Banana Research Articles

Per-acetic acid effect on separation of banana fiber and their dyeing with natural dyes

The fiber derived from the pseudo-stem of the banana plant is the subject of this investigation. It describes the processes involved in creating pseudo-stem fiber from bananas, such as fiber extraction, retting, and degumming. Banana fiber has been separated using per-acetic acid. To evaluate the efficacy of the process, the fiber's appearance and form have been altered. A homogeneous, spotless surface was observed under Scanning Electron Microscopy. Weight loss is the outcome of the treatment and absorbency increases. 3.66% of the weight loss is attributed to the per-acetic acid treatment. The fiber’s average diameter was reduced 81.9% compared to the raw fiber. Fourier transform infrared spectroscopy analysis was utilized to assess the chemical changes brought about by the treatment, which verified the presence of cellulose in the fiber. The separated fibers were colored using natural dyes, which were then assessed based on how well they characterized the color. The results demonstrated the use of natural colors derived from extracts of madder and myrobalan. The standard test indicates that ferrous sulfate (FeSO4) exhibits strong resistance to light, washing, and rubbing fastness, making it a viable mordant for achieving brown to black color.Graphical

SKGDC: Effective Segmentation Based Deep Learning Methodology for Banana Leaf, Fruit, and Stem Disease Prediction

SKGDC: Effective Segmentation Based Deep Learning Methodology for Banana Leaf, Fruit, and Stem Disease Prediction

Development of artificial lighting system for light supplementation in smart greenhouses with agrivoltaic systems

This work developed two smart greenhouses for the protected cultivation of banana and orchid seedlings. The greenhouses feature control and automation systems, bioclimatic architecture and strategies, and energy systems. A sensor network monitors indoor environmental variables, and a weather station monitors outdoor environmental variables. A computational system based on artificial intelligence is responsible for the autonomous control of the greenhouses. This article presents the development of an artificial lighting system for light supplementation in smart greenhouses. The artificial lighting system was defined from modeling and simulation in a computational tool. The proposed system was installed in two smart greenhouses in southern Brazil. The article also presents the development of methods for estimating electricity consumption based on assumptions and operational profiles of the system and the experimental measurement of the artificial lighting system performed according to the procedure described in technical standards. The article presents the energy performance of the agrivoltaic system applied to smart greenhouses. From August 2022 to July 2023, the final yield of the agrivoltaic systems of the smart greenhouses was 1418.91 kW h/kWP and 1490.68 kW h/kWP. The annual electricity consumption of the artificial lighting systems of the smart greenhouses ranges between 3290 kW h and 3825 kW h.

Analysis of banana plant health using machine learning techniques

The Indian economy is greatly influenced by the Banana Industry, necessitating advancements in agricultural farming. Recent research emphasizes the imperative nature of addressing diseases that impact Banana Plants, with a particular focus on early detection to safeguard production. The urgency of early identification is underscored by the fact that diseases predominantly affect banana plant leaves. Automated systems that integrate machine learning and deep learning algorithms have proven to be effective in predicting diseases. This manuscript examines the prediction and detection of diseases in banana leaves, exploring various diseases, machine learning algorithms, and methodologies. The study makes a contribution by proposing two approaches for improved performance and suggesting future research directions. In summary, the objective is to advance understanding and stimulate progress in the prediction and detection of diseases in banana leaves. The need for enhanced disease identification processes is highlighted by the results of the survey. Existing models face a challenge due to their lack of rotation and scale invariance. While algorithms such as random forest and decision trees are less affected, initially convolutional neural networks (CNNs) is considered for disease prediction. Though the Convolutional Neural Network models demonstrated impressive accuracy in many research but it lacks in invariance to scale and rotation. Moreover, it is observed that due its inherent design it cannot be combined with feature extraction methods to identify the banana leaf diseases. Due to this reason two alternative models that combine ANN with scale-invariant Feature transform (SIFT) model or histogram of oriented gradients (HOG) combined with local binary patterns (LBP) model are suggested. The first model ANN with SIFT identify the disease by using the activation functions to process the features extracted by the SIFT by distinguishing the complex patterns. The second integrate the combined features of HOG and LBP to identify the disease thus by representing the local pattern and gradients in an image. This paves a way for the ANN to learn and identify the banana leaf disease. Moving forward, exploring datasets in video formats for disease detection in banana leaves through tailored machine learning algorithms presents a promising avenue for research.

