Prediction of chick hatching time using visible transmission spectroscopy combined with partial least squares regression

被引：0

作者：

Islam, Md. Hamidul ^{[1
]}

Kondo, Naoshi ^{[1
]}

Ogawa, Yuichi ^{[1
]}

Fujiura, Tateshi ^{[1
]}

Suzuki, Tetsuhito ^{[1
]}

Nakajima, Shusaku ^{[1
]}

Fujitani, Shinichi ^{[2
]}

机构：

[1] Graduate School of Agriculture, Kyoto University, Kitashirakawa-Oiwakecho, Sakyo-ku, Kyoto,606-8502, Japan

[2] NABEL Co. Ltd., 86 Morimotocho, Nishikujo, Minami-ku, Kyoto,606-8444, Japan

来源：

Engineering in Agriculture, Environment and Food | 2015年 / 8卷 / 01期

关键词：

Spectrum analysis;

D O I：

10.1016/j.eaef.2014.10.001

中图分类号：

学科分类号：

摘要：

The feasibility of using visible transmission spectroscopy for the prediction of chick hatching time was investigated. An experiment was conducted with 100 chicken eggs in which transmission spectra were measured between incubation day 0 (non-incubated) and days 8 and subsequent hatching time was recorded. Spectral transmittance in the range of 500-750 nm was used in analysis. Spectral data were linked to hatching time using a partial least squares (PLS) regression method. Different pre-processing procedures were compared. The calibration model using incubation day 4 spectra with multiplicative scatter correction (MSC) resulted in the lowest root mean square error of prediction (RMSEP) = 3.41 h. The result indicates that the use of visible transmission spectroscopy combined with multivariate analysis has potential to predict the chick hatching time. © 2014 Asian Agricultural and Biological Engineering Association.

引用

页码：61 / 66

共 50 条

[1] Bankruptcy prediction using Partial Least Squares Logistic Regression
Ben Jabeur, Sami
JOURNAL OF RETAILING AND CONSUMER SERVICES, 2017, 36 : 197 - 202
[2] Direct determination of leather dyes by visible reflectance spectroscopy using partial least-squares regression
Blanco, M
Canals, T
Coello, J
Gené, J
Iturriaga, H
Maspoch, S
ANALYTICA CHIMICA ACTA, 2000, 419 (02) : 209 - 214
[3] Prediction of Total Volatile Basic Nitrogen in Pork Using Local Partial Least Squares Combined with Visible and Near-Infrared Spectroscopy
Wang, Wenxiu
Peng, Yankun
Wang, Fan
Ma, Ying
Shipin Kexue/Food Science, 2019, 40 (14): : 339 - 345
[4] Rapid quantification of pullulan in fermentation broth using UV-visible spectroscopy and partial least squares regression
Sahu, Nageswar
Mahanty, Biswanath
Haldar, Dibyajyoti
ANALYTICAL METHODS, 2025, 17 (14) : 2841 - 2849
[5] Chemometric Quantification of Peaberry Coffee in Blends Using UV-Visible Spectroscopy and Partial Least Squares Regression
Suhandy, Diding
Yulia, Meinilwita
Kusumiyati
8TH ANNUAL BASIC SCIENCE INTERNATIONAL CONFERENCE: COVERAGE OF BASIC SCIENCES TOWARD THE WORLD'S SUSTAINABILITY CHALLANGES, 2018, 2021
[6] Prediction of K value for fish flesh based on ultraviolet-visible spectroscopy of fish eye fluid using partial least squares regression
Rahman, Anisur
Kondo, Naoshi
Ogawa, Yuichi
Suzuki, Tetsuhito
Shirataki, Yuri
Wakita, Yumi
COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2015, 117 : 149 - 153
[7] Combined prediction model based on partial least squares regression and its application to near infrared spectroscopy quantitative analysis
Cheng Zhong
Zhu Ai-Shi
Chen De-Zhao
CHINESE JOURNAL OF ANALYTICAL CHEMISTRY, 2007, 35 (07) : 978 - 982
[8] Determination of High Concentration Copper Ions Based on Ultraviolet-Visible Spectroscopy Combined with Partial Least Squares Regression Analysis
Liang, Qian
Jiang, Linhua
Zheng, Jiwu
Duan, Ning
PROCESSES, 2024, 12 (07)
[9] Prediction of viability of oriental beechnuts, Fagus orientalis, using near infrared spectroscopy and partial least squares regression
Soltani, A
Lestander, TA
Tigabu, M
Odén, PC
JOURNAL OF NEAR INFRARED SPECTROSCOPY, 2003, 11 (05) : 357 - 364
[10] Prediction of sample physical and chemical properties by Raman spectroscopy and partial least squares regression.
Wang, HL
Vickers, TJ
Mann, CK
ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 1996, 212 : 56 - ANYL

← 1 2 3 4 5 →