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Dataset of air cargo supply chain conditions and fruit quality evolution: Case study of mango shipment from Thailand to France
(2025-08-01)
Paviet-Salomon, Y.
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Laguerre, O.
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Duret, S.
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Denis, A.
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Mawilai, P.
This study presents a detailed dataset collected during the international transport of mangoes (Mangifera indica L. cv. ‘Nam Dok Mai Si-Thong’) within a fully loaded Unit Load Device (ULD). The ULD contained 148 boxes (14 mangoes/box) and 31 boxes were instrumented by data loggers to monitor air and mango temperatures, as well as air humidity along the shipment. Measurements were recorded every 5 min throughout the 86.2 hour journey from Bangkok (Thailand) to Paris (France), it included cold storage, refrigerated transport, airport warehouse, air transport, and final delivery to the FRISE-INRAE laboratory in Paris suburban. At reception (Day 3), all boxes were stored at two temperatures (16 °C and 21 °C) over 15 days during which mango quality was assessed. Key quality attributes such as mass loss, peel color, pH, sugar content, and visual appearance were evaluated at Day 3, Day 6, Day 9, and Day 15 to highlight the impact of storage conditions on fruit quality. It is to be noticed that the same quality assessment was undertaken after harvest and before the cold storage in Thailand (Day 0). The dataset comprises raw and processed data files that include the temperature and humidity changes over time, as well as the quality evolution. These data are stored in series of txt files, with raw values and processed results i.e. min, max, average values, standard deviation and variance to facilitate future analysis. Additionally, the dataset includes series of jpeg files of mango images at different assessment days. This dataset is valuable for both practical and research purposes. For fruit exporters, it offers the insights into how different positions within a ULD can affect mango quality during a long-distance transport and implements certain measures to minimize quality degradation. For researchers, the dataset provides a base for numerical models validation, such as simplified thermal models and Computational Fluid Dynamics simulations. The international supply chain dataset is rare because of the complexity and the cost of implementation.
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Experimental study of air cargo temperature variations and its impact on mango quality
(2024-04-01)
Chaomuang, N.
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Laguerre, O.
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Denis, A.
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Paviet Salomon, Y.
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Mawilai, P.
An air cargo supply chain for fresh mango was investigated from Thailand to France. Measurements of air temperature, air relative humidity, and fruit (peel) temperature were conducted using thermo-hygrometer data loggers in cartons. In a Unit Load Device (ULD) containing 148 cartons, twenty-seven instrumented cartons were placed at different positions to observe spatial and temporal temperature variations during 12 h cruising. At the destination, mango quality attributes were assessed at different time-points during 15-day storage at 16.1 °C and 21.6 °C. Throughout the supply chain, fruit temperatures ranged from 16.6 °C to 30.5 °C. During cruising, fruit temperatures in upper cartons remained almost constant, whereas base carton temperatures continuously decreased from 26.1 °C to 18.1 °C. Because of a short cruising period in comparison to a storage duration at the destination and proper ambient temperature condition during the experiment, carton position in the ULD had no discernible impact on fruit quality during storage. Fruit stored at 16.1 °C preserved superior fruit quality compared to 21.6 °C storage. For the same storage temperature, better quality of fruits stored in Thailand demonstrated the impact of air shipment on product degradation. The measured temperature and relative humidity evolutions were used as input parameters of a mass loss evolution model. A comparison with the measured data exhibited good agreement (RMSE < 1.8 % mass loss). Considering 10 % mass loss as a critical value, this model allows an estimation of the product shelf life based on a supply chain scenario.
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Influence of long-distance air transport conditions on horticultural product quality: Case study of fresh mango shipment from Thailand to France
(2023-08-01)
Laguerre, O.
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Duret, S.
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Chaomuang, N.
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Denis, A.
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Derens-Bertheau, E.
Four instrumented boxes of mangoes Mangifera indica L. cv. “Nam Dok Mai” were shipped from Bangkok, Thailand, to Paris, France, without control of the boxes’ positions on the aircraft. Two boxes were shipped via a direct flight and two boxes were shipped via an indirect flight. For each box, the internal air temperature, the external air temperature and relative humidity and surface temperature of two fruits were recorded throughout the supply chain from a packing house in Thailand to a storage room in France. A maximum fruit temperature of 33 °C (during transport from an orchard to the packing house) and a minimum fruit temperature of 8 °C (in a cold room of the logistics company following arrival at the airport in France via the indirect flight) were observed. The slight temperature difference between the air and the fruit surface temperature (< 1 °C on average) for both direct and indirect flights suggests that the air was stagnant inside the box and, thus conduction was the main heat transfer mode. Models of product temperature, mass loss, and peel color changes throughout the supply chain were developed. The numerical and the experimental values were in good agreement. These models were able to predict the product mass loss and peel color evolution as a function of a supply chain scenario.
