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[IEEE 2019 6th International Conference on Instrumentation, Control, and Automation (ICA) - Bandung, Indonesia (2019.7.31-2019.8.2)] 2019 6th International Conference on Instrumentation, Control, and Automation (ICA) - Moisture Content Prediction System of Dried Sea Cucumber (Beche-de-mer) Based on Visual Near-Infrared Imaging
摘要： Dried sea cucumber (Beche-de-mer), the product after cleaning, boiling, salting, and drying, is as delicious and healthy food. Dried sea cucumber (Beche-de-mer) also has a high market price and the highest nutritional value of all seafood products. Moisture content in dried sea cucumber (Beche-de-mer) can affect the international market prices of dried sea cucumber to decline. This condition takes place because the moisture content is one of the parameters that determine the quality of dried sea cucumber. Therefore, this research will discuss a prediction system for measuring moisture content in dried sea cucumber (Beche-de-mer) using hyperspectral imaging technique. This system uses reflectance mode with the wavelength from 400 to 1000 nm. The hardware from the prediction system for measuring moisture content is motors to generate, hyperspectral camera system, two 150 W halogen lamps, Teflon table, and personal computer link. Then, the PLSR algorithm is applied to the prediction system model at full wavelength. The prediction model is used to obtain the predicted value of moisture content. Then the results of the prediction model are compared with the data references obtained by the gravimetric method. The root means square errors and correlation coefficient are used to evaluate the prediction system performance of moisture content prediction. The best result of the prediction system in this work is to have a correlation coefficient of 0.99 and root mean square errors of 0.92% respectively, with the number of PLS component is 30. Based on the results of this research, the proposed system can be used as an alternative method of measuring the moisture content in dried sea cucumber (Beche-de-mer) with excellent accuracy and high reliability
关键词： Hyperspectral Imaging,Moisture content,Partial Least Square Regression,Dried Sea Cucumber (Beche-de-mer)
更新于2025-09-11 14:15:04
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[IEEE 2018 7th International Conference on Agro-geoinformatics (Agro-geoinformatics) - Hangzhou (2018.8.6-2018.8.9)] 2018 7th International Conference on Agro-geoinformatics (Agro-geoinformatics) - Hyperspectral Inversion of Soil Moisture Content Based on SOILSPECT Model
摘要： Soil moisture content (SMC) is the important information for the crop land irrigation management and drought warning. The study of SMC quantitative inversion based on hyperspectral remote sensing technology has become the hot spot. Because of using statistical modeling methods and without considering soil bidirectional reflection characteristics, the SMC inversion accuracy and model applicable scope were limited. The purpose of this study was to use the soil radiation transfer model (SOILSPECT) to invert SMC in order to not only improve the SMC hyperspectral inversion accuracy, but also make the model applying widely. Taking the black soil and chernozem in Gongzhuling city of Jilin province as the study object, spectrometry measurement for different SMC from 5% to 45% (5% interval) to get measured soil reflectance by using the ASD Fieldspec Pro spectrometer under the indoor condition. The influences of the light source zenith angle, observing zenith angle, azimuth angle and SMC on soil bidirectional reflectance analyzed. Then distribution SOILSPECT model parameters were obtained by using Particle Swarm Optimization (PSO) method under the different SMC gradients, and SMC inversion by using SOILSPECT model was conducted. The results showed that soil BRDF declined with SMC rising in the range of 400~1400 nm wavelength, when SMC was less than the field water holding capacity, and soil BRDF rose with SMC rising when SMC was larger than the field water holding capacity. In the range of 1400~2400nm wavelength and under different observing zenith angles, there was no rules for soil BRDF changing. SMC inversion accuracy based on SOILSPECT model was higher. R2 value was above 0.98 compared the estimated values with the measured values. The inversion accuracy for 15% and 30% of SMC were higher at every sensitive band, but that for other SMC was unsteadiness. SMC inversion accuracy based on SOILSPECT model increased with the decreasing of the observational zenith angle. The vertical observation can get the highest SMC inversion accuracy.
