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Climate thresholds and yield elasticity of durian, mangosteen, and coffee under hydroclimatic variability in Thailand
(2026-08-01)
Ansari, Kutubuddin
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Tanır Kayıkçı, Emine
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Jamjareegulgarn, Punyawi
This study examines the empirical relationships between hydroclimatic variability and the yields of durian, mangosteen, and coffee across Thailand using meteorological observations from 56 stations and provincial level yield statistics for 2008 to 2024. An integrated statistical framework was applied, including exploratory correlation analysis, nonlinear quadratic additive modelling, lagged climate response analysis, elasticity estimation, model comparison, mangosteen regional sensitivity analysis, and a Climate Risk Index (CRI). The results show clear spatial gradients in temperature, humidity, and precipitation across the six agroclimatic regions of Thailand, broadly corresponding to regional crop productivity patterns. Annual anomaly analysis indicates that warm and humid years are generally associated with higher durian and mangosteen yields, whereas excessive rainfall and warming are associated with reduced coffee productivity. Pairwise linear correlations between annual climate variables and crop yields are generally weak, suggesting that simple linear models may not fully capture crop climate relationships. Nonlinear modelling indicates approximate empirical temperature turning points near 28.0°C for durian, 27.3°C for mangosteen, and 26.6°C for coffee, with humidity related turning points around 76–78%. Lagged climate response models suggest that multi-year hydroclimatic conditions may influence perennial crop productivity, particularly humidity for durian, precipitation for coffee, and temperature and precipitation for mangosteen. The mangosteen sensitivity analysis shows that humidity and precipitation thresholds are affected by regional composition, especially when marginal production regions are included. The CRI formulation under the equal weight, mangosteen shows the highest rainfall related climate risk signal, while coffee is more sensitive to temperature related risk and durian shows moderate vulnerability to prolonged humid and wet conditions.
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Identification and quantification of quality of intact durian fruits using NIR spectroscopy
(2026-01-01)
Pitak, Lakkana
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Ditcharoen, Sirirak
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Maraphum, Kanvisit
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Khamwan, Buathip
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Warorost, Nithithada
Quality classification of durian fruits is based on the dry matter (DM) content of the pulp. According to Thai agricultural standards, durian fruit (Monthong variety) must contain at least 32% DM. This study aimed to develop a classification model for assessing durian quality based on DM content, categorizing fruits as either “rejected” (DM < 32%) or “accepted” (DM ≥ 32%). Near-infrared (NIR) spectra were collected as the durian fruits moved along a conveyor belt. The models were developed using two spectral ranges: short-wavelength near-infrared (SWNIR; 4501000 nm) and long-wavelength near-infrared (LWNIR; 8601750 nm). Owing to the imbalance in the dataset between the two classes, the data were adjusted using the synthetic minority oversampling technique to create a balanced dataset. Prediction models were built using different spectral preprocessing methods and algorithms. For the LWNIR range, the models constructed using LDA, SVM, KNN, and SDA achieved accuracies of 95%, 90%, 93%, and 93%, respectively, for the test set. The SWNIR models, developed using the same algorithms, achieved accuracies of 90%, 88%, 90%, and 90%, respectively, for the test set. PLS-regression was used to predict the DM content from both LWNIR and SWNIR data. With the 2nd derivative preprocessing method, the models achieved R² values of 0.89 and 0.79, SEP values of 5% and 6.89%, and RPD values of 2.29 and 1.66, respectively. The wavelength range significantly influenced the model performance, whereas spectral pretreatment had a minor effect on the model's predictive ability. Overall, NIR spectroscopy demonstrated the potential for nondestructive quality grading of whole durian fruits. This work is the first to establish real-time, in-line models for durian grading based on DM content, advancing beyond the previous destructive method. The findings demonstrate the feasibility of automated, nondestructive, and objective quality assessment, supporting industrial automation, precision agriculture, and export quality assurance.