SOLIDWORKS™ Design, fabrication and performance analysis of a banana fiber extraction machine and its components

Banana cultivation is a prominent agricultural activity in Pakistan, particularly in the lower Sindh districts such as Tando Muhammad Khan, Hyderabad, Sanghar, and Mirpur Khas. Each banana plant bears fruit only once in its lifetime, resulting in a significant amount of waste biomass from the pseudo stems after harvest. Utilizing these waste stems can enhance environmental sustainability and increase economic benefits for farmers. Traditional methods of extracting banana Fiber are plagued by inefficiencies, including lengthy processing times and subpar Fiber quality. This study possesses the design and development of a mechanized solution to extract high quality banana Fiber efficiently. The process encompasses the selection of suitable material, detailed design, mathematical analysis, and the assembly of machine components, aiming to address the shortcomings of conventional extraction methods. The performance analysis was conducted for the machine successfully handled banana stems up to 155mm in width and 22mm in thickness, demonstrating its robust capacity and versatility in processing various sizes. The positive simulation results provide a theoretical validation of the design before physical testing, suggesting the machine components are well designed and capable of enduring typical operational stresses. This study addressed Sustainable development goal 8 Decent work and economic growth, 9 industry innovation and infrastructure, 12 Responsible consumption and production and 13 climate action.

Extension Design for Making Jackfruit Banana Flour Cookies in Tambaksari Village, Purwodadi Sub-District, Pasuruan District

Jackfruit banana in Tambaksari Village is the dominant variety with a high yield productivity of 4 tons/ha. However, the utilization of these bananas is not optimal, so an innovation was developed to utilize raw jackfruit banana fruit into jackfruit banana flour to be processed into cookies. This study aims to design extension services, analyze the increase in knowledge, and determine the level of skills and attitudes of 15 members of Women Farmers Group Sri Rejeki regarding the making of jackfruit banana flour cookies in Tambaksari Village, Purwodadi District, Pasuruan Regency from February to April 2024. The research method used a qualitative approach with a Level III action research method. The process of implementing Extension includes the stages of planning, action, observation, and reflection. Based on observations and interviews, there are significant changes in behavior supported by simple quantitative data from the results of the first evaluation, which shows an increase in knowledge from the value of increasing knowledge percentage of 59%, the level of attitude with a percentage value of 85% (responsible category), and the level of skills getting 12 skilled people. The second evaluation shows the value of increasing knowledge percentage of 60%, the level of attitude with a percentage value of 86% (responsible category), and the level of skills getting 10 skilled people. The conclusion of this research is that this extension is effective in increasing the knowledge, skill level, and attitude level of Women Farmers Group members in making jackfruit banana flour cookies.

Enhancing Shelf-Life of Banana Fruit Using Fermented Cabbage Extract

Biochemical changes along with microbial contamination may shorten the shelf life of post harvested fruits and vegetables. Generally, various physical and chemical treatments are being used to preserve the post harvested fruits. However, those treatments are hardly good for human health as well as the environment. Interestingly, lactic acid bacteria (LAB) produce antimicrobial peptides that are harmful to food spoilage bacteria and extend shelf life by killing them. Therefore, the present study is designed to investigate spontaneous fermentation by the autochthonous LAB in the cabbage leaves and the application of fermented cabbage extract to enhance the shelf-life of banana fruits. The result showed that the fermented cabbage extract was acidic (pH = 3.6 after 40 hours) in nature and increased its acidity over time. In 24 hours, 1 mgL-1 lactic acid was produced by LAB in cabbage leaves. In fermented cabbage extract, 3.85 mg per 100g vitamin-C was measured, antioxidant properties expressed by the DPPH and it was 3.02 mgml-1. Anthocyanin and flavonoids were present in cabbage extract but no tannin was observed. After 48h fermentation, the fermented cabbage extract was applied immediately to the harvested mature banana fruits. The brown surface of the banana was considered as an indicator before rotting. The brown surface in the control banana appeared on Day 7 after exposing to cabbage extract. On the other hand, such surface appeared on treated banana on Day 11. By Day 11, control banana group had already succumbed to rot. This result indicates that the treated banana took an additional 4 days to reach the state. Taken all together, it may be concluded that fermented cabbage extract possesses a promising role to extend the shelf life of banana fruits and to reduce the postharvest loss through eco-friendly natural approach without compromising quality and safety. J Bangladesh Agril Univ 22(2):241-248, 2024

