Measuring the Sugar Content of Apples and Apple Juice by Near Infrared Spectroscopy

Temma, Tsuyoshi; Hanamatsu, Kenkoh; Shinoki, Fujitoshi

doi:10.1007/s10043-002-0040-1

Cited by 19 publications

(14 citation statements)

References 2 publications

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“…In this experiment, the reflectance spectrum was calculated by comparing the NIR intensity (energy) reflected from the sample with a standard reference. From this research, Temma et al (2002) concludes that a standard error of prediction (SEP) value obtained for four varieties of apples (Fuji, Star King Delicious, Jonagold and Golden Delicious) is 0.546 o Bx at most with correlation coefficients above 0.94. While the measurement of sugar content for two kinds of apple juice, leads to a maximum SEP value of 0.439 o Bx and correlation coefficients above 0.97.…”

Section: Spectroscopic Methods In Fruits Quality Analysismentioning

confidence: 86%

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Optical Sensor in the Measurement of Fruits Quality: A Review on an Innovative Approach

Omar¹,

MatJafri²

2009

IJCEE

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Agriculture industries are developing standards that evaluating on fruits intrinsic properties before it is put in the market for the consumer, unlike current standards that focuses only on the physical appearance of the fruits. To achieve this, there exist well established instruments to evaluate fruits intrinsic quality parameters such as firmness, acidity and sugar content. However, the current approach utilizes an invasive techniques and time consuming. Efforts have been delivered by various researchers world wide in making use of optical measurement techniques, specifically through spectrometer. While realizing that a specific biochemical composition is responsive the best at a certain wavelength, an effort is being made by researchers from University Science Malaysia in developing a specialize instrument in measuring fruits intrinsic quality. Besides, several works has also been accomplished in understanding optical phenomena in fruits to further enhance the current methodology in benefiting agriculture industry, especially farmers in producing only best quality of fruits to the market.

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Section: Spectroscopic Methods In Fruits Quality Analysismentioning

confidence: 86%

“…This method takes longer time and at higher cost since sampling had to be made and the tested fruits will carry no more commercial values. Therefore, a much simpler, faster and highly accurate measurement method is required [3].…”

Section: Technological Efforts In Agriculture Industrymentioning

confidence: 99%

Optical Sensor in the Measurement of Fruits Quality: A Review on an Innovative Approach

Omar¹,

MatJafri²

2009

IJCEE

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“…The lycopene content measurement with NIR spectroscopy was not acceptable in this research. The researchers subjectively attributed this unsatisfactory to the uncertainty during Reflectance SSC [34] Reflectance SSC [33] Reflectance SSC [58] Interactance SSC [31] Reflectance Sugar content [38] Absorption Sugar content [65] Reflectance Sugar content [66] Reflectance Flavonols [67] N/A Firmness, sugars, acid, dry matter [68] Reflectance Sugar content [69] Reflectance Storage quality [70] Reflectance Maturity [71] Reflectance Bruise [72] Reflectance Bruise [73] Reflectance…”

Section: Discriminationmentioning

confidence: 99%

Theory and application of near infrared spectroscopy in assessment of fruit quality: a review

Lin

Ying

2009

Sens. & Instrumen. Food Qual.

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Fruits provide nutrients for human body and are able to prevent sorts of non-communicable diseases. The fruit quality test is an area that both technology and market section concern about. Near infrared spectroscopy (NIR) is a rapid, precise, and non-destructive technique which can be well utilized in determination of fruit quality. This review paper summarizes the theory of NIR analysis, and the fundamental structure of instruments based on NIR for fruit quality assessment. Chemometrics for NIR spectroscopy involving analysis methods of data pre-processing, calibration, model transfer and evaluation, is also included. In recent 11 years, significant progresses were achieved in fruit quality assessment via NIR spectroscopy, which is the main focus in this review. Furthermore, urgent problems in this research field are discussed, expecting to be solved in the near future.

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“…MLR is one of the established spectral evaluation techniques, and has been widely applied in spectroscopic analysis for fruit quality measurement. For example, Temma et al [3] and Ventura et al [4] applied MLR for SSC measurement in apples, Abebe [5] for SSC measurement in watermelon, Jaiswal et al [6] for SSC and pH measurement in mangoes, and Jha et al [7] for SSC and pH measurement in banana. The spectral linearisation technique compares the spectral linearity at a predefined range with the actual SSC values measured using a refractometer, unlike MLR, which uses selected wavelengths for prediction algorithm development.…”

Section: Introductionmentioning

confidence: 99%

Near Infrared Spectral Linearisation in Quantifying Soluble Solids Content of Intact Carambola

Omar

MatJafri

2013

Sensors

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This study presents a novel application of near infrared (NIR) spectral linearisation for measuring the soluble solids content (SSC) of carambola fruits. NIR spectra were measured using reflectance and interactance methods. In this study, only the interactance measurement technique successfully generated a reliable measurement result with a coefficient of determination of (R2) = 0.724 and a root mean square error of prediction for (RMSEP) = 0.461° Brix. The results from this technique produced a highly accurate and stable prediction model compared with multiple linear regression techniques.

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Measuring the Sugar Content of Apples and Apple Juice by Near Infrared Spectroscopy

Cited by 19 publications

References 2 publications

Optical Sensor in the Measurement of Fruits Quality: A Review on an Innovative Approach

Optical Sensor in the Measurement of Fruits Quality: A Review on an Innovative Approach

Theory and application of near infrared spectroscopy in assessment of fruit quality: a review

Near Infrared Spectral Linearisation in Quantifying Soluble Solids Content of Intact Carambola

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