Prediksi Indeks Panen Jambu “Kristal” secara Non Destruktif Menggunakan Portable Near Infrared Spectrometer

“Crystal” guava (Psidium guajava L.) is a climacteric fruit that is generally harvested by farmers based on cultivation experience. In this study, portable 740-1070 nm of near-infrared spectrometer was employed to rapidly predict harvest indices of “crystal” guava, by means of non-contact and non-destructive approach. Samples of guava fruit were collected at days after anthesis (DAS) of 91, 94, 97, and 100. The total number of each sample were 30 fruits. The firmness, soluble solid content, acidity and sugar acid ration were evaluated as quality parameters. Partial least square (PLS) method was utilized for data processing. It was found that Standard Normal Variate (SNV) resulted the best pre-processing for all quality parameters. Performances of best models were demonstrated by coefficient of corraltion (R), standard error of calibration (SEC) and standard error of prediction (SEP), which were respectively 0.88, 6.21, 5.92 for firmness prediction, 0.74, 0.84, 0.79 for soluble solid content prediction, 0.59, 0.19, 0.26 for acidity prediction, and 0.71, 1.21, 1.58 for sugar acid ratio prediction model.

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Hyperspectral Imaging for Predicting Soluble Solid Content of Starfruit

Jurnal Teknologi ◽

10.11113/jt.v73.3480 ◽

2015 ◽

Vol 73 (1) ◽

Cited By ~ 1

Author(s):

Feri Candra ◽

Syed Abd. Rahman Abu Bakar

Keyword(s):

Hyperspectral Imaging ◽

Near Infrared ◽

Imaging System ◽

Solid Content ◽

Partial Least Square ◽

Least Square ◽

Coefficient Of Determination ◽

Soluble Solid Content ◽

Calibration Model ◽

Soluble Solid

Hyperspectral imaging technology is a powerful tool for non-destructive quality assessment of fruits. The objective of this research was to develop novel calibration model based on hyperspectral imaging to estimate soluble solid content (SSC) of starfruits. A hyperspectral imaging system, which consists of a near infrared camera, a spectrograph V10, a halogen lighting and a conveyor belt system, was used in this study to acquire hyperspectral images of the samples in visible and near infrared (500-1000 nm) regions. Partial least square (PLS) was used to build the model and to find the optimal wavelength. Two different masks were applied for obtaining the spectral data. The optimal wavelengths were evaluated using multi linear regression (MLR). The coefficient of determination (R2) for validation using the model with first mask (M1) and second mask (M2) were 0.82 and 0.80, respectively.

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Pendugaan Kandungan Kimia Mangga Gedong Gincu Menggunakan Spektroskopi Inframerah Dekat (Prediction of Chemical Contents in ‘Gedong Gincu’ Mango using Near Infrared Spectroscopy)

Jurnal Agritech ◽

10.22146/agritech.16599 ◽

2016 ◽

Vol 36 (03) ◽

pp. 294 ◽

Cited By ~ 1

Author(s):

Herna Permata Sari ◽

Yohanes Aris Purwanto ◽

I Wayan Budiastra

Keyword(s):