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Insights from dual-platform metabolomics on durian flowers: An alternative source of procyanidins from agricultural waste with bioactivities
(2025-07-01)
Potijun, Supakorn
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Pattarapipatkul, Nattaya
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Boonma, Pitchakorn
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Pewlong, Putthamas
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Pathtubtim, Intira
Procyanidins, which are polyphenol compounds in grape seeds, apples, and berries, are known for their anti-inflammatory and antioxidant properties. In this study, we investigated durian flowers, an agricultural waste, as a novel procyanidin source. Durian trees bloom prolifically, but not all flowers develop into mature fruits, representing underutilized resources. Dual-platform metabolomic analysis using ultra-high-performance liquid chromatography with electrospray ionization quadrupole time-of-flight mass spectrometry and gas chromatography–mass spectrometry annotates polyphenols such as (−)-epicatechin, procyanidins B1, B2, and C1. The 80 % (v/v) ethanol extraction yielded a crude extract with a total procyanidin content of 7.68 mg/g. Bioactivity assays revealed that the procyanidin-rich crude extract reduced oxidative stress and exhibited anti-inflammatory effects against UVA in human keratinocytes (HaCaT). This study is the first to propose durian flowers as a sustainable and cost-effective procyanidin source with potential application in the nutraceutical and cosmeceutical industries, contributing significantly to the repurposing of agricultural waste through green technology.
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Comparison of cost and return for durian farmers on Magik Growth wrapping bag innovation to increase the quality of durian production in Rayong Province, Thailand
(2025-07-01)
Thongtem, K.
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Suwanmaneepong, S.
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Suwunnamek, N.
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Kerdsriserm, C.
The results of the study revealed that farmers who did not use the Magik Growth durian wrapping bag innovation had total costs of 37,647.48 baht per rai, resulting in an average yield of 1,420.41 kilograms per rai and a net profit of 164,999.25 baht per rai. In contrast, farmers who used the Magik Growth durian wrapping innovation had total costs of 48,724.58 baht per rai, leading to an average yield of 1,420.83 kilograms per rai and a net profit of 195,068.58 baht per rai. There was a significant difference of 0.01 in the average yield between those using and not using the Magik Growth durian wrapping innovation. Fixed costs and break-even yield also showed a statistically significant difference at 0.05. However, total costs, variable costs, production factors, product prices, net profit, and prices showed no statistically significant difference.
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Deep neural networks (DNNs) chemical compositions estimation of fresh durian in-line via near infrared spectroscopy
(2025-06-01)
Posom, Jetsada
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Saenphon, Chirawan
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Ditcharoen, Sirirak
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Pitak, Lakkana
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Sirisomboon, Panmanas
Near infrared (NIR) spectroscopy and deep neural network (DNN) models were adopted for evaluating the nutritional compositions in durian pulp. The quality inspection of durians through online channels remains challenging because consumers cannot directly touch or smell the fruit. This leads to issues with substandard durians, such as unripe ones or those infested with pests. One hundred and sixty durian samples of Mon Thong varieties were used in this experiment. Then, the collected NIR spectra were augmented to improve the generalization ability of regression models. Deep neural network (DNNs) regressions were developed. The results showed that deep neural network (DNN) regression model possessed the best prediction performance, which were provided performance index. Almost all the best performance models were developed from the second derivative, except for the fat content model, which was developed from raw spectra. The best total soluble solids (TSS) model provided the coefficient of determination of calibration (R2c) and root mean square error of calibration (RMSEc) were 0.84 and 2.25 % and coefficient of determination of calibration (R2p), root mean square error of prediction (RMSEp) and ratio of performance to deviation (RPD) were 0.72 2.92 % and 1.92, respectively, and those of dry matter content (DMC) were provided R2c and RMSEc were 0.997, 0.58 %, and for prediction set provided R2p, RMSEp and RPD were 0.94, 3.13 %, and 4.21, respectively. For fat content (FC), they have also provided R2c and RMSEc were 0.84, 0.36 (g/100 g), while it provided R2p, RMSEp and RPD were 0.86, 0.50 (g/100 g), and 2.72, respectively. Moreover, for total sugar content (TSC) value, it also gave high accuracy, which provided R2c and RMSEc were 0.93, 0.49 (g/100 g) and R2p, RMSEp, and RPD were 0.91, 0.81 (g/100 g), 3.44, and for starch content (SC) also provided R2c and RMSEc were 0.93, 0.49(g/100 g) and R2p, RMSEp, and RPD were 0.76, 2.79 (g/100 g), 2.09, respectively. Therefore, the proposed method offers an ultrasensitive and effective strategy for estimation of nutritional compositions.
