KMITL

Permanent URI for this communityhttps://dspace.kmitl.ac.th/handle/123456789/1

Browse

Search Results

Now showing 1 - 6 of 6

Some of the metrics are blocked by your
consent settings
The efficacy of natural preservatives in extending the vase life of cut flowers
(2026-01-01)
Bhandari, Nirajan
;
Pun, Umed Kumar
;
Panth, Milan
The cut flower business has been growing rapidly worldwide, with a positive and significant impact on the economies of many countries. Maintaining quality and extending the vase life of cut flowers are crucial aspects of the floral industry. Synthetic preservatives (silver nitrate, silver thiosulfate, nano-silver, hydroxy quinoline, thiabendazole, and aluminum compounds) have been commercially used in the vase to maintain the quality and longevity of cut flowers for a long time. However, these preservatives may persist in the environment, causing severe health hazards and environmental pollution, and are also expensive. Therefore, cut flower industries seek low-cost, eco-friendly, and safer alternatives. In this context, natural preservatives (NPs), including plant extracts (PEs) and essential oils (EOs), offer a promising and sustainable alternative to synthetic preservatives in the vase. This review highlights the potential NPs and their role in enhancing the quality and vase life of cut flowers. We discussed how these preservatives exert their beneficial effects, such as inhibiting microbial growth, reducing ethylene production, and enhancing water uptake, and also explored the potential issues associated with them. We conducted a structured literature review and summarized the most commonly used EOs and PEs, their optimal dosages, efficacy, and combinations, and concluded with future directions to enhance the vase life of cut flowers sustainably.
Some of the metrics are blocked by your
consent settings
Moisture content prediction in durian husk biomass via near infrared spectroscopy coupled with aquaphotomics and explainable machine learning
(2025-12-15)
Shrestha, Zenisha
;
Shrestha, Bijendra
;
Sirisomboon, Panmanas
;
Pun, Umed Kumar
;
Bajracharya, Tri Ratna
Accurate determination of moisture content is essential for energy efficiency and biomass management for fuel materials such as durian husk. Traditional methods of determining biomass moisture content are time-consuming and require specialized expertise, posing challenges for continuous monitoring. To address this limitation, this study applies Near Infrared Spectroscopy (NIRS) combined with machine learning models to rapidly and accurately assess moisture content. Both linear Partial Least Squares Regression (PLSR) and non-linear approaches were used, including Support Vector Machines (SVM), Artificial Neural Networks (ANN), and Extreme Gradient Boosting (XGB). The application of preprocessing techniques, notably the Savitzky-Golay second derivative (SD) and Standard Normal Variate (SNV), significantly augmented the predictive performance, highlighting the importance of data preprocessing in spectral analysis. Synthetic spectral augmentation using Gaussian noise revealed that while SVM and ANN exhibited near-perfect performance, SVM demonstrated quantifiable reliability. This study also demonstrates SVM as the most sensitive and reliable method for detecting and quantifying moisture content in durian husk. This research contributes novel insights to biomass analysis, highlighting the benefits of integrating NIRS and feasibility of explainable machine learning techniques to identify water related spectral parameters to advance aquaphotomics, thereby advancing rapid and accurate biomass characterization.
Some of the metrics are blocked by your
consent settings
Implementation of LoRa-Based Remote Monitoring System for Precision Mango Farming
(2025-11-13)
Wongrujira, Krit
;
Pun, Umed Kumar
;
Rakmae, Samak
This study investigated the effectiveness of a LoRa-based remote monitoring system for enhancing precision mango farming. The main objective was to evaluate how real-time environmental data collected from soil. air. and light sensors can support improved cultivation practices. A sensor network was deployed in a commercial mango orchard in Chachoengsao. Thailand, focusing on two areas: one managed with good agricultural practices, and the other with conventional methods. Ten mango trees were randomly selected from these areas for sensor installation to monitor environmental conditions. Data were collected hourly from July 2023 to April 2024. transmitted to a cloud-based MQTT broker, and visualized using a web dashboard. The study hypothesizes that sensor-guided interventions, such as optimized irrigation and pruning, lead to better environmental conditions and higher fruit yield. The results confirmed that trees under good practices, where the soil effectively retained rainwater, showed higher moisture retention. In contrast, some trees subjected to conventional practices exhibited lower retention rates. These findings support the potential of IoT-based LoRa systems to enable data-driven sustainable mango cultivation.
Some of the metrics are blocked by your
