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

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.

2018 ◽  
Vol 5 (1) ◽  
pp. 170714 ◽  
Author(s):  
Xiuhan Guo ◽  
Rui Cai ◽  
Shisheng Wang ◽  
Bo Tang ◽  
Yueqing Li ◽  
...  

Sea cucumber is the major tonic seafood worldwide, and geographical origin traceability is an important part of its quality and safety control. In this work, a non-destructive method for origin traceability of sea cucumber ( Apostichopus japonicus ) from northern China Sea and East China Sea using near infrared spectroscopy (NIRS) and multivariate analysis methods was proposed. Total fat contents of 189 fresh sea cucumber samples were determined and partial least-squares (PLS) regression was used to establish the quantitative NIRS model. The ordered predictor selection algorithm was performed to select feasible wavelength regions for the construction of PLS and identification models. The identification model was developed by principal component analysis combined with Mahalanobis distance and scaling to the first range algorithms. In the test set of the optimum PLS models, the root mean square error of prediction was 0.45, and correlation coefficient was 0.90. The correct classification rates of 100% were obtained in both identification calibration model and test model. The overall results indicated that NIRS method combined with chemometric analysis was a suitable tool for origin traceability and identification of fresh sea cucumber samples from nine origins in China.


2021 ◽  
pp. 101189
Author(s):  
Alin Khaliduzzaman ◽  
Ayuko Kashimori ◽  
Tetsuhito Suzuki ◽  
Yuichi Ogawa ◽  
Naoshi Kondo

2015 ◽  
Vol 671 ◽  
pp. 356-362 ◽  
Author(s):  
Zhi Feng Chen ◽  
Yuan Quan Hong ◽  
Chang Jiang Wan ◽  
Lian Ying Zhao

A fast non-destructive method of detection of wool content in blended fabrics was studied based on Near Infrared spectroscopy technology in order to avoid the time-consuming, tedious work and the destruction of samples in the traditional inspection. 621 wool/nylon, wool/polyester and wool/nylon/polyester blended fabrics were taken as research objects. To get the wool content, we established the wool near-infrared quantitative model by partial least squares (PLS) method after analyzing the color and composition of the samples. For verifying the validity and practicability of the model, 100 samples were chosen as an independent validation set. The variance analysis shows that there is no significant difference between Near Infrared fast detection method and national standard method (GB/T2910-2009),which indicates that this method is expected to be a means of fast non-destructive detection and will have extensive application future in the field of wool content detection.


LWT ◽  
2019 ◽  
Vol 103 ◽  
pp. 101-107 ◽  
Author(s):  
Lívia C. Carvalho ◽  
Marcondes L. Leite ◽  
Camilo L.M. Morais ◽  
Kássio M.G. Lima ◽  
Gustavo H.A. Teixeira

Sign in / Sign up

Export Citation Format

Share Document