A dataset of UAV multispectral images for a banana Fusarium wilt survey

Banana Fusarium wilt, also known as "banana cancer", currently poses a significant threat to banana production worldwide. Timely and accurate identification of Fusarium wilt disease is crucial for effective disease control and optimizing agricultural planting structure. To explore the use of unmanned aerial vehicle (UAV) remote sensing for identifying banana wilt disease, in this study, we obtained comprehensive experimental data on wilted banana plants in a banana plantation in Long'an County, Guangxi. The dataset includes UAV multispectral reflectance data and ground survey data on the incidence of banana wilt disease. The UAV multispectral imagery was acquired under clear, cloud-free, and well-illuminated weather conditions, at a flying altitude of 120 meters with a spatial resolution of 8 cm/pixel. The ground sample points survey on the occurrence of banana wilt disease was conducted using a high-precision handheld GPS unit to collect latitude and longitude information for each sample point, and the positions were matched with the corresponding center positions of banana plants in the UAV imagery indoors. The dataset provides high- spatial-resolution UAV multispectral imagery data and accurate ground sample point survey data. It can be applied in the research and monitoring of UAV remote sensing identification and surveillance of banana wilt disease. It plays a crucial role in advancing research and application of remote sensing monitoring for agricultural crop diseases.

Computing Edge Irregularity Strength of Star and Banana Trees Using Algorithmic Approach

After the Chartrand definition of graph labeling, since 1988 many graph families have been labeled through mathematical techniques. A basic approach in those labelings was to find a pattern among the labels and then prove them using sequences and series formulae. In 2018, Asim applied computer-based algorithms to overcome this limitation and label such families where mathematical solutions were either not available or the solution was not optimum. Asim et al. in 2018 introduced the algorithmic solution in the area of edge irregular labeling for computing a better upper-bound of the complete graph \(es(K_n)\) and a tight upper-bound for the complete \(m\)-ary tree \({es(T}_{m,h})\) using computer-based experiments. Later on, more problems like complete bipartite and circulant graphs were solved using the same technique. Algorithmic solutions opened a new horizon for researchers to customize these algorithms for other types of labeling and for more complex graphs. In this article, to compute edge irregular \(k\)-labeling of star \(S_{m,n}\) and banana tree \({BT}_{m,n}\), new algorithms are designed, and results are obtained by executing them on computers. To validate the results of computer-based experiments with mathematical theorems, inductive reasoning is adopted. Tabulated results are analyzed using the law of double inequality and it is concluded that both families of trees observe the property of edge irregularity strength and are tight for \(\left\lceil \frac{|V|}{2} \right\rceil\)-labeling.

Characterization and Conservation of Native Banana Germplasms Available in Salt Ecosystem

This study aimed to assess, conserve, and characterize banana germplasms in Bangladesh's coastal salt ecosystem, with the goal of improving cultivation resilience and sustainability under challenging environmental conditions. Thirty-five banana germplasms were subjected to in situ investigation, with 11 germplasms undergoing morphological characterization, revealing significant variations in key parameters. Additionally, 11 germplasms representing Musa species were collected for ex situ conservation at the Germplasm Center, Department of Horticulture, PSTU, with three, four, and four germplasms falling under Musa paradisiaca, Musa acuminata, and Musa sapientum, respectively. Notably, M. paradisiaca (kacha kola), M. acuminata (atia kola), and M. sapientum (table banana) exhibited promising traits in terms of morphological characteristics, total yield, and shelf-life. Among these, germplasm MP01 (M. paradisiaca), MA17 (M. acuminata), and MS09 (M. sapientum) demonstrated superior potential for maximizing production and profitability within the coastal salt ecosystem region. These findings offer valuable insights for banana cultivation in similar challenging environments, contributing to enhanced agricultural sustainability and livelihoods. J Bangladesh Agril Univ 22(2):193-201,2024

