Evidence map›Paper›PMID 37372626›Full record

ArticleFoods (Basel, Switzerland)2023

Potential of Near-Infrared Spectroscopy (NIRS) for Efficient Classification Based on Postharvest Storage Time, Cultivar and Maturity in Coconut Water.

Xiaojun Shen, Tao Wang, Jingyi Wei, Xin Li, Fuming Deng, Xiaoqing Niu, Yuanyuan Wang, Jintao Kan, Weimin Zhang, Yong-Huan Yun and 1 more

Open access · goldAbstract read
In one paragraph

Article in Foods (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.8field-weighted citation impact, top 32% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 8 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors at 3 institutions in 1 country.

Xiaojun ShenCoconut Research Institute, Chinese Academy of Tropical Agricultural Sciences, Wenchang 571339, China.
Tao WangSchool of Food Science and Technology, Hainan University, Haikou 570228, China.ORCID 0000-0003-0812-8546
Jingyi WeiCollege of Food Science and Technology, Huazhong Agricultural University, Wuhan 430070, China.
Xin LiCoconut Research Institute, Chinese Academy of Tropical Agricultural Sciences, Wenchang 571339, China.
Fuming DengCoconut Research Institute, Chinese Academy of Tropical Agricultural Sciences, Wenchang 571339, China.
Xiaoqing NiuCoconut Research Institute, Chinese Academy of Tropical Agricultural Sciences, Wenchang 571339, China.
Yuanyuan WangCoconut Research Institute, Chinese Academy of Tropical Agricultural Sciences, Wenchang 571339, China.
Jintao KanCoconut Research Institute, Chinese Academy of Tropical Agricultural Sciences, Wenchang 571339, China.
Weimin ZhangSchool of Food Science and Technology, Hainan University, Haikou 570228, China.
Yong-Huan YunSchool of Food Science and Technology, Hainan University, Haikou 570228, China.ORCID 0000-0003-1777-3205
Fusheng ChenCollege of Food Science and Technology, Huazhong Agricultural University, Wuhan 430070, China.ORCID 0000-0001-8525-4154
Chinese Academy of Tropical Agricultural Sciences · CNHainan University · CNHuazhong Agricultural University · CN

Funding

Demonstration and Promotion of Coconut Industry Technology in Lancang and Mekong River Basin not applicableNational Natural Science Foundation of China No. 22164008the major science and technology project of hainan province zdkj201902the major science and technology project of hainan province ZDKJ2021012
6 · The paper itself

Abstract

Coconut water (CW) is a popular and healthful beverage, and ensuring its quality is crucial for consumer satisfaction. This study aimed to explore the potential of near-infrared spectroscopy (NIRS) and chemometric methods for analyzing CW quality and distinguishing samples based on postharvest storage time, cultivar, and maturity. CW from nuts of Wenye No. 2 and Wenye No. 4 cultivars in China, with varying postharvest storage time and maturities, were subjected to NIRS analysis. Partial least squares regression (PLSR) models were developed to predict reducing sugar and soluble sugar contents, revealing moderate applicability but lacking accuracy, with the residual prediction deviation (RPD) values ranging from 1.54 to 1.83. Models for TSS, pH, and TSS/pH exhibited poor performance with RPD values below 1.4, indicating limited predictability. However, the study achieved a total correct classification rate exceeding 95% through orthogonal partial least squares discriminant analysis (OPLS-DA) models, effectively discriminating CW samples based on postharvest storage time, cultivar, and maturity. These findings highlight the potential of NIRS combined with appropriate chemometric methods as a valuable tool for analyzing CW quality and efficiently distinguishing samples. NIRS and chemometric techniques enhance quality control in coconut water, ensuring consumer satisfaction and product integrity.

Indexed as

Cocos nucifera L.discriminationdwarfsliquid endospermnon-destructive analysis

Identifiers

PMID37372626
PMCPMC10297207
OpenAlexW4381435539

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.