Near Infrared ◽

Scatter Correction ◽

Solid Content ◽

Partial Least Square ◽

Least Square ◽

Error Prediction ◽

Soluble Solid Content ◽

Total Acid ◽

Acid Ratio ◽

Soluble Solid

The objective of this work was to predict the soluble solid content, total acid, sugar acid ratio, and crude fiber of ‘Gedong Gincu’ mango non destructive using Near infrared Spectroscopy. Experiments were carried out using 182 samples of ‘Gedong Gincu’ mango. NIR reflectance spectra measurements were performed at wavelength of 1000-2500 nm using NIRFlex N-500 fiber optic solid. References data were collected from laboratory measurements. Five pre-processing treatments, smoothing 3 points (sa3), normalization (n01), first derivative Savitzky-Golay 9 points (dg1), combination (n01, dg1), and the Multiplicative Scatter Correction (MSC) were used to improve the accuracy of the calibration model. Partial Least Square (PLS) method was used to calibrate NIR data through references data. The results show that the best method for prediction of soluble non solid spectra were MSC and 12 factor of PLS with calibration value of Correlation Coefficient (r), Square Error Calibration (SEC), Square Error Prediction (SEP), Ratio of standard error prediction to deviation (RPD) were 0.91, 0.25 %, 0.39 %, 2.14 respectively. Sugar acid ratio content was predictd using MSC and 12 factor of PLS calibration with values of r, SEC, SEP, RPD were 0.81, 32.08 °Brix/%, 38.44 °Brix/%, 1.45. Soluble solid content was predicted using sa3 and 15 factor of PLS calibration with values of r, SEC, SEP, RPD were 0.82, 1.04 °Brix, 1.28 °Brix, 1.52 respectively. Total acid was predicted using dg1 and 3 with the value of r, SEC, SEP, RPD were 0.74, 0.01 %, 0.12 %, 1.33 respectively. It could be concluded that the developed model could be used to predict the chemical contents of ‘Gedong Gincu’ mango non destructively. ABSTRAKTujuan dari penelitian ini adalah memprediksi kandungan total padatan terlarut (TPT), total asam, rasio gula asam, dan padatan tidak terlarut (serat kasar) mangga Gedong Gincu secara non destruktif menggunakan spektroskopi inframerah dekat (NIR). Bahan yang digunakan berupa mangga Gedong Gincu sebanyak 182 buah. Pengukuran spektra reflektan NIR dilakukan pada panjang gelombang 1000 – 2500 nm menggunakan NIRFlex N-500 fiber optik solid dilanjutkan pengukuran data referensi laboratorium. Lima pra-proses data spektra yaitu smoothing 3 points (sa3), normalisasi (n01), first derivative Savitzzky-golay (dg1), kombinasi (n01,dg1), dan Multiplicative Scatter Correction (MSC) dilakukan untuk meningkatkan akurasi model kalibrasi. Kalibrasi data NIR dan data kimia dilakukan menggunakan metode Partial Least Square (PLS). Metode terbaik untuk prediksi padatan tidak terlarut diperoleh dengan pra-proses MSC dan kalibrasi PLS dengan nilai Correlation Coefficient (r), Square Error Calibration (SEC), Square Error Prediction (SEP), Ratio of standard error prediction to deviation (RPD) adalah 0,91, 0,25 %, 0,39 %, 2,14, dan faktor PLS 12. Kandungan rasio gula asam diduga dengan pra-proses MSC serta kalibrasi PLS dengan nilai r, SEC, SEP, RPD adalah 0,81, 32,08 °Brix/%, 38,44 °Brix/%, 1,45 dan faktor PLS yang digunakan 12. TPT diduga menggunakan pra-proses sa3 dan kalibrasi PLS dengan nilai r, SEC, SEP, RPD adalah 0,82, 1,04 oBrix, 1,28 °Brix, 1,52. Model kalibrasi total asam diperoleh pra-proses dg1 dan kalibrasi PLS dengan nilai r, SEC, SEP, RPD adalah 0,74, 0,01 %, 0,12 %, 1,33. Hasil penelitian ini menunjukkan bahwa model yang dikembangkan dapat digunakan untuk menduga kandungan kimia mangga Gedong Gincu secara non destruktif.Kata kunci: Mangga Gedong Gincu; non destruktif; partial least square; pra-proses; spektroskopi NIR

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Quantitative Evaluation of Color, Firmness, and Soluble Solid Content of Korla Fragrant Pears via IRIV and LS-SVM

Agriculture ◽

10.3390/agriculture11080731 ◽

2021 ◽

Vol 11 (8) ◽

pp. 731

Author(s):

Yuanyuan Liu ◽

Tongzhao Wang ◽

Rong Su ◽

Can Hu ◽

Fei Chen ◽

...

