Melon Leaf Research Articles

Comparative transcriptome profiling suggests the role of phytohormones in leaf stalk-stem angle in melon (Cucumis melo L.).

Leaf stalk-stem angle is an important agronomic trait influencing melon architecture, photosynthetic efficiency, and crop yield. However, the mechanisms governing leaf stalk-stem angle, particularly in melon, are not well understood. In this study, we explored the comparative transcriptome in the expanded architecture line Y164 and the compact plant architecture line Z151 at 30 days after pollination. Phytohormones were measured at the leaf stalk-angle site at the same time in these two lines using liquid chromatography (LC) tandem mass spectrometry (MS) (LC-MS/MS). The phytohormones and transcriptomes were jointly analyzed. Differential hormone profiling revealed that the levels of 1-aminocyclopropane-1-carboxylate (ACC) and 12-oxophytodienoic acid (OPDA) in the large-angled line Y164 were significantly higher than those in the small-angled line Z151. These differences were quantified as 2.1- and 2.8-fold increases, respectively. Conversely, the content of isopentenyl adenosine (IPA) was significantly elevated in Z151, with a 3.8-fold higher concentration relative to Y164. Transcriptome analysis identified a total of 1709 differently expressed genes (DEGs), with a predominant enrichment in the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways related to photosynthesis and plant hormone signal transduction. Similarly, photosynthesis and the hormone metabolic process were predominantly enriched in the biological process of Gene Ontology (GO) terms. Further integration of transcriptome and hormone analyses substantiated the close relationship between melon leaf stalk-stem angle and phytohormones, especially ACC, OPDA and IPA. Selected DEGs from phytohormone signal transduction were validated. Detailed analysis of DEGs highlighted the potential role of genes such as GH3s (LOC103490488, LOC103490483), SUARs (LOC107991561, LOC103497281 and LOC103489067), ARFs (LOC103503893, LOC103493078) and five genes in abscisic acid pathway. In summary, our findings strongly suggest a direct correlation between phytohormones and the leaf stalk-stem angles in melon.

Carcass Characteristics, Meat Antioxidative State, and Gut Microbiota of Broilers Fed With a Mixture of Bitter Melon and Basil Leaves Powder

The impact of a mixture of bitter melon leaf and basil leaf powder (BBLPB) on the carcass characteristics, meat antioxidant state, and gut microbiota of broilers was investigated. Three hundred one-day-old Cobb 500 broiler chicks were allocated to five diets: diet 1 (negative control), diet 2 (positive control; 0.1% blend of probiotic, prebiotic, and acidifier (BPPA) supplementation), diets 3 (0.25% BBLPB), 4 (0.5% BBLPB), and 5 (0.75% BBLPB) randomly. The 0.25% BBLPB supplementation improved (P < 0.05) slaughtered weight, dressed weight, dressing %, and growth rate of broilers, while organ weights remained unchanged (P > 0.05). Slaughtered weight recorded in diets 2 and 3 was higher (P

Identification of Chromosomal Regions and Candidate Genes for Round leaf Locus in Cucumis melo L.

Leaf morphology plays a crucial role in plant classification and provides a significant model for studying plant diversity while directly impacting photosynthetic efficiency. In the case of melons, leaf shape not only influences production and classification but also represents a key genetic trait that requires further exploration. In this study, we utilized forward genetics to pinpoint a recessive locus, dubbed Cmrl (Round leaf), which is responsible for regulating melon leaf shape. Through bulked segregant analysis sequencing and extensive evaluation of a two-year F2 population, we successfully mapped the Cmrl locus to a 537.07 kb region on chromosome 8 of the melon genome. Subsequent genetic fine-mapping efforts, leveraging a larger F2 population encompassing 1322 plants and incorporating F2:3 phenotypic data, further refined the locus to an 80.27 kb interval housing five candidate genes. Promoter analysis and coding sequence cloning confirmed that one of these candidates, MELO3C019152.2 (Cmppr encoding a pentatricopeptide repeat-containing family protein, Cmppr), stands out as a strong candidate gene for the Cmrl locus. Notably, comparisons of Cmrl expressions across various stages of leaf development and different leaf regions suggest a pivotal role of Cmrl in the morphogenesis of melon leaves.

