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The present manuscript focuses on reviewing the optical techniques proposed to monitor milk quality in dairy farms to increase productivity and reduce costs. As is well known, the quality is linked to the fat and protein concentration; in addition, this issue is crucial to maintaining a healthy herd and preventing illnesses such as mastitis and ketosis. Usually, the quality of the milk is carried out with invasive methods employing chemical reagents that increase the time analysis. As a solution, several spectroscopy optical methods have been proposed, here, the benefits such as non-invasive measurement, online implementation, rapid estimation, and cost-effective execution. The most attractive optical methods to estimate fat and protein in cow’s milk are compared and discussed considering their performance. The analysis is divided considering the wavelength operation (ultraviolet, visible, and infrared). Moreover, the weaknesses and strengths of the methods are fully analyzed. Finally, we provide the trends and a recent technique based on spectroscopy in the visible wavelength.
Abraham Gastélum-Barrios; Genaro M. Soto-Zarazúa; Axel Escamilla-García; Manuel Toledano-Ayala; Gonzalo Macías-Bobadilla; Daniel Jauregui-Vazquez. Optical Methods Based on Ultraviolet, Visible, and Near-Infrared Spectra to Estimate Fat and Protein in Raw Milk: A Review. Sensors 2020, 20, 1 .
AMA StyleAbraham Gastélum-Barrios, Genaro M. Soto-Zarazúa, Axel Escamilla-García, Manuel Toledano-Ayala, Gonzalo Macías-Bobadilla, Daniel Jauregui-Vazquez. Optical Methods Based on Ultraviolet, Visible, and Near-Infrared Spectra to Estimate Fat and Protein in Raw Milk: A Review. Sensors. 2020; 20 (12):1.
Chicago/Turabian StyleAbraham Gastélum-Barrios; Genaro M. Soto-Zarazúa; Axel Escamilla-García; Manuel Toledano-Ayala; Gonzalo Macías-Bobadilla; Daniel Jauregui-Vazquez. 2020. "Optical Methods Based on Ultraviolet, Visible, and Near-Infrared Spectra to Estimate Fat and Protein in Raw Milk: A Review." Sensors 20, no. 12: 1.
This article reviews the applications of artificial neural networks (ANNs) in greenhouse technology, and also presents how this type of model can be developed in the coming years by adapting to new technologies such as the internet of things (IoT) and machine learning (ML). Almost all the analyzed works use the feedforward architecture, while the recurrent and hybrid networks are little exploited in the various tasks of the greenhouses. Throughout the document, different network training techniques are presented, where the feasibility of using optimization models for the learning process is exposed. The advantages and disadvantages of neural networks (NNs) are observed in the different applications in greenhouses, from microclimate prediction, energy expenditure, to more specific tasks such as the control of carbon dioxide. The most important findings in this work can be used as guidelines for developers of smart protected agriculture technology, in which systems involve technologies 4.0.
Axel Escamilla-García; Genaro M. Soto-Zarazúa; Manuel Toledano-Ayala; Edgar Rivas-Araiza; Abraham Gastélum-Barrios. Applications of Artificial Neural Networks in Greenhouse Technology and Overview for Smart Agriculture Development. Applied Sciences 2020, 10, 3835 .
AMA StyleAxel Escamilla-García, Genaro M. Soto-Zarazúa, Manuel Toledano-Ayala, Edgar Rivas-Araiza, Abraham Gastélum-Barrios. Applications of Artificial Neural Networks in Greenhouse Technology and Overview for Smart Agriculture Development. Applied Sciences. 2020; 10 (11):3835.
Chicago/Turabian StyleAxel Escamilla-García; Genaro M. Soto-Zarazúa; Manuel Toledano-Ayala; Edgar Rivas-Araiza; Abraham Gastélum-Barrios. 2020. "Applications of Artificial Neural Networks in Greenhouse Technology and Overview for Smart Agriculture Development." Applied Sciences 10, no. 11: 3835.
The present work experimentally demonstrates a multimode fiber optic sensing setup for total fat detection in raw milk samples. The optical fiber arrangement incorporates a low-coherence Fabry–Perot cavity operating in dual response. The system provides a phase modulation for a total fat range from 0.97% to 4.36%. Here, the protein remains constant at 3%. The data indicate that maximum sensitivity close to 616 pm/%fat could be achieved at optimal wavelength operation (500 nm). In addition, the system presented a minimal repeatability error measurement of 0.08%, cross-sensitivity between protein and fat of 0.134, and a regression coefficient of r2=0.9763. A thermal analysis was also performed, which indicate the temperature immunity of the system. The proposed method represents a low-cost alternative to detect minimal fat variations in raw cow milk.
Abraham Gastélum-Barrios; Genaro M. Soto-Zarazúa; Juan F. García-Trejo; Juan M. Sierra-Hernandez; Daniel Jauregui-Vazquez; Gastélum- Barrios; Soto- Zarazúa; García- Trejo; Sierra- Hernandez; Jauregui- Vazquez. A New Method for Total Fat Detection in Raw Milk Based on Dual Low-Coherence Interferometer. Sensors 2019, 19, 4562 .
AMA StyleAbraham Gastélum-Barrios, Genaro M. Soto-Zarazúa, Juan F. García-Trejo, Juan M. Sierra-Hernandez, Daniel Jauregui-Vazquez, Gastélum- Barrios, Soto- Zarazúa, García- Trejo, Sierra- Hernandez, Jauregui- Vazquez. A New Method for Total Fat Detection in Raw Milk Based on Dual Low-Coherence Interferometer. Sensors. 2019; 19 (20):4562.
Chicago/Turabian StyleAbraham Gastélum-Barrios; Genaro M. Soto-Zarazúa; Juan F. García-Trejo; Juan M. Sierra-Hernandez; Daniel Jauregui-Vazquez; Gastélum- Barrios; Soto- Zarazúa; García- Trejo; Sierra- Hernandez; Jauregui- Vazquez. 2019. "A New Method for Total Fat Detection in Raw Milk Based on Dual Low-Coherence Interferometer." Sensors 19, no. 20: 4562.
We present a multi-wavelength ring fiber laser cavity based on modified loop fiber optic interferometer. Here, the interferometer is composed by three segments: two thin-core fiber (TCF) sections and one no-core fiber (NCF) section, these fibers are arranged as follows: TCF-NFC-TCF, then this structure is set into a fiber loop. Hence, by using a conventional ring laser cavity the proposed fiber optic loop is seed. Afterward, by controlling the modal fiber curvature and the ring cavity polarization state: single, dual and triple lasing modes can be achieved. The laser offers good power and wavelength stability, the maximal variations are 0.2 nm and 0.12 dB.
Enrique Delacruz-Mendoza; Daniel Jáuregui-Vázquez; Juan M. Sierra-Hernández; Luis M. Morales-Villagómez; Miguel A. Bello-Jiménez; Abraham Gastélum-Barrios; Julián M. Estudillo-Ayala; Roberto Rojas-Laguna; Luis A. Herrera-Piad. Multi-wavelength ring fiber laser cavity based on loop modal fiber optic interferometer. Fiber Lasers XVI: Technology and Systems 2019, 10897, 108972E .
AMA StyleEnrique Delacruz-Mendoza, Daniel Jáuregui-Vázquez, Juan M. Sierra-Hernández, Luis M. Morales-Villagómez, Miguel A. Bello-Jiménez, Abraham Gastélum-Barrios, Julián M. Estudillo-Ayala, Roberto Rojas-Laguna, Luis A. Herrera-Piad. Multi-wavelength ring fiber laser cavity based on loop modal fