scholarly journals Multi-product Calibration Model for Soluble Solids and Water Content Quantification in Cucurbitaceae family, using Visible/Near-Infrared Spectroscopy

Heliyon ◽  
2021 ◽  
pp. e07677
Author(s):  
Kusumiyati ◽  
Yuda Hadiwijaya ◽  
Ine Elisa Putri ◽  
Agus Arip Munawar
Keyword(s):  
Infrared Spectroscopy ◽  
Water Content ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Soluble Solids ◽  
Calibration Model ◽  
Cucurbitaceae Family

scholarly journals Prediction of water content and soluble solids content of ‘manalagi’ apples using near infrared spectroscopy

2021 ◽  
Vol 922 (1) ◽  
pp. 012062
Author(s):  
K Kusumiyati ◽  
Y Hadiwijaya ◽  
D Suhandy ◽  
A A Munawar
Keyword(s):  
Infrared Spectroscopy ◽  
Water Content ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Quality Attributes ◽  
Soluble Solids ◽  
Coefficient Of Determination ◽  
Soluble Solids Content ◽  
Orthogonal Signal Correction ◽  
Solids Content

Abstract The purpose of the research was to predict quality attributes of ‘manalagi’ apples using near infrared spectroscopy (NIRS). The desired quality attributes were water content and soluble solids content. Spectra data collection was performed at wavelength of 702 to 1065 nm using a Nirvana AG410 spectrometer. The original spectra were enhanced using orthogonal signal correction (OSC). The regression approaches used in the study were partial least squares regression (PLSR) and principal component regression (PCR). The results showed that water content prediction acquired coefficient of determination in calibration set (R2cal) of 0.81, coefficient of determination in prediction set (R2pred) of 0.61, root mean squares error of calibration set (RMSEC) of 0.009, root mean squares of prediction set (RMSEP) of 0.020, and ratio performance to deviation (RPD) of 1.62, while soluble solids content prediction displayed R2cal, R2pred, RMSEC, RMSEP, and RPD of 0.79, 0.85, 0.474, 0.420, and 2.69, respectively. These findings indicated that near infrared spectroscopy could be used as an alternative technique to predict water content and soluble solids content of ‘manalagi’ apples.

scholarly journals Kandungan karotenoid, antioksidan, dan kadar air dua varietas cabai rawit pada tingkat kematangan berbeda dan deteksi non-destruktif

Jurnal Agro ◽  
2022 ◽  
Vol 8 (2) ◽  
pp. 212-225
Author(s):  
Kusumiyati Kusumiyati ◽  
Ine Elisa Putri ◽  
Wawan Sutari ◽  
Jajang Sauman Hamdani
Keyword(s):  
Infrared Spectroscopy ◽  
Water Content ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Calibration Model ◽  
Maturity Level ◽  
Total Carotenoids ◽  
Randomized Design ◽  
Completely Randomized Design ◽  
Non Destructive