Feeding Activity of Heliotis armigera Hubner Larvae on Food Formulated with Ethanol Extracts of Bitter Melon Leaves (Momordica charantia L.), Galangal Leaves (Lactuna indica L.) and Adjuvant Agrestic

The research on the Feeding Activity of Heliotis armigera Hubner larvae on food formulated with ethanol extracts of bitter melon leaves (Momordica charantia L.), galangal leaves (Lactuna indica L.) and adjuvant agrestic has been conducted. This study used the ratio formulation of bitter melon and galangal (1:1, 1:2, 2:1), 1% adtjuvan agristik. The feeding activity was observed using the feeding method with several concentrations (0.00, 0.58, 1.16, 1.74, 2.32, 2.92) and 15 larvae for iterations using a completely randomized design (CRD). The data from the observations were analyzed using variance; if there were differences, it would proceed to the Duncan test of 5%. Insect feeding activity is influenced by food containing concentrations of 1.16% - 2.92% of a formulation (1:1, 1:2, 2:1) of bitter melon leaf extract, galangal leaf extract, and 1% agrestic adjuvant, leading to a decrease in insect growth rate (RGR). The insect's feeding ability (RCR), ability to convert consumed food into usable nutrients (ECI), and ability to digest food and utilize it (ECD) are also reduced. Conversely, the ability to digest insect food (AD) is increased. The best formulation and concentration are (2:1) and (1.74%).

Healing of diabetic foot ulcer with topical and oral administrations of herbal products: A systematic review and meta-analysis of randomized controlled trials.

This systematic review aimed to qualitatively synthesize recent randomized controlled trials (RCTs) regarding the effect of topical application and oral intake of herbal products on the healing of diabetic foot ulcer (DFU). Also, we sought to pool the obtained findings in a meta-analysis using a random-effects model, if RCTs were relatively comparable and homogenous. A comprehensive search was performed on five electronic data sources from their inception through 23 January 2024. The RCTs, without restriction on the country of origin, were included if they compared the effect of administering standard treatments and/or placebo (i.e. control condition) to applying standard treatments and/or herbal products in topical or oral routes (i.e. experimental condition). Out of 1166 retrieved records, 28 RCTs were included. Studies used different poly and single herbal formulations. Based on the meta-analysis, administration of standard care plus daily dressing of the ulcer site with olive oil for 28 days significantly increased the total ulcer healing score (3 RCTs; weighted mean difference [WMD] = 89.30; p < 0.001), raised frequency of complete ulcer healing (2 RCTs; risk ratio [RR] = 12.44; p = 0.039) and declined ulcer degree (3 RCTs; WMD = -22.28; p = 0.002). Also, daily use of the bitter melon leaf extract in oral form for 28 days significantly increased the total ulcer healing score (2 RCTs; WMD = 0.40; p = 0.001). Additionally, based on qualitative synthesis, the adjuvant use of herbal agents seems an intriguing choice to manage DFU. Nonetheless, considering the undesirable methodological quality of most studies and the high heterogeneity in administered herbal formulations, more robust trials are required to build a solid conclusion regarding the use of herbal products for healing DFU.

Utilizing UAV Data for Neural Network-based Classification of Melon Leaf Diseases in Smart Agriculture

Utilizing UAV Data for Neural Network-based Classification of Melon Leaf Diseases in Smart Agriculture

Design and Experiment of a Portable Near-Infrared Spectroscopy Device for Convenient Prediction of Leaf Chlorophyll Content.

