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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Wiyada Tanvatanagul | en_US |
dc.contributor.author | Peena Saleewong | en_US |
dc.date.accessioned | 2018-09-11T08:58:53Z | - |
dc.date.available | 2018-09-11T08:58:53Z | - |
dc.date.issued | 2006-12-01 | en_US |
dc.identifier.issn | 09720502 | en_US |
dc.identifier.other | 2-s2.0-84890038323 | en_US |
dc.identifier.other | 10.1080/09720502.2006.10700455 | en_US |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=84890038323&origin=inward | en_US |
dc.identifier.uri | http://cmuir.cmu.ac.th/jspui/handle/6653943832/61768 | - |
dc.description.abstract | The objective of this research is to propose a model for predicting the sugar content or Total Soluble Solid (TSS) in pineapple flesh by measurements of light absorption at the wavelength in NIR stage of which fruits are not destroyed. In addition, relation between the sugar content in pineapple flesh that was predicted by multiple linear regression which derived from NIR data and sugar content obtained from chemical process is investigated. Moreover, we can apply our prediction method in screening the qualities of pineapple through the use of the reflectance (Rλ) data which is transformed to the quantity of absorption at the wavelength λ (Aλ). This research is conducted using 120 sampling units. There were 60 randomly assigned by SPSS/FW program for chemical process, and the rest for comparing sugar content obtained from this assumption with the prediction results using multiple linear regression and equation from Principal Component Regression (PCR). © Taru Publications. | en_US |
dc.subject | Mathematics | en_US |
dc.title | A statistical analysis of total soluble solid in pineapple fruits | en_US |
dc.type | Journal | en_US |
article.title.sourcetitle | Journal of Interdisciplinary Mathematics | en_US |
article.volume | 9 | en_US |
article.stream.affiliations | Chiang Mai University | en_US |
Appears in Collections: | CMUL: Journal Articles |
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