关键词： BRDF,SOILSPECT model,hyperspectral inversion,soil moisture content
更新于2025-09-11 14:15:04
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Quantitative detection of moisture content in rice seeds based on hyperspectral technique
摘要： To explore the best method for quantitative detection of moisture content in rice seeds, the total of 120 samples of rice seeds with different moisture content were studied by hyperspectral technique in the experiment. Sensitive wavelengths of moisture were firstly selected by calculating the migration rate, after that successive projections algorithm (SPA) was used to select characteristic wavelengths. The clustering method was proposed to increase the ability of prediction model by increasing the discrimination of hyperspectral eigenvalues of each sample group. Firstly, fuzzy C-mean clustering (FCM) algorithm was applied to cluster the characteristic wavelengths selected by SPA. Then the prediction model was established by support vector regression (SVR). Due to the unsatisfied clustering effect, simulated annealing genetic algorithm (SAGA) was introduced for clustering. By comparing the results based on original eigenvalues, FCM and SAGA clustering, respectively, it was found that the best method was SAGA. The SAGA-SVR mode achieved the value with R2 p of .8892 and RMSEP of 0.0296. The relaxation variable was introduced to reduce interval threshold because the R2 p was not ideal, and the final value achieved with R2 p of .9318 and RMSEP of 0.0264. It was proved that the SAGA-SVR model can be used for moisture detection of rice seeds.
关键词： moisture content,quantitative detection,rice seeds,SAGA-SVR model,hyperspectral technique
更新于2025-09-11 14:15:04
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[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia, Spain (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Geophysical Relationship between Cygnss GNSS-R Bistatic Reflectivity and Smap Microwave Radiometry Brightness Temperature Over Land Surfaces
摘要： This work presents an assessment on the correlation between CyGNSS-derived Global Navigation Satellite Systems Reflectometry (GNSS-R) bistatic reflectivity rl? and SMAP-derived brightness temperature BT, over land surfaces. This parametric-study is performed as a function of Soil Moisture Content (SMC), and vegetation opacity τ. Several target areas are selected to evaluate potential differentiated geophysical effects on “active” (as many transmitters as navigation satellites are in view), and passive approaches. Although microwave radiometry has potentially a better sensitivity to SMC, the spatial resolution is poor ~ 40 km. On the other hand, GNSS-R bistatic coherent radar footprint is limited by half of the first Fresnel zone which provides about ~ 150 m of spatial resolution (depending on the geometry). The synergetic combination of both techniques could provide advantages with respect to active monostatic Synthetic Aperture Radar (SAR).
关键词： vegetation opacity,CyGNSS,GNSS-R,land,microwave radiometry,SMAP,multi-static radar,Soil Moisture Content (SMC)
更新于2025-09-10 09:29:36
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Near-Infrared (NIR) Spectrometry as a Fast and Reliable Tool for Fat and Moisture Analyses in Olives
摘要： The evaluation of fat and moisture contents for olive fruits is crucial for both olive growers and olive oil processors. Reference methods, such as Soxhlet extraction, used for fat content determination in olive fruits are time- and solvent- consuming and labor intensive. Near-infrared (NIR) spectroscopy is proposed as a solution toward rapid and nondestructive analyses of olive fruit fat and moisture contents. In the present work, comparative studies of the fat and moisture quantification methods were performed on four cultivars (Arbosana, Arbequina, Chiquitita, and Koroneiki) during six different harvesting time points to determine the potential of NIR as an alternative methodology. The impact of olive paste crushing degree on NIR performance was also investigated using three different grid sizes (4, 6, and 8 mm) on a hammer mill, in addition to a blade crusher. Results indicate a satisfactory correlation between the reference Soxhlet and NIR methods with R2 = 0.995. A comparison study of moisture content was also done on NIR and the use of conventional oven with the R2 value of 0.995. The crushing blade produced higher values in both moisture and fat contents in comparison to the hammer mill. The evaluation indicates that when building a chemometric model, all crush sizes and blade sizes should be represented in the model for highest accuracy.
关键词： Soxhlet extraction,Near-infrared (NIR) spectroscopy,moisture content,olive fruit,fat content,chemometric model
更新于2025-09-04 15:30:14