This study designs a spectrum data collection device and system based on the Internet of Things technology, aiming to solve the tedious process of chlorophyll collection and provide a more convenient and accurate method for predicting chlorophyll content. The device has the advantages of integrated design, portability, ease of operation, low power consumption, low cost, and low maintenance requirements, making it suitable for outdoor spectrum data collection and analysis in fields such as agriculture, environment, and geology. The core processor of the device uses the ESP8266-12F microcontroller to collect spectrum data by communicating with the spectrum sensor. The spectrum sensor used is the AS7341 model, but its limited number of spectral acquisition channels and low resolution may limit the exploration and analysis of spectral data. To verify the performance of the device and system, this experiment collected spectral data of Hami melon leaf samples and combined it with a chlorophyll meter for related measurements and analysis. In the experiment, twelve regression algorithms were tested, including linear regression, decision tree, and support vector regression. The results showed that in the original spectral data, the ETR method had the best prediction effect at a wavelength of 515 nm. In the training set, RMSEc was 0.3429, and Rc2 was 0.9905. In the prediction set, RMSEp was 1.5670, and Rp2 was 0.8035. In addition, eight preprocessing methods were used to denoise the original data, but the improvement in prediction accuracy was not significant. To further improve the accuracy of data analysis, principal component analysis and isolation forest algorithm were used to detect and remove outliers in the spectral data. After removing the outliers, the RFR model performed best in predicting all wavelength combinations of denoised spectral data using PBOR. In the training set, RMSEc was 0.8721, and Rc2 was 0.9429. In the prediction set, RMSEp was 1.1810, and Rp2 was 0.8683.

Aktivitas Kombinasi Krim Daun Pare (Momordica charantia L) dan Kulit Jeruk (Citrus nobilis) dalam Penyembuhan Luka Bakar

Burns are injuries to the skin caused by heat, fire, hot steam, exposure to chemicals, solar radiation, or electric shock. Burns need to be treated immediately because they can cause infection in the skin. Healing burns can be done by utilizing several types of existing plants, namely bitter melon leaves and orange peels which are known to be able to help heal burns because they contain secondary metabolites such as flavonoids, tannins, saponins, steroids, alkaloids, and terpenoids which can be used for wound healing. The purpose of this study was to determine the effect of a combination of bitter melon leaf extract cream and orange peel as healing burns in white rats. This research is a quantitative study using laboratory experimental methods with a post test only control group design. In this study, male white rats were made with wounds on the back skin. Using 20 white rats divided into 5 different treatment groups. The negative control was given a cream base, the positive control was given Burnazin cream, F1 3% : 5%, F2 ie 4% : 4%, F3 ie 5% : 3%. The wound was smeared with preparations according to group division and carried out for 14 days. Based on the results of observations of the effect of a combination of bitter melon leaf extract and orange peel cream at F1 concentrations with a concentration ratio of 3%: 5%, it has a faster healing effect on burn area. Based on the results of the Kruskal wallis test on the healing of second degree burns in male white rats, there was a significant difference. The p value or sig is 0.014, so it can be concluded that there is a significant difference between the healing areas of burns in white rats.

Gambaran Daya Bunuh Larvasida Ekstrak Daun Pare (Momordica charantia L.) dengan Metode Infudasi dan Metode Maserasi

Culex sp. is one of the insects as a vector of chronic filariasis disease. Filariasis are often found in tropical countries such as Indonesia so its presence needs to be controlled. One of the controls that can be done is by killing the larvae with natural larvicides made by infudsion and maceration methods. This study aims to determine the description of mortality of Culex sp. larvae after being given natural larvicides, namely bitter melon leaf extract with certain concentration levels. Descriptive research was conducted with samples of Culex sp. larvae taken from a ditch which is the original habitat. This study was repeated 6 times and observation of larvae mortality at 24 hours after administration of the extract. The extract was made into 4 concentration levels, namely 1%, 5%, 10% and 15%. The four concentrations obtained results that the maceration method effectively kills 100% of Culex sp larvae at a concentration of 5% while the infusion method requires a concentration of &gt;15% so that all larvae can be killed. This can occur because in the infusion method the bioactive compounds do not diffuse optimally so that the levels of bioactive compounds as larvicides are also lower than the maceration method.