PELATIHAN PEMBUATAN PRODUK DIVERSIFIKASI PELEPAH PISANG BAGI WARGA DESA DUWET KAB.MALANG

Banana fronds or Gedebog in Javanese, banana fronds are one part of the banana tree that is rarely 'touched', even though banana fronds themselves contain many vitamins and are rich in health benefits. Therefore, it is feasible to increase the value of the product and its selling value so that it can be enjoyed by the wider community as a healthy snack product through diversification of banana fronds into banana frond chips that can be accepted by the community. Duwet Village as a good banana producing village, has not yet understood the diversification of products that can be processed from banana fronds. The methods used in this activity are a) Initiation of PPM Activity Program, b) Transfer of Knowledge, c) Discussion and Q&A, d) Problem Discussion. The training participants were mothers of Duwet villagers who were housewives, farmers, and who did not have a fixed income. The results of this activity found several obstacles that not all types of bananas, the fronds can be diversified into banana frond chips, for the process of making this product also has special criteria related to down time production time.

Effect of Hyperparameter Tuning on the Performance of YOLOv8 for Multi Crop Classification on UAV Images

This study investigates the performance of YOLOv8, a Convolutional Neural Network (CNN) architecture, for multi-crop classification in a mixed farm with Unmanned Aerial Vehicle (UAV) imageries. Emphasizing hyperparameter optimization, specifically batch size, the study’s primary objective is to refine the model’s batch size for improved accuracy and efficiency in crop detection and classification. Using the Google Colaboratory platform, the YOLOv8 model was trained over various batch sizes (10, 20, 30, 40, 50, 60, 70, 80, and 90) to automatically identify the five different classes (sugarcane, banana trees, spinach, pepper, and weeds) present on the UAV images. The performance of the model was assessed using classification accuracy, precision, and recall with the aim of identifying the optimal batch size. The results indicate a substantial improvement in classifier performance from batch sizes of 10 up to 60, while significant dips and peaks were recorded at batch sizes 70 to 90. Based on the analysis of the obtained results, Batch size 60 emerged with the best overall performance for automatic crop detection and classification. Although the F1 score was moderate, the combination of high accuracy, precision, and recall makes it the most balanced option. However, Batch Size 80 also shows very high precision (98%) and balanced recall (84%), which is suitable if the primary focus is on achieving high precision. The findings demonstrate the robustness of YOLOv8 for automatic crop identification and classification in a mixed crop farm while highlighting the significant impact of tuning to the appropriate batch size on the model’s overall performance.

Agronomic perspective: exploring the diversity and potentialities of banana cultivation (Musa spp.)

Agronomic perspective: exploring the diversity and potentialities of banana cultivation (Musa spp.)

Supplementary irrigation in banana trees Prata common in the western brazilian Amazon

Supplementary irrigation in banana trees Prata common in the western brazilian Amazon

A method for measuring banana pseudo-stem phenotypic parameters based on handheld mobile LiDAR and IMU fusion.

Diameter and height are crucial morphological parameters of banana pseudo-stems, serving as indicators of the plant's growth status. Currently, in densely cultivated banana plantations, there is a lack of applicable research methods for the scalable measurement of phenotypic parameters such as diameter and height of banana pseudo-stems. This paper introduces a handheld mobile LiDAR and Inertial Measurement Unit (IMU)-fused laser scanning system designed for measuring phenotypic parameters of banana pseudo-stems within banana orchards. To address the challenges posed by dense canopy cover in banana orchards, a distance-weighted feature extraction method is proposed. This method, coupled with Lidar-IMU integration, constructs a three-dimensional point cloud map of the banana plantation area. To overcome difficulties in segmenting individual banana plants in complex environments, a combined segmentation approach is proposed, involving Euclidean clustering, Kmeans clustering, and threshold segmentation. A sliding window recognition method is presented to determine the connection points between pseudo-stems and leaves, mitigating issues caused by crown closure and heavy leaf overlap. Experimental results in banana orchards demonstrate that, compared with manual measurements, the mean absolute errors and relative errors for banana pseudo-stem diameter and height are 0.2127 cm (4.06%) and 3.52 cm (1.91%), respectively. These findings indicate that the proposed method is suitable for scalable measurements of banana pseudo-stem diameter and height in complex, obscured environments, providing a rapid and accurate inter-orchard measurement approach for banana plantation managers.