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Community enterprise quality management of durian exports in Ban Khao Hin Thaen, Wang Chan District, Rayong Province, Thailand
(2024-05-01)
Charoenpituk, S.
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Suwanmaneepong, S.
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Llones, C.
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Kerdsriserm, C.
Results showed that most farmers interviewed in this study (40.40%) were aged 51–60, and 43.90% had 1–10 years of durian cultivation experience. Around 82.50% of farmers possessed Good Agricultural Practices (GAP) standard certificates, indicating high compliance. The study of knowledge in durian quality management aligned with the standards of GAP. Considering the average of all eight factors, the highest accuracy rates were revealed in production process management (88.89%) and data recording (84.80%). Other factors receiving correct answer scores ranged from 60.23 to 75.44%. The levels of operation in managing durian markets across the 8Ps framework for product, personnel, process, physical characteristics, efficiency, and quality were relatively high, with an average score ranging from 3.57 to 4.39. On the other hand, the factors relating to price, distribution, and marketing promotion were relatively low, with an average score ranging from 2.87 to 3.39. The average scores for each factor relating to durian quality management for export were as follows: planning (94.04%), production operation (94.74%), and resource management (90.35%). In conclusion, the quality management, marketing, and key influencing factors of durian were carefully considered by the members of the community enterprise under study. These findings can be used to guide strategies to improve durian cultivation and marketing, ensuring high-quality products that meet export standards. To enhance durian exports, policymakers and practitioners should consider support and training in the areas where farmers face challenges.
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A rapid cotton swab for on-site screening of coloring curcumin on durian skin: food safety aspects
(2023-08-01)
Teerasong, Saowapak
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Boonyaratsewee, Phanaporn
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Aunruan, Panuwat
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Saard, Worawan
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Saetear, Phoonthawee
Exported durians from Thailand are sometimes immersed in curcumin to give the fruits a good appearance. Curcumin is regarded as non-toxic additive, however some importing countries prohibited use of any additive to fresh fruits and vegetables. This work aims to develop a rapid, low cost and convenient cotton swab device for curcumin detection. The detection principle involves a colorimetric acid–base characteristic of curcumin. Curcumin in an acidic/neutral solution presents a bright yellow color, while it displays an intense orange–red color in basic solution. A cotton swab acted for both sample collection and as a sensing platform. A pre-moistened swab was used to wipe a durian surface. Afterward, a NaOH solution was dropped onto the swab. A distinct orange–red color appearing on the swab indicates the presence of curcumin. The cotton swab was applied for qualitative analysis of curcumin contaminated on durian husks via visual detection. The developed device provided good reliability, 93.75% (36 samples). Furthermore, the device was demonstrated for quantitative determination using camera detection. Two linear calibrations were obtained in ranges of 10–75 and 75–250 mg L−1, with a detection limit of 3.2 mg L−1. The method was also successfully applied to quantification of curcumin in durians (three samples) and dietary supplements (two samples). The test can be done in a few minutes. The developed device was established as an useful tool for food safety and control of contamination by curcumin in an on-site application. Graphical abstract: [Figure not available: see fulltext.]