Essential oils on the control of melon leafminer

Studies on the effect of essential oils for the control of melon leaf miner adults (Liriomyza trifolii Burgess) and the phytoxicity on melon plants (Cucumis melo L.) were carried out under green house and laboratory experiments with the aim to find the effectivity of essential oils to control this pest. Essential oils (treatments) used in the tests belonged to the following plant species: Ocimum basilicum, Ocimum kilimandshanicum, Lippia alba, Ocimum gratissimum, Cymbopogon citratus, Ocimum micrantum, Lippia sidoides, Pipper aduncum, Citrus sinensis, Ocimum selloi and water as the control. In addition, two mixtures were evaluated: Mix 1 (Ocimum selloi + Pipper aduncum) and Mix 2 (Ocimum kilimandshanicum + Ocimum gratissimum). Each essential oil evaluated had the following dilutions: 0.125%, 0.25%, 0.5%, 1.0%, 3.0%, 5.0%, 7.0%, and 10.0%. The dilution 0.125% of Ocimum basilicum, Ocimum kilimandshanicum, Ocimum seloi, Cimbopogon citratus, Lippia alba, Peper aduncum and Mix 2 presented the best results by not causing any phytotoxicity damage to melon leaves. The other dilutions were significantly different from the pattern water. As result, the essential oil of the species Ocimum kilimandshanicum with 0.125% caused 100.0% of mortality to melon leaf miner adults and it did not cause any phytotocixity damage to melon leaves. Therefore, these results suggest that this essential oil presents a high potential to be a future commercially friendly product against melon leaf miner pest.

Benchmarking the LGBM, Random Forest, and XGBoost Models Based on Accuracy in Classifying Melon Leaf Disease

Benchmarking the LGBM, Random Forest, and XGBoost Models Based on Accuracy in Classifying Melon Leaf Disease

Perbandingan Algoritma K-Means dan Fuzzy C-Means untuk Clustering Citra Daun Melon

Melon plants are plants that are susceptible to disease, both diseases caused by viruses and those caused by bacteria. One part of the plant that can be affected by the disease is the leaves. Leaves on diseased plants generally change color which will then affect other leaves and inhibit the development and growth of these plants. This study aims to classify melon plant diseases from melon leaf images. The data used in this study are 160 images of melon leaves which will be grouped into several groups from the healthy group to the unhealthy group. The method used is the Clustering method, namely: K-Means algorithm and Fuzzy C-Means algorithm. Clustering results using K-Means and Fuzzy C-Means can be compared to get the best clustering results. The comparison results show the Fuzzy C-Means Clustering method with a validation value of 0.8359 and the K-Means Clustering method with a validation value of 0.5793. The final result shows that the Fuzzy C-Means Clustering method is better than the K-Means Clustering method because the validation value is close to 1.

First report of zucchini yellow mosaic virus infecting bitter melon (Momordica charantia) in South Korea.