Keyword(s):

Quality Parameters ◽

Solid Content ◽

Partial Least Square ◽

Least Square ◽

Function Parameter ◽

Support Vector ◽

Soluble Solid Content ◽

A Value ◽

Soluble Solid ◽

Error Weight

Customers pay significant attention to the organoleptic and physicochemical attributes of their food with the improvement of their living standards. In this work, near infrared hyperspectral technology was used to evaluate the one-color parameter, a*, firmness, and soluble solid content (SSC) of Korla fragrant pears. Moreover, iteratively retaining informative variables (IRIV) and least square support vector machine (LS-SVM) were applied together to construct evaluating models for their quality parameters. A set of 200 samples was chosen and its hyperspectral data were acquired by using a hyperspectral imaging system. Optimal spectral preprocessing methods were selected to obtain out partial least square regression models (PLSRs). The results show that the combination of multiplicative scatter correction (MSC) and Savitsky-Golay (S-G) is the most effective spectral preprocessing method to evaluate the quality parameters of the fruit. Different characteristic wavelengths were selected to evaluate the a* value, the firmness, and the SSC of the Korla fragrant pears, respectively, after the 6 iterations. These values were obtained via IRIV and the reverse elimination method. The correlation coefficients of the validation set of the a* value, the firmness, and the SSC measure 0.927, 0.948, and 0.953, respectively. Furthermore, the values of the regression error weight, γ, and the kernel function parameter, σ2, for the same parameters measure (8.67 × 104, 1.21 × 103), (1.45 × 104, 2.93 × 104), and (2.37 × 105, 3.80 × 103), respectively. This study demonstrates that the combination of LS-SVM and IRIV can be used to evaluate the a* value, the firmness, and the SSC of Korla fragrant pears to define their grade.

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Rapid Determination of Intact Sardine Fat by NIRS Using Surface Interactance Fibre Probe

International Journal of Food Engineering ◽

10.2202/1556-3758.1248 ◽

2007 ◽

Vol 3 (6) ◽

Cited By ~ 3

Author(s):

Musleh Uddin ◽

Sandor Turza ◽

Emiko Okazaki

Keyword(s):

Near Infrared ◽

Rapid Determination ◽

Scatter Correction ◽

Screening Method ◽

Fat Content ◽

Partial Least Square ◽

Least Square ◽

Partial Least Square Regression ◽

Infrared Spectrometer ◽

Near Infrared Spectrometer

A near-infrared spectrometer equipped with surface interactance optical fiber probe (400-1100 nm) was used to determine the fat content in intact sardine Sardinops melanostictus which is considered one of the important fish species of world aquaculture as well as human food source. The fat contents were 2.6425.52 % and fish weight ranges were between 45.23g and 133.76g. Partial least square regression was used to develop predictive equations for fat where two models (with and without multiplicative scatter correction known as MSC) showed relatively good performances with regression coefficients higher than 0.9 and errors below 1% on a fresh weight basis. Results showed that NIR interactance was a suitable non-destructive screening method for fat content in intact small pelagic fish like sardine.

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Optical Absorption and Scattering Properties at 900–1650 nm and Their Relationships with Soluble Solid Content and Soluble Sugars in Apple Flesh during Storage

Foods ◽

10.3390/foods9121881 ◽

2020 ◽

Vol 9 (12) ◽

pp. 1881

Author(s):

Li Fang ◽

Kangli Wei ◽

Li Feng ◽

Kang Tu ◽

Jing Peng ◽

...

Keyword(s):