Determination of fermentation conditions of Streptomyces sp. VNUA116 to improve the antifungal activities against Fusarium oxysporum f.sp. cubense causing Panama wilt disease on banana plants

This study aims to identify medium components (carbon source, carbon concentration, nitrogen source) and fermentation conditions (temperature, pH) to enhance the resistance against Fusarium oxysporum f. sp. cubenseTropical Race 4 (Foc Tr4), causing Panama wilt disease of Streptomyces sp. VNUA116 (VNUA116). By using the agar well diffusion method, it was determined that strain VNUA116 has strong anti-fungal pathogen activities FocTr4 under fermentation nutrients: YIM 301 medium, carbon source CB1 (soluble starch 40 g/l: D-glucose 1 g/l, and nitrogen source N1 beef extract 3 g/l: yeast extract 5 g/l: peptone 3 g/l). Additionally, optimal fermentation conditions were established, including pH 7, and temperature 30oC. Strain VNUA116 exhibited the highest antifungal activity, reaching a diameter of 30.67±0.58 mm after 10 days of cultivation. Furthermore, under these optimised fermentation conditions, Streptomycessp. VNUA116 demonstrated an impressive inhibitory capability against Foc-Tr4, reaching up to 93.20%, equivalent to the concentration of the fungicide Ridomil gold 68WG at 3 g/l in laboratory conditions. This affirms the considerable potential of the VNUA116 strain for applications in the production of biofertilizers for the biological control of Panama wilt disease in banana plants.

Valorization of unripe banana peel (Robusta) powder for the production of tannase using Bacillus xiamenensis in submerged fermentation

Tannases are industrial enzymes used in cosmetic, pharmaceutical, food, and environmental management. In the present study, 11 tannase-producing Bacillus spp. were isolated from agricultural soil, banana root soil, vegetable garbage, and fruit garbage. These isolated bacteria were screened using tannic acid agar plates. The zone of hydrolysis varied from 9 mm to 21 mm, and the strain Bacillus xiamenensis BR1 exhibited the highest activity. The dried unripe banana peel (Robusta) was powdered, and particles between 1 and 1.5 mm were used as substrate. The banana peel consists of 7.84 ± 0.15% hydrolysable tannin, which induces the production of tannase. The production medium was prepared at 10% (w/v) unripe banana peel powder. The screening experiments revealed that fermentation period, pH, inoculums, and tannic acid improved tannase production. A two-level full factorial design revealed the influence of pH, inoculums, and incubation time on tannase production (F-value=8.99; p-value=<0.0001). The optimum concentration was analyzed using a central composite design, and the model was significant (F-value = 17.03; p-value = 0.0001). Under optimal bioprocess conditions, tannase yield was 2.4-fold higher than in an unoptimized medium. The unripe banana peel can be used as a substrate for the production of tannase by Bacillus sp.

Analysis of Metoxyl and Galacturonate Contents from Pectin of Banana Peel Waste Combined with Sappan Wood

The production of banana plants (Musaceaea sp.) ranks first in agricultural output in Indonesia, but this is not balanced by the processing of waste from banana peels, which is a large amount. Therefore, an attempt is made to use banana peel waste as raw material for making pectin. Pectin is used as a functional component in the food industry because of its ability to form thin gels and stabilize proteins. Pectin is also used as a filler in the paper and textile industries, and as a thickener in the rubber industry. This research aims to determine the effect of extraction time and temperature on the quality of pectin from Kepok banana peels. The method used is extraction through Ultrasonic Assisted Solvent Extraction (UASE) in 40 kHz. Banana peels that had been dried and ground into powder were extracted with 0.1 N HCl at temperatures of 70 oC, 80 oC and 90 oC. The variables used in this extraction are variations in extraction time, namely 60 minutes and 80 minutes. The extracted solution is filtered and thickened to half the volume of the original filtrate by heating, then the pectin is thickened using acid ethanol. The pectin precipitate was washed using 96% alcohol until it was free of chloride and the precipitate was separated using a vacuum and then dried in an oven then to analysis of pectin using methoxyl and galacturonate as method to determine pectin quality form banana peel waste. The research results showed that the pectin quality was optimum at a temperature of 90 oC for 80 minutes with a methoxyl content of 4.12% (low methoxyl) and a galacturonic acid content of 79.96%.