Bitter melon (Momordica charantia L., family Cucurbitaceae) is used in traditional medicine for diabetes, cancer, and inflammation-associated diseases due to bioactive compounds in Asia and tropical Africa (Bortolotti et al. 2019). In July 2021, approximately 10% of bitter melon plants in the field showed symptoms such as mosaic, yellowing, and leaf deformation on the leaves, in Samchcuk, South Korea. Cucumber and zucchini plants growing in the same field exhibited symptoms like those of bitter melon plants (Ali et al. 2012). To investigate the causative virus, leaf dip preparations from three symptomatic bitter melon leaf samples with symptoms were analyzed by transmission electron microscopy (TEM). Potyvirus-like particles (approximately 680-730 nm in length and 11-13 nm in diameter) were observed in all samples. To further identify the causal viral pathogens, leaf extracts from five symptomatic bitter melon plants were tested by DAS-ELISA using specific antibodies (Agdia, Elkhart, IN, USA) against cucumber mosaic virus, zucchini yellow mosaic virus (ZYMV), watermelon mosaic virus, and papaya ring spot virus. Positive controls from commercial kits and negative controls from healthy bitter melon plants were included in ELISA assay. The serological assay revealed that all five symptomatic samples positively reacted with the antiserum against ZYMV, but not for other viruses. Total RNA extracted from the five ELISA-positive samples and two healthy bitter melon plants (as negative controls), using Clear-S Total RNA extraction kit (InVirusTech Co., Gwangju, Korea), was tested by RT-PCR with ZYMV-specific primers as previously described (Cho et al. 2011). All amplicons of the expected size (~822 bp) were individually cloned into the pGEM-T Easy Vector (Promega, Madison, WI), and sequenced in both orientations. Thereafter, all the sequenced clones shared 100% nucleotide identity. The sequence of ZYMV-MC1 isolated from bitter melon was deposited in the GenBank (accession no. LC652434). Pairwise comparison of the nucleotide sequence with that of ZYMV isolates in the GenBank revealed 99% sequence identity with ZYMV-chk (MG020559) from Korea, 98% with ZYMV-14-HY-SCS (KU743321) from China, 97% with ZYMV-Y21 (MW345249) from Turkey, 96% with ZYMV-AUIKTPK (KR261951) from Pakstan. Leaf saps from the ZYMV-positive bitter melon samples, prepared in 10 mM phosphate buffer (pH 7.0), were mechanically inoculated in five young, healthy bitter melon plants to fulfil Koch's postulates. ZYMV-MC1 isolate caused mosaic and leaf deformation on bitter melon plants 10 days post-inoculation. The presence of ZYMV in the symptomatic leaves was confirmed by RT-PCR using the mentioned above primers mentioned above followed by nucleotide sequencing of the amplicons. Several cotton aphids (Aphis gossypii) were observed in the bitter melon field, which indicated that they might transmit the virus from ZYMV-infected cucumber or zucchini plants. ZYMV is one of the economically important viruses of cucurbits worldwide and has been recently reported from various crops as natural hosts, including Chayote (Yoon et al. 2018) and balloon flowers (Kim et al. 2021). To the best of our knowledge, this is the first report of ZYMV naturally infecting bitter melon in South Korea. Further large -scale surveys are required to determine its incidence, yield losses, and management in bitter melon in Korea.

Enhanced ultrasonically assisted extraction of bitter melon (Momordica charantia) leaf phenolic compounds using choline chloride-acetic acid–based natural deep eutectic solvent: an optimization approach and in vitro digestion

Bitter melon (Momordica charantia) is a rich source of phytochemicals including phenolic compounds with diverse health-promoting benefits and potential food industry application due to their antioxidant potential. Bitter melon leaves have been limitedly investigated in comparison to bitter melon fruits. The current work explores the use of green extraction methodology to optimize enhanced extraction of phenolic compounds from bitter melon leaves using ultrasonically assisted extraction and choline chloride-acetic acid (CHAC)–based natural deep eutectic solvent. Extraction using CHAC significantly improved the extraction of total phenolic compounds, total flavonoids, and individual phenolic compounds (including gallic acid, chlorogenic acid, vanillic acid, epicatechin, and quercetin-3-glucoside) in comparison to water, ethanol, and methanol. The effect of molar ratio, water content, temperature, and time on the extraction efficiency of bitter melon leaf phenolic compounds by CHAC was explored and optimized with surface response methodology (central composite design). The optimum condition for the extraction of individual phenolic compounds is a molar ratio of 1:4.35 CHAC with 20.68% water content at 75 °C for 21.23 min. Evaluation of the bioaccessibility of individual phenolic compounds concluded that the most bioaccessible compound was vanillic acid (105.00 ± 2.52%) followed by salicylic acid, chlorogenic acid, syringic acid, gallic acid, epicatechin, and quercetin-3-glucoside.