consent settings
Golden Ratio-Based Assessment of Nam Dok Mai Mango Shape Using Image Processing
(2025-11-13)
Wongrujira, Krit
;
Pun, Umed Kumar
;
Pornchaloempong, Samak
This study presents an application of the golden ratio (<p - 1.618) to evaluate the shape aesthetics of the Nam Dok Mai mango variety. Mango shape plays a critical role in determining both market value and consumer preferences. However, the assessment of visually appealing mango shapes based on human perception is inherently subjective and susceptible to inconsistencies. To address this, the proposed model utilizes one-dimensional (ID) top-view images processed using automated image analysis techniques, including segmentation, contour detection, and feature extraction. Four geometric components (G1, G2, G3, and G4) were derived from the images and statistically analyzed. The results revealed that the computed ratios closely aligned with the golden ratio. The experiment was conducted using a dataset of 100 Nam Dok Mai mangoes. The shapes perceived as visually desirable by the human evaluators corresponded closely with those identified by the model as exhibiting golden ratio proportions. Furthermore, for each mango, consistent values of G1 through G4 were obtained from both the top A and top B views, confirming the model's repeatability across symmetrical perspectives. This study demonstrates the potential of incorporating mathematical aesthetics, specifically the golden ratio, into agricultural quality assessment frameworks to enhance objectivity and standardization in fruit grading.
Some of the metrics are blocked by your
consent settings
Mangosteen Pericarp Processing Technology to Create Economic Value and Reduce Biowaste
(2024-07-01)
Soontornwat, Alisa
;
Pongsuttiyakorn, Thadchapong
;
Rakmae, Samak
;
Sritham, Eakasit
;
Sirisomboon, Panmanas
This research comparatively investigates different mangosteen pericarp processing schemes. The experimental pericarp processing schemes were hot air drying (HAD; control), quick freezing/HAD (QF + HAD), slow freezing/HAD (SF + HAD), and slow freezing/freeze-drying (SF + FD). For freezing, the QF temperature was −38 °C for 2 h and that of SF was −25 °C for 2 weeks. For drying, the HAD temperature was 60 °C for 7 h. In the FD process, the primary and secondary temperatures were −20 °C and 50 °C for 48 h. The experimental results showed that the freezing method (i.e., QF and SF) affected the physical properties (moisture content, water activity, and color) of dried mangosteen pericarp. The antioxidant activities (DPPH and ABTS) of the SF + HAD scheme (28.20 and 26.86 mg Trolox/g DW of mangosteen pericarp) were lower than the SF + FD scheme (40.68 and 41.20 mg Trolox/g DW of mangosteen pericarp). The α-mangostin contents were 82.3 and 78.9 mg/g DW of mangosteen pericarp for FD and HAD, respectively; and the corresponding TPC were 1065.57 and 783.24 mg GAE/g DW of mangosteen pericarp. The results of this study suggest that the drying process had a negligible effect on bioactive compounds. Essentially, the SF + HAD technology is the most operationally and economically viable scheme to process mangosteen pericarp.
Some of the metrics are blocked by your
consent settings
Temperature Difference in Loading Area (Tarmac) during Handling of Air Freight Operations and Distance of Production Area Affects Quality of Fresh Mango Fruits (Mangifera indica L. ‘Nam Dok Mai Si Thong’)
(2022-11-01)
Srisawat, Kraisuwit
;
Sirisomboon, Panmanas
;
Pun, Umed Kumar
;
Krusong, Warawut
;
Rakmae, Samak
Mango (Mangifera indica L.) ‘Nam Dok Mai Si Thong’ is an important cultivar for export from Thailand. Export mainly takes place via air transport, but for about 2 h at the loading area (tarmac), unit loading devices (ULDs) are exposed to ambient environmental conditions. In this research, the effects of different temperature conditions at the loading area (tarmac) and the distance of the production area from the tarmac on the quality of fresh mango fruits were studied. The treatments included three temperature conditions for 2 h (simulated handling in tarmac)—constant temperature (20 °C), non-insulated or insulated and exposed to sun—and two distances of the tarmac from the production area—short distance (i.e., transport occurring 53 h after harvest) and long distance (i.e., transport occurring 70 h after harvest). The temperature variation in the boxes exposed to the sun was greater in the non-insulated than in the insulated boxes, but this effect was more pronounced in fruit from the short-distance production area (28.1 °C insulated and 36.9 °C non-insulated) than in fruit from the long-distance production area (34.2 °C insulated and 38 °C non-insulated). Insulation and short distance increased the shelf life, decreased weight loss, delayed the decrease in average firmness and rupture force, etc. The insulation of mango fruit boxes mitigates the deleterious effect of exposure to 2 h of direct sun by reducing the increase in temperature, thus improving the shelf life and quality of mango fruit.

KMITL

Browse

Filters

Settings

Sort By

Results per page

Search Results