timing for each Harumanis growth stages. The system utilizes Fuzzy Logic Control (FLC) to predict the nutrients demand for Harumanis mango growth. Results shows the system able to calculate and predict values of required N-P-K fertilizer for optimal growth. Thus, assist farmers in predicting the proper amount of N-P-K to apply to Harumanis mango soil.

Harumanis Mango Leaves Image Segmentation on RGB and HSV Colour Spaces using Fast k-Means Clustering

Harumanis mango is the signature fruit in Perlis due to its delicious taste and its sweet-smelling. A good quality Harumanis tree requires rich in nutrition (healthy), and the tree will grow lots of fruits compared to the trees which are poor in nutrition (unhealthy). The health condition of a tree can be observed through the leaves in term of shape of leaves. For a healthy Harumanis tree, the leaves grow in scattering shapes. Meanwhile, an unhealthy Harumanis tree grows in gathered shapes. Therefore, this research is focusing on Harumanis mango leaves image segmentation by comparing between RGB and HSV colour spaces in order to obtain the best segmentation performance. 100 of Harumanis mango tree leaves images are used in this research. These images have undergo through image pre-processing such as modified linear contrast stretching and colour components extraction based on RGB and HSV colour spaces. Then, the colour component images have been segmented by using fast k-means clustering in order to obtain the leaves segmented images. Finally, quantitative analyses have been performed to measure the segmentation performance based on sensitivity, specificity and accuracy. Overall, the results show that S component of HSV colour space archives the highest accuracy with 85.81%.

Defects Detection Algorithm of Harumanis Mango for Quality Assessment Using Colour Features Extraction

Visual defects detection is one of the main problems in the post-harvest processing caused a major production and economic losses in agricultural industry. Manual fruits detection become easy when it is done in small amount, but the result is not consistent which will generate issue in fruit grading. A new fruit quality assessment system is necessary in order to increase the accuracy of classification, more consistencies, efficient and cost effective that would enable the industry to grow accordingly. In this paper, a method based on colour feature extraction for the quality assessment of Harumanis mango is proposed and experimentally validated. This method, including image background removal, defects segmentation and recognition and finally quality classification using Support Vector Machine (SVM) was developed. The results show that the experimental hardware system is practical and feasible, and that the proposed algorithm of defects detection is effective.

English

Identification of zygotic and nucellar seedlings of Harumanis mango by morphological approach is impossible or hard to be performed. Therefore, this research were to identify zygotic or nucellar seedlings from Harumanis mango polyembryonic seeds through simple sequence repeat (SSR) molecular markers in relation with germination sequence and vigour of seedlings for source of true-to-type cutting material. The results showed that there were 3 seedlings per seed on average. The result from the molecular analysis of 136 seedlings (45 seeds) showed four zygotic seedlings in seeds 1, 15, 29 and 43 representing 8.9% of seeds evaluated. Most of the zygotic seedlings were found towards the end of germination sequence except for seed number 15 and the rest were considered as nucellar seedlings. Based on the fitted logistic regression, the predicted sequence to obtain 90% nucellar seedlings is 5.47. This means that, the germination sequence of less than 6 has 90% chance of getting nucellar seedlings compared to zygotic seedlings. Morphological characters such as number of leaves, stem diameter and leaf area could also be used as references with germination sequence. The results showed that there were significant (p<0.01) relationships between germination sequence and all the growth variables. All growth variables were negatively correlated with germination sequence. This suggested that in order to have 90% chances of getting nucellar seedling (germination sequence below 6), the seedling needs to exhibit several morphology characters; big stem girth, tall plant, high leaf number and large leaf area. Therefore, choosing vigour seedling will increase chances of getting nucellar seedlings, which can be used as cutting source for true-to-type planting material or for breeding purposes.   Key words: Harumanis, molecular, morphology, nucellar, SSR markers, zygotic.

Analysis for the Estimation of Harumanis Mango Ripeness Guide

Harumanis mango ripeness guide is hardly to reach to predict the ripening stages in a such this emerging artificial intelligence commencing technology. The use of digital support tool for selective fruits in predicting the ripening stages should be subdued, exercising to be accessible by directive users. Having those lacks, this preliminary project is a first step to analyse the ripeness stages of harumanis mango referring to firmness, pulp colours and total soluble sugar (TSS) for digitalization purposes. Twenty-five harumanis mangoes harvested at week tenth were used, which had an average of mass for 417.96 ± 163.24 g. Five samples randomly selected in each stage by settling them under a room temperature and two days interval period. Findings showed the lowest TSS content uncovered at stage 2 for 6.94 Brix and the highest found at stage 5 for 15.02 Brix. The highest firmness unfolded in stage 2 with value of 2.902 kgf and the lowest discovered in stage 5 for 0.810 kgf. The pulp colours showed reduction of blue values for 70, activated at stage 3. The results suggested that harumanis mango started deteriorating after six days of room temperature storing period, this followed by rapid degradation of firmness and increasing of TSS value. Moreover, combinations colour values of red, green and blue composed constructive predictive yellowish variants throughout stages, positively useable to development of digital decision support tool.