Real-time object detection method of melon leaf diseases under complex background in greenhouse

Real-time object detection method of melon leaf diseases under complex background in greenhouse

First report of chayote yellow mosaic virus in Côte d’Ivoire: a divergent strain infecting bitter melon

In this report, we present the first description of nine complete genome sequences of a new strain of chayote yellow mosaic virus (ChaYMV, genus Begomovirus, family Geminiviridae), provisionally named Côte d’Ivoire (ChaYMV-CI), isolated from bitter melon (Momordica charantia) leaf samples showing yellow mosaic symptoms collected in the region of Abidjan in Côte d’Ivoire in 2013 and 2019. The nucleotide sequences of ChaYMV-CI DNA-A-like genome share the highest nucleotide sequence identities (91.8–92.5%) with those of ChaYMV isolates from Benin and Cameroon. Phylogenetic analysis confirmed the segregation of ChaYMV isolates into two distinct clades and their affiliation to Old World monopartite begomoviruses. The discovery of a new strain of ChaYMV in West Africa, at the limit of the taxonomic demarcation threshold for begomoviruses (91%), call for further investigations into the molecular diversity, geographical distribution and host range of ChaYMV in Western Africa.

Pengaruh Ekstrak Etanol Daun Momordica Charantia L. Terhadap Aktivitas Proteksi Mukosa Lambung Tikus

Momordica charantia L. contain alkaloid, flavonoid, phenolic, tannin and saponin compounds which can protect the gastric mucosa. This study aims to determine the effect of giving the ethanol extract of bitter melon leaves (Momordica charantia L.) on the protective activity of the gastric mucosa in aspirin-induced male white rats. Momordica charantia L maceration using 70% ethanol as a solvent. The gastric mucosal protective activity test used 15 male white rats which were divided into 5 groups. The treatments were given orally for 3 days including: the positive control group was given 0.5% Na-CMC + aspirin 600 mg/kgBB, the comparison control group was given sucralfate suspension 360 mg/kgBB + aspirin 600 mg/kgBB, the test dose group 1 was given Pare leaf ethanol extract 100 mg/kgBB + aspirin 600 mg/kgBB, group 2 test dose was given ethanol extract of bitter melon leaves 200 mg/kgBB + aspirin 600 mg/kgBB and group 3 test dose was given ethanol extract of bitter melon leaves 400 mg/kgBB + aspirin 600 mg/kgBB. On day 3, the mice were dissected after 4 hours of aspirin administration, observation and the percentage of gastric mucosal protection in the rats was calculated. Data were analyzed statistically with one-way ANOVA test followed by Duncan's test. The bitter melon leaf extract had a significant effect (p &lt;0.05) on the protection of the gastric mucosa. The highest percentage of protection was shown by the dose of 400 mg / kgBW at 62.48%.

Performance Analysis of Deep Learning-based Object Detectors on Raspberry Pi for Detecting Melon Leaf Abnormality