Cabe rawit umumnya berwarna hijau, jingga dan merah. Tiap tingkat kematangan memiliki kualitas yang berbeda. Teknologi non-destruktif visible/near infrared spectroscopy (Vis/NIRS) telah banyak digunakan untuk memprediksi kualitas secara cepat dan akurat serta tidak merusak. Penelitian bertujuan untuk mengetahui kandungan kadar air, total karotenoid dan antioksidan dua varietas buah cabai rawit dengan tingkat kematangan berbeda dan memprediksi kualitas secara non-destruktif menggunakan Vis/NIRS. Penelitian dilakukan di Laboratorium Hortikultura, Fakultas Pertanian, Universitas Padjadjaran. Penelitian disusun dalam rancangan acak lengkap (RAL) dengan 6 perlakuan yaitu varietas ‘Manik’ dan ‘Domba’, yang dipanen pada 20 hari setelah bunga mekar (HSBM), 40 HSBM dan 60 HSBM, serta diulang 5 kali. Data dianalisis dengan analisis varians (ANOVA). Hasil penelitian menunjukkan bahwa varietas ‘Manik’ and ‘Domba’ yang dipanen pada 20 HSBM memiliki kandungan kadar air dan antioksidan tertinggi sedangkan total karotenoid meningkat pada buah matang. Model kalibrasi dan uji validasi silang kadar air, total karotenoid, dan antioksidan mendapatkan nilai Rkal  ≥ 0,87 dan Rval  ≥ 0,84. Berdasarkan hasil tersebut, maka kandungan air dan antioksidan terbesar yaitu buah cabai rawit hijau sedangkan total karotenoid tertinggi pada buah cabai rawit merah. Vis/NIRS dapat digunakan untuk mendeteksi kandungan air, total karotenoid dan antioksidan pada buah cabai rawit. Generally, cayenne pepper is coloring in green, orange, and red. Each maturity level has a different quality.  A non-destructive technology, visible/near infrared spectroscopy (Vis/NIRS), has been widely used to predict the quality quickly and accurately without causing damage. The study aimed to determine water content, total carotenoids, and antioxidant of two varieties cayenne pepper with different maturity levels and to predict quality non-destructively using Vis/NIRS. The research was conducted at the Horticulture Laboratory, Agriculture Faculty, Universitas Padjadjaran. The research was arranged in a completely randomized design (CRD) with 6 treatments, namely ‘Manik’ and ‘Domba’ varieties harvested at 20 days after flowering (DAF), 40 DAF and 60 DAF, and 5 replications with analysis of variance (ANOVA). The results showed that ‘Manik’ and ‘Domba’ harvested at 20 DAF had the highest water content and antioxidant while the total carotenoids increased in ripe fruit. The calibration model and cross-validation of water content, total carotenoids, and antioxidants obtained values of Rcal 0.87 and Rval 0.84. Based on these results, the highest water and antioxidant content was green cayenne pepper, while the highest total carotenoids were in red cayenne pepper. Vis/NIRS can be used to detect water content, total carotenoids, and antioxidants in cayenne pepper.

scholarly journals Near Infrared Spectroscopy as a Green Technology for the Quality Prediction of Intact Olives

Foods ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 1042
Author(s):  
Silvia Grassi ◽  
Olusola Samuel Jolayemi ◽  
Valentina Giovenzana ◽  
Alessio Tugnolo ◽  
Giacomo Squeo ◽  
...  
Keyword(s):  
Infrared Spectroscopy ◽  
Olive Oil ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Green Technology ◽  
Soluble Solids ◽  
Integrating Sphere ◽  
Total Phenolic ◽  
Handheld Device ◽  
Quality Design

Poorly emphasized aspects for a sustainable olive oil system are chemical analysis replacement and quality design of the final product. In this context, near infrared spectroscopy (NIRS) can play a pivotal role. Thus, this study aims at comparing performances of different NIRS systems for the prediction of moisture, oil content, soluble solids, total phenolic content, and antioxidant activity of intact olive drupes. The results obtained by a Fourier transform (FT)-NIR spectrometer, equipped with both an integrating sphere and a fiber optic probe, and a Vis/NIR handheld device are discussed. Almost all the partial least squares regression models were encouraging in predicting the quality parameters (0.64 < R2pred < 0.84), with small and comparable biases (p > 0.05). The pair-wise comparison between the standard deviations demonstrated that the FT-NIR models were always similar except for moisture (p < 0.05), whereas a slightly lower performance of the Vis/NIR models was assessed. Summarizing, while on-line or in-line applications of the FT-NIR optical probe should be promoted in oil mills in order to quickly classify the drupes for a better quality design of the olive oil, the portable and cheaper Vis/NIR device could be useful for preliminary quality evaluation of olive drupes directly in the field.

scholarly journals Determination of glomalin in agriculture and forest soils by near-infrared spectroscopy

2017 ◽  
Vol 63 (No. 5) ◽  
pp. 226-230 ◽  
Author(s):  
Zbíral Jiří ◽  
Čižmár David ◽  
Malý Stanislav ◽  
Obdržálková Elena
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Forest Soils ◽  
Near Infrared ◽  
Arable Land ◽  
Calibration Model ◽  
Sustainable Land Management ◽  
Chemical Methods ◽  
Calibration Models