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Precision test for scanning of soil in durian orchard using near-infrared spectroscopy
(2019-09-09)
Phanomsophon, T.
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Sirisomboon, P.
Near infrared (NIR) spectroscopy is a rapid technique for non destructive testing. Durian is popular fruit in Thailand. Growing durian is not easy. It needs to provide proper nutrients. Therefore, this paper aims to test the repeatability and reproducibility of NIR scanning before conducting the feasibility test of creating the equation to predict the N P K value in the soil for the durian trees. Results showed that the repeatability of FT-NIR spectrometer and Micro-NIR spectrometer for fresh soil were 0.064 and 0.075, respectively and for soil powder, they were 0.039 and 0.048, respectively. The reproducibility of FT-NIR spectrometer and Micro-NIR spectrometer for fresh soil were 0.048 and 0.051, respectively and for soil powder were 0.051 and 0.046, respectively.
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Evaluation of pH of curry soup containing coconut milk by near infrared spectroscopy
(2019-09-09)
Thitibunjan, N.
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Sirisomboon, P.
The pH is the important parameters to characterize the food deterioration and an indicative of food spoilage. The aim of this research was to apply the near infrared (NIR) spectroscopy to evaluate pH of curry soup containing coconut milk. The soup samples from mixing tank, water content adjusted tank, UHT pipe and laminated containers in the production line were collected. There were also the pH adjusted samples where the curry was made from the same recipe but increasing placed time for 2, 4 and 6 hr after 0 hr. There are 73 samples in total. The sample was scanned with FT-NIR spectrometer. A prediction model for pH was established using NIR spectral data in conjunction with partial least squares regression, which was validated using leave one out cross validation and test set validation. After validated by unknown samples, the leave one out cross validation model showed better prediction performance. The best model developed using first derivative spectra in 9403.8-7498.3, 6102-5446.3 and 4605.4-4242.9 cm-1 provided an coefficient of determination (r2), root mean square error of cross validation (RMSECV), bias and ratio of performance to interquartile (RPIQ) of 0.73, 0.28, 0.01 and 1.89. The model was usable for screening and some other "approximate" calibrations. The model could be improved for further development of robust model using more natural samples in evaluation of pH in the curry soup
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Near infrared scanning precision analysis for intact durian fruits (cv. Chanee, Kanyao and Monthong)
(2019-09-09)
Chanachot, K.
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Saechua, W.
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Sirisomboon, P.
In order to develop a model of near infrared (NIR) spectroscopy, it is important to first perform the precision analysis of scanning of the NIR spectrometer. Therefore, it was the main aim of this paper by evaluating the scanning repeatability and reproducibility on intact durian fruit of 3 varieties including Chanee, Kanyao and Monthong using 3 spectrometers including FT-NIR spectrometer (MPA.), Long wavelength diode array spectrometer (MICRO NIR PRO) and Short wavelength diode array spectrometer (FQA NIR GUN). Results show that the lowest repeatability was of MPA for the scanning of Chanee and Kanyao. The lowest reproducibility was of the scanning by MICRO NIR PRO for all varieties. Therefore, from precision analysis of intact durian scanning, the MPA and MICRO NIR PRO could be recommended for the scanning to get the spectra for development the NIR predictive model for identify the geographic origin and variety of the durian.
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Precision test for the spectral characteristic of FT-NIR for the measurement of water content of wheat straw
(2019-09-09)
Fonseca, F. G.
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Funke, A.
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Saechua, W.
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Sirisomboon, P.
Near Infrared (NIR) Spectroscopy is widely employed as a rapid technique for the evaluation of properties of biomass materials. Precision and accuracy of the instruments is an important aspect in order to minimize error in the determination of results. The objective of this publication is to determine scanning repeatability and reproducibility of the NIR spectrometer for wheat straw (Triticum aestivum L.), using either a fixed scan or a rotating scan. The former presented marginally better repeatability but worse reproducibility. Samples in equilibrium with the local atmosphere versus samples of controlled and different moisture contents were also compared, and the latter performed better on the precision test but both fixed and rotating scans. As the ultimate objective of this test is the use of this method to determine variations between different moisture content, and as the rotating scan presents better reproducibility, this method was selected as the reference method for further NIR analyses focused on the variation of moisture content.
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Potential of near infrared spectroscopy as a rapid method to detect aflatoxins in brown rice
(2019-06-01)
Dachoupakan Sirisomboon, C.
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Wongthip, P.
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Sirisomboon, P.