Melon requires intensive treatment with a high cost of maintenance. Digital image processing with deep learning can help handle diseases in melon plants efficiently. Deep-learning-based object detection has significantly better accuracy than the traditional one. However, the deep-learning-based approach leads to high computational and storage resources consumption. Speed and accuracy become tradeoffs to deal with its implementation on devices with limited computing capabilities like Raspberry Pi. This study comparatively analyzes deep-learning-based object detection algorithm performance implemented on a limited computing device, namely Raspberry Pi. The detected object in this study is melon leaves which are classified into two categories, namely abnormal and normal. The experiment was conducted using Faster R-CNN, Single Shot Multibox Detection (SSD), and YOLOv3. The results showed that Faster R-CNN had the highest mAP (~49 %) that ran ~2.5 seconds for an image but had the highest resource usage. Since accuracy is more important than time complexity in melon leaf detection, Faster R-CNN can be recommended as the best object detection algorithm to implement on Raspberry Pi. However, SSD is a fast algorithm with considerable accuracy for real-time detection. In addition, it had not only fast computational time, but SSD MobileNetV2 also spent the least resource usage. Although YOLOv3 had a significantly better running time (0.5 s) which made YOLOv3 the fastest algorithm, it had too low mAP (below 20%). Therefore, YOLOv3 is not recommended for melon leaf abnormality detection since it can allow more detection errors to occur.

Insecticidal Activity of Bitter Melon (Momordica charantia L.) Leaf Extract on Mung Bean Weevil (Callosobruchus chinensis L.)

Infection of mung bean weevil (Callosobruchus chinensis) might cause weight loss of mung bean seeds up to 55-69% and loss of protein content up to 45.6-66.3%. An eco-friendly strategy to manage this storage pest could be performed through the utilization of botanical pesticide, such as the leaf extract bitter melon (Momordica charantia L.). This study was aimed to investigate the insecticidal activity of bitter melon leaf extract (BMLE) against mung bean weevil. This study was conducted using Completely Randomized Design consisting of 5 dosages of BMLE application (0, 1.4, 2.7, 5.3, and 9.6%) with 5 repetitions. BMLE was applied to 100 g of mung bean seeds, then 10 mung bean weevils were infested into the treated seeds and stored for 38 days in room temperature. Both insecticidal activity and seed quality were carefully observed during the storage period. Results showed that application of 5.3 and 9.6% BMLE exhibited similar mortality of mung bean weevil. Both dosages also showed no negative effect on the seed quality indicating that BMLE might also contribute in maintaining the seed during the storage. Therefore, these results emphasized the promising potential of BMLE to be developed as the botanical insecticide for storage pest.

Improving Diabetic Foot Ulcer Healing with Adjuvant Bitter Melon Leaf Extract (Momordica charantia L.)

BACKGROUND: Diabetes mellitus is a serious disease that affects more than 340 million people and causes approximately 20% of diabetic ulcer cases worldwide. Wound healing is a complex and dynamic process in restoring cellular structures and tissue layers. It consists of four continuous overlapping phases that are precisely programmed AIM: This study aims to examine the adjuvant administration of bitter melon leaf extract to increase the healing of diabetic foot ulcers (DFU). METHODS: This study used a randomized, double-blind, and placebo-controlled trial. A total of 30 DFU patients with a perfusion, extent, depth, infection, and sensation (PEDIS) score of 1–8 who met the criteria were divided into two groups, namely, the treatment group with adjuvant administration of bitter melon leaf extract at a dose of 6 g/day as many as 15 patients and the control group 15 patients with placebo. This intervention was carried out for 4 weeks. DFU cure was measured by PEDIS scores at baseline, weeks 2, 3, and the end of week 4. Data were analyzed using paired t-test and independent t-test. RESULTS: After 4 weeks of treatment, the PEDIS score in the treatment group decreased at week 2 (0.9 ± 1.8), but not significant (p = 0.19), decreased at week 3 (1.9 ± 1.9) and significant (p = 0.01), decreased in week IV (2.3 ± 2.1) and significantly (p = 0.001). The control group experienced a decrease in week 2 (0.3 ± 2.3), but not significant (p = 0.71), decreased in week 3 (1.2 ± 2.5), but not significant (p = 0.18), decreased in week 4 (1.9 ± 2.7) and significantly (p = 0.03), and there was an effect of adjuvant administration of bitter melon leaf extract on the cure of DFU (p = 0.004). CONCLUSION: Adjuvant administration of bitter melon leaf extract has been shown to increase the healing of DFU.