Optical Properties ◽

Soluble Sugars ◽

Solid Content ◽

Partial Least Square ◽

Least Square ◽

Coefficient Of Determination ◽

Internal Quality ◽

Integrating Sphere ◽

Soluble Solid Content ◽

Soluble Solid

Soluble solid content (SSC) is regarded as the most significant internal quality associated with the taste and maturity in fruits. Evaluating the relationship between the optical properties and soluble sugars facilitates exploration of the mechanism of optical techniques in SSC assessment. In this research, absorption coefficient (μa) and reduced scattering coefficient (μ′s) of Fuji apple during storage were obtained using automatic integrating sphere (AIS) at 905–1650 nm. Relationships between μa, μ′s and SSC, and soluble sugars contents, were investigated. The result showed that SSC, the content of total soluble sugars (TSS), fructose, glucose and sucrose were all decreasing after storage, and the same trend appeared in the change of μa and μ′s. In the whole wavelength range, both μa and μ′s were positively related to SSC and soluble sugars contents. The correlations between μa and SSC, and soluble sugars contents, showed increasing tendencies with increasing wavelengths, while for μ′s, correlations had the opposite trend. The strongest correlations between μa and SSC, and soluble sugars contents, were observed in the correlation of μa with sucrose, with an r of 0.934. Furthermore, a partial least square (PLS) model for sucrose based on μa was built with the coefficient of determination of prediction (Rp2) and the root mean square error of prediction (RMSEP) of 0.851 and 1.047, respectively. The overall results demonstrate that optical properties at the range of 905–1650 nm could be used to evaluate SSC of apples and this may due to the strong correlation between sucrose content and μa.

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Monitoring of moisture content and basic specific gravity in black spruce logs using a hand-held MEMS-based near-infrared spectrometer

The Forestry Chronicle ◽

10.5558/tfc2013-112 ◽

2013 ◽

Vol 89 (05) ◽

pp. 607-620 ◽

Cited By ~ 14

Author(s):

Guillaume Hans ◽

Brigitte Leblon ◽

Rod Stirling ◽

Joseph Nader ◽

Armand LaRocque ◽

...

Keyword(s):

Specific Gravity ◽

Moisture Content ◽

Near Infrared ◽

Black Spruce ◽

Micro Electro Mechanical System ◽

Partial Least Square ◽

Least Square ◽

Partial Least Square Regression ◽

Infrared Spectrometer ◽

Near Infrared Spectrometer

Our study presents results of a test of a hand-held micro-electro-mechanical system (MEMS)-based near-infrared (NIR) spectrometer to estimate moisture content and basic specific gravity of black spruce frozen and unfrozen logs. The spectra were acquired on sapwood and heartwood as well as on tangential and transversal log sections. Partial least square regression was used to develop and validate the models that relate NIR spectral data to the log properties. Models were developed for the frozen and unfrozen logs separately (temperature-specific models) and for both kinds of logs together (generalized model). Both model types gave similar prediction accuracy and there were no temperature condition effects on the PLS model, for both moisture content and basic specific gravity estimation. This implies that the NIR spectrometer can be used whatever the log temperature conditions, even under freezing conditions.

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Effect of Cross-Linked Alginate/Oil Nanoemulsion Coating on Cracking and Quality Parameters of Sweet Cherries

Foods ◽

10.3390/foods10020449 ◽

2021 ◽

Vol 10 (2) ◽

pp. 449

Author(s):

Camilo Gutiérrez-Jara ◽

Cristina Bilbao-Sainz ◽

Tara McHugh ◽

Bor-Sen Chiou ◽

Tina Williams ◽

...

Keyword(s):

Titratable Acidity ◽

Quality Parameters ◽

Solid Content ◽

Postharvest Quality ◽

Soluble Solid Content ◽

Nutritional Values ◽

Quality Properties ◽

Vapor Transfer ◽

Sweet Cherries ◽

Soluble Solid

The cracking of sweet cherries causes significant crop losses. Sweet cherries (cv. Bing) were coated by electro-spraying with an edible nanoemulsion (NE) of alginate and soybean oil with or without a CaCl2 cross-linker to reduce cracking. Coated sweet cherries were stored at 4 °C for 28 d. The barrier and fruit quality properties and nutritional values of the coated cherries were evaluated and compared with those of uncoated sweet cherries. Sweet cherries coated with NE + CaCl2 increased cracking tolerance by 53% and increased firmness. However, coated sweet cherries exhibited a 10% increase in water loss after 28 d due to decreased resistance to water vapor transfer. Coated sweet cherries showed a higher soluble solid content, titratable acidity, antioxidant capacity, and total soluble phenolic content compared with uncoated sweet cherries. Therefore, the use of the NE + CaCl2 coating on sweet cherries can help reduce cracking and maintain their postharvest quality.

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