Instrumentation and control

Stanbury, Peter F.; Whitaker, Allan; Hall, Stephen J.

doi:10.1016/b978-0-08-099953-1.00008-9

Cited by 12 publications

(2 citation statements)

References 45 publications

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“…Near infrared is a quick, low-cost and non-destructive technique of analysis to distinguish between varieties and measure internal properties of fruits [11]. Near infrared uses light of wavelengths between the visible and the infrared region [12]. The use of shortwave near infrared region from 700-1100 nm can be accessed using inexpensive detectors and has been investigated in studies using various measurement modes such as reflectance, transmission, and interanctance [13].…”

Section: Introductionmentioning

confidence: 99%

Investigating the Relationship between the Reflected Near Infrared Light and the Internal Quality of Pineapples Using Neural Network

Jam¹,

Chia²

2017

International Journal on Advanced Science, Engineering and Information Technology

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One of the important internal qualities of pineapples is the total soluble solid content (SSC). Normally, the SSC can be evaluated using a reflectometer that is destructive and time-consuming. This research investigates the relationship between the reflected near infrared light and the internal quality of pineapples non-destructively. Five light emitted diodes (LEDs) that are in the range between 750 nm and 950 nm were used as the light source. The photodiode (OPT101) sensor was used to collect the light from the pineapple. The digital reflectometer was used to determine the reference SSC. The Near-infrared (NIR) data and the digital refractometer data were used to build the predictive model. The relationship between the near infrared light and the SSC of the pineapple was determined using artificial neural network predictive model. The internal quality of pineapples was determined using five NIR data wavelengths, the result points out that the k-fold cross-validation accurate classification was 75.56%. Besides, findings indicate that the artificial neural network that used four wavelengths that were 780 nm, 850 nm, 870 nm, and 940 nm achieved better classification than that used five wavelengths that included 910 nm. Thus, the artificial neural network coupled with NIR light is promising to be used to classify the internal quality of pineapples non-destructively.

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Section: Introductionmentioning

confidence: 99%

Investigating the Relationship between the Reflected Near Infrared Light and the Internal Quality of Pineapples Using Neural Network

Jam¹,

Chia²

2017

International Journal on Advanced Science, Engineering and Information Technology

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“…The TPC or ON/OFF controller is a simple controller. There are two operating conditions: fully opened or completely closed, depending on the controlled variable related to the set value [23]. For example, when the controlled variable increases above the set value, the TPC switches from "OFF" to "ON" states.…”

Section: Two-positions Controller (Tpc)mentioning

confidence: 99%

CFD—Assisted Expert System for N2-Controlled Atmosphere Process of Rice Storage Silos

Angsrisuraporn,

Samakkarn,

Lekawat

et al. 2024

Sustainability

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Since organic rice storage silos were faced with an insect problem, an owner solved this problem using the expert system (ES) in the controlled atmosphere process (CAP) under the required standard, fumigating insects with an N2, reducing O2 concentration to less than 2% for 21 days. This article presents the computational fluid dynamics (CFD) assisted ES successfully solved this problem. First, CFD was employed to determine the gas flow pattern, O2 concentration, proper operating conditions, and a correction factor (K) of silos. As expected, CFD results were consistent with the experimental results and theory, assuring the CFD’s credibility. Significantly, CFD results revealed that the ES controlled N2 distribution throughout the silos and effectively reduced O2 concentration to meet the requirement. Next, the ES was developed based on the inference engine assisted by CFD results and the sweep-through purging principle, and it was implemented in the CAP. Last, the experiments evaluated CAP’s efficacy in controlling O2 concentration and insect extermination in the actual silos. The experimental results and owner’s feedback confirmed the excellent efficacy of ES implementation; therefore, the CAP is effective and practical. The novel aspect of this research is a CFD methodology to create the inference engine and the ES.

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Food biotechnology

Fellows¹

2022

Food Processing Technology

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Instrumentation and control

Cited by 12 publications

References 45 publications

Investigating the Relationship between the Reflected Near Infrared Light and the Internal Quality of Pineapples Using Neural Network

Investigating the Relationship between the Reflected Near Infrared Light and the Internal Quality of Pineapples Using Neural Network

CFD—Assisted Expert System for N2-Controlled Atmosphere Process of Rice Storage Silos

Food biotechnology

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