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Near-infrared hyperspectral imaging combined with machine learning for physicochemical-based quality evaluation of durian pulp
(2023-06-01)
Sharma, Sneha
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Sirisomboon, Panmanas
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K.C, Sumesh
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Terdwongworakul, Anupun
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Phetpan, Kittisak
This research reports on the application of near-infrared hyperspectral imaging (NIR-HSI) system for predicting the physicochemical properties; dry matter (DM), total soluble solids (TSS), and fat content (FC) of durian. Partial least squares regression (PLSR), support vector machine (SVM), random forest (RF), and 1D convolution neural network (CNN) models: custom, U-Net, and VGG19; were developed to predict DM, TSS, and FC of durian pulp. Feature wavelengths were selected using a genetic algorithm (GA) and successive projection algorithm (SPA). The selected wavelengths were then validated based on the algorithms for regression model development. GA-PLSR model was compelling to predict the DM and FC in durian pulp, which obtained the coefficient of determination for the test set (r2) and root mean square error of prediction (RMSEP) of 0.97 and 1.12% for DM and 0.86 and 0.64% for FC, respectively. The GA-PLSR model provided the best result for the TSS prediction with r2, and RMSEP of 0.90 and 1.40%, respectively, whereas the SPA-PLSR model based on only thirteen wavelengths attained fair result with the r2 and RMSEP of 0.79 and 2.03%, respectively. The above results show that the pushbroom NIR-HSI system achieved promising results for estimating DM, TSS, and FC in durian pulp. This research identified the featured wavelengths that can be used to develop a portable and reliable HSI or multispectral system to be installed at durian packaging firms for quality inspection and grading.
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Nanoparticles Derived from Active Metabolites of Chaetomium cupreum CC3003 against Phytophthora Rot of Durian
(2022-01-01)
Tongon, Rujira
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Soytong, Kasem
Phytophthora rot of durian (Durio zibetinus L.) is a serious disease wherever the crop has been planted and the disease control customarily uses chemical fungicides reported to be resistant by pathogen. Alternative non-chemical control strategies are being investigated to produce safe food. The main objective of this research was to test the activity of metabolites from Chaetomium cupreum CC3003 in the form of crude materials and nanoparticles to control and induce immunity to Phytophthora palmivora causing rot of durian var. Monthong. The results showed that P. palmivora proved to be pathogenic to durian var. Monthong. C. cupreum CC3003 acted as an antagonist and P. palmivora was confirmed as the pathogen by morphological and molecular genetic identification. Effective doses (ED50) of CC-E, CC-H and CC-M crude metabolites for spore inhibition were 60, 97 and 140 mg.kg-1, respectively. The research findings found that the diameters of nano CC-E, nano CC-H and nano CC-M were 534, 499 and 537 nm, respectively. The nano CC-E, nano CC-H and nano CC-M demonstrated antifungal activity against P. palmivora with ED50 of 11, 13 and 16 mg.kg-1, respectively. The nanoparticles at low concentrations were more effective than crude metabolites at high concentrations. Nano-CC-E used to treat seedlings of durian resulted in the production of scopoletin which served as an immunity agent or elicitor against rot disease of durian. It is concluded that active metabolites derived from C. cupreum significantly inhibited P. palmivora and induced immunity through phytoalexin production
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Properties of different varieties of durian
(2021-06-02)
Arsa, Supeeraya
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Wipatanawin, Angkana
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Suwapanich, Rachit
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Makkerdchoo, Orachorn
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Chatsuwan, Niphattha
Durian (Durio zibethinus Murr.), like many other exotic, tropical, and conventional fruits, is important in the prevention of different diseases. In this study, the characterization of the main bioactive compounds of the most popular cultivars of durian and their properties are described. The changes in the quality indices of the antioxidant status were determined by CUPRAC, ABTS, FRAP, DPPH, and ORAC assays. The profiling of phytochemicals was carried out by Fourier transform infrared (FTIR) spectroscopy and differential scanning calorimetry (DSC). For the first time, in vitro studies were performed by the interaction of extracted durian polyphenols with human serum proteins (HSP) such as human serum albumin (HSAlb), fibrinogen (HSFib) and globulin (HSGlo) as novel biomarkers of coronary artery disease (CAD). The fluorescence measurements of the resulting intensity and calculated binding properties of the interaction of polyphenols with proteins showed that the most reactive was Monthong durian cultivar. This study suggests that durian cultivars have relatively strong antioxidant, binding, and health potentials and could be a significant source of natural antioxidants used in daily fresh consumption and for functional foods.

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