Brown rice is a main popular health food with high nutritional value and health benefits. As a result of poor post-harvest drying and inappropriate storage conditions, rice grains are often damaged through fungal spoilage as well as mycotoxin production. The objective of this research was to evaluate the possibility of using the near infrared spectroscopy, with a wavenumber range between 12500 and 4000 cm−1 (800–2500 nm), as a rapid method for detection of aflatoxins in brown rice. Firstly, storage trials were carried out to generate representative of samples contaminated and non-contaminated with aflatoxins. These data were used to create a partial least squares regression model using 120 brown rice samples with the required near infrared spectral data and aflatoxin concentration levels that were determined using a standard enzyme-linked immunosorbent assays method. The accuracy of developed models was externally validated using the test set. The statistical model developed from the treated spectra (vector normalization; SNV) provided the best accuracy in prediction with a coefficient of determination of prediction (r2) of 0.95, a root mean square error of prediction of 415.00 µg kg−1 and a bias −54.00 µg kg−1. The model developed showed good predictive performance which suggests that it could have practical applications as a rapid method to detect aflatoxins in brown rice.
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Shortwave near-infrared spectroscopy for rapid detection of aflatoxin B1 contamination in polished rice
(2019-01-01)
Putthang, R.
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Sirisomboon, P.
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Sirisomboon, C. Dachoupakan
The objective of this research was to apply near-infrared spectroscopy, with a short-wavelength range of 950 to 1,650 nm, for the rapid detection of aflatoxin B<inf>1</inf> (AFB<inf>1</inf>) contamination in polished rice samples. Spectra were obtained by reflection mode for 105 rice samples: 90 samples naturally contaminated with AFB<inf>1</inf> and 15 samples artificially contaminated with AFB<inf>1</inf>. Quantitative calibration models to detect AFB<inf>1</inf> were developed using the original and pretreated absorbance spectra in conjunction with partial least squares regression with prediction testing and full cross-validation. The statistical model from the external validation process developed from the treated spectra (standard normal variate and detrending) was most accurate for prediction, with a correlation coefficient (r) of 0.952, a standard error of prediction of 3.362 µg/kg, and a bias of-0.778 µg/kg. The most predictive models according to full cross-validation were developed from the multiplicative scatter correction pretreated spectra (r = 0.967, root mean square error in cross-validation [RMSECV] = 2.689 µg/kg, bias = 0.015 µg/kg) and standard normal variate pretreated spectra (r = 0.966, RMSECV = 2.691 µg/kg, bias = 0.008 µg/kg). A classification-based partial least squares discriminant analysis model of AFB<inf>1</inf> contamination classified the samples with 90% accuracy. The results indicate that the near-infrared spectroscopy technique is potentially useful for screening polished rice samples for AFB<inf>1</inf> contamination. HIGHLIGHTS • Shortwave near-infrared spectroscopy allowed rapid detection of AFB<inf>1</inf> in polished rice. • The partial least squares model provided the best accuracy for prediction (r = 0.967). • The partial least squares discriminant analysis model had a classification accuracy of 90%.
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Determination of the gamma-aminobutyric acid content of germinated brown rice by near infrared spectroscopy
(2014-01-01)
Kaewsorn, K.
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Sirisomboon, P.
Rice rich in gamma-aminobutyric acid (GABA) has been increasing in popularity worldwide, particularly within the commercially important health food market. The aim of this research was to develop a near infrared (NIR) spectroscopic method to evaluate the GABA content of germinated brown rice. Germinated brown rice (GBR) from two groups was used in this study. The first group contained GABA adjusted rice samples produced from germinated rough rice, which had been soaked for 24 h and 48 h and then incubated for 0 h, 6 h, 12 h, 18 h, 24 h, 30 h and 36 h (GBR samples). The second group was the GBR purchased from local markets (MGBR samples). The GABA content of each sample was subsequently determined by high performance liquid chromatography (HPLC). A prediction model for the GABA content was subsequently established using the NIR spectral data in conjunction with partial least square regression (PLSR), which was validated using test set validation. There were three optimal models obtained from GBR samples, MGBR-Khao Dawk Mali 105 samples and MGBR-various varieties. The first model was established using spectral data pre-treated with first derivative + multiple scatter correction and the second and third models were from first derivative + vector normalisation pre-treated spectra. The coefficient of determination (r2), root mean squared error of prediction (RMSEP) and a bias of 0.97-0.98 mg, 0.21-0.52 mg per 100 g dry matter and -0.285-0.067 mg per 100 g dry matter, respectively, were obtained. This is the first report on the application of NIR spectroscopy to evaluate the GABA content of the germinated brown rice, which could prove useful in an industrial applications and consumers. © IM Publications LLP 2014.

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