Determining and characterizing soil organic matter (SOM) cheaply and reliably can help to support decisions concerning sustainable land management and climate policy. Glomalin was recommended as one of possible indicators of SOM quality. Extracting glomalin from and determining it in soils using classical chemical methods is too complicated and therefore near-infrared spectroscopy (NIRS) was studied as a method of choice for the determination of glomalin. Representative sets of 84 different soil samples from arable land and grasslands and 75 forest soils were used to develop NIRS calibration models. The parameters of the NIRS calibration model (R = 0.90 for soils from arable land and grasslands and R = 0.94 for forest soils) proved that glomalin can be determined in air-dried soils by NIRS with adequate trueness and precision simultaneously with determination of nitrogen and oxidizable carbon.

scholarly journals Estimation of selected properties of forest soils using near-infrared spectroscopy (NIR)

2016 ◽  
Vol 67 (1) ◽  
pp. 32-36 ◽  
Author(s):  
Mateusz Kania ◽  
Piotr Gruba
Keyword(s):  
Infrared Spectroscopy ◽  
Near Infrared Spectroscopy ◽  
Forest Soils ◽  
Near Infrared ◽  
C:N Ratio ◽  
Soil Samples ◽  
Initial Assessment ◽  
Calibration Model ◽  
Organic Carbon Content ◽  
Spectra Analysis

Abstract The study was focused on the application of near-infrared spectroscopy (NIR) as a tool for evaluation of selected properties of forest soils. We analysed 144 soil samples from the topsoil of nine plots located in southern Poland. Six plots were established under pine stands, and three plots under oak stands. The NIR measurements were performed using Antharis II FT scanner. On the basis of the spectrum files obtained from scanning of 96 samples and the measurement results obtained for selected properties of the soil samples, we developed a calibration model. The model was validated using 48 independent samples. We attempted to estimate the following properties of forest soils: pH, C:N ratio, the organic carbon content (Ct), total nitrogen (Nt), clay content (Clay), base cation content (BC), cation exchange capacity (CEC) and total acidity (TA). We conclude that estimation of soil properties using NIR method can be applied as additional (to laboratory analysis) or initial assessment of soil quality. Our results also suggest that forest species composition may affect the mathematical model applied to NIR spectra analysis, however, this hypothesis needs some of further investigations.

Fast Determination of Active Components in Fructus Corni by Near Infrared Spectroscopy

2013 ◽  
Vol 807-809 ◽  
pp. 2054-2058
Author(s):  
Hai Yan Gong ◽  
Ya Nan Hu ◽  
Cai Xia Xie ◽  
Yong Xia Cui ◽  
Yan Bai
Keyword(s):  
Quality Control ◽  
Infrared Spectroscopy ◽  
Mean Square Error ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Calibration Model ◽  
Mean Square ◽  
Active Components ◽  
Near Infrared Reflectance ◽  
Pharmaceutical Industries

Today, near-infrared (NIR) has been proved to be a powerful analytical tool. It has been applied widely in agricultural, petrochemical, textile and pharmaceutical industries. In this paper, near-infrared spectroscopy (NIRS) combined with partical least square (PLS) was used as a qualitative tool to rapidly determinate two active components in Fructus Corni. The PLS calibration model of NIR Spectroscopy, the correlation coefficients (R2) of Loganin and Morroniside were 0.95895 and 0.98450, the root-mean-square error of cross-validation (RMSECV), the Correction of deviation, the prediction mean square error was 0.0344,0.109;0.0625, 0.2641 and 0.0948, 0.233. The result shows that, the near-infrared Reflectance Spectroscopy could be used to determinate the content of Loganin and Morroniside, and meanwhile as a simple and rapid new method for the quality assessment of Fructus Corni. In addition, the NIRS has a unique advantage in the quality control of traditional Chinese Medicine (TCM), such as rapid, accurate, nondestructive and no pollution. It is expected to be further uses in the quality control of TCM. It is can achieve the requirement of rapid detection of large quantities of Fructus Corni.

Towards a robust water content determination of freeze-dried samples by near-infrared spectroscopy

2010 ◽  
Vol 676 (1-2) ◽  
pp. 34-40 ◽  
Author(s):  
Holger Grohganz ◽  
Delphine Gildemyn ◽  
Erik Skibsted ◽  
James M. Flink ◽  
Jukka Rantanen
Keyword(s):  
Infrared Spectroscopy ◽  
Water Content ◽  
Near Infrared Spectroscopy ◽  
Near Infrared ◽  
Content Determination ◽  
Freeze Dried
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