Surface-Imprinted Polysiloxane with Recognition Ability Based on an ITO Layer for Rapid Detection of Fusarium oxysporum f. sp. cubense by the Naked Eye.

Direct observation by the naked eye of fluorescence-stained microbes adsorbed on surface imprinted polymers (SIPs) is highly challenging and limited by speed, accuracy and the semiquantitative nature of the method. In this study, we tested for the presence of spores of Fusarium oxysporum f. sp. cubense race 4 (Foc4), which cause severe banana Fusarium wilt disease and reduces the area of banana plants. This kind of spore can become dormant in soil, which means that the detection of secreted molecules (molecular imprinting) in soil may be inaccurate; detection methods such as polymerase chain reaction (PCR) and Raman spectroscopy are more accurate but time-consuming and inconvenient. Therefore, a semiquantitative and rapid SIP detection method for Foc4 was proposed. Based on the ITO conductive layer, a reusable and naked-eye-detectable Foc4-PDMS SIP film was prepared with a site density of approximately 9000 mm-2. Adsorption experiments showed that when the Foc4 spore concentration was between 104 to 107 CFU/mL, the number of Foc4 spores adsorbed and the fluorescence intensity were strongly correlated with the concentration and could be fully distinguished by the naked eye after fluorescence staining. Adsorption tests on other microbes showed that the SIP film completely recognized only the Foc series. All the results were highly consistent with the naked-eye observations after fluorescence staining, and the results of the Foc4-infected soil experiment were also close to the ideal situation. Taken together, these results showed that Foc4-PDMS SIPs have the ability to rapidly and semiquantitatively detect the concentration of Foc in soil, which can provide good support for banana cultivation. This method also has potential applications in the detection of other fungal diseases.

Nutritional and Biochemical Analysis of Locally Produced Wine from a Blend of Banana (Musa sapientum) and Date Palm Fruit (Phoenix dactylifera L.)

Background: Wine is a low-alcohol beverage made from fresh grapes or grape juice through partial or complete fermentation. Wine contains many nutrients necessary for the human body, such as sugar, vitamins, amino acids, mineral elements, polyphenols etc. Objective: This project aimed at analysing the nutritional and biochemical composition of locally produced wine from a blend of banana and dates palm fruit. The study includes determining the proximate, phytochemical, mineral, physicochemical, and amino acid profiles. Methods: The method involves heating a crucible dish to eliminate moisture, determining fat content, defatting the sample, determining ash, and determining crude protein. The phytochemical analysis includes tests for saponin, flavonoid, alkaloid, and tannin. Mineral analysis was carried using an atomic absorption spectrophotometer, while physicochemical analysis includes alcohol, pH, and temperature measurements as well as determination of amino acid profile analysis of banana-date palm wine. Results: The proximate analysis revealed high moisture content (97.87%), suggesting a good source of fruit wine production. The wine contains low crude fibre (1.01%), low crude protein (0.14%), Ash content (0.49%) and low crude lipid (0.58%). The wine also contains antioxidant and anti-inflammatory properties. Physicochemical analysis revealed an average pH of 4.62 to 4.71, with sugar concentration decreasing daily over four days and two mineral elements were reveal which are potassium and phosphorus. The amino acid profile analysis of banana-date palm wine reveals that it contains both essential and non-essential amino acids. The essential amino acids include isoleucine, methionine, histidine, and phenylalanine, non-essential amino acids include glutamic acid, asparagine, proline, and cysteine. Conclusion: The findings of this study suggest that a blend of Banana (musa sapientum) and date palm fruit (Phoenix dactyliferal) wine has a unique pleasant aroma, and may have the potential to provide both essential and non-essential amino acids, provide other nutrients that are important for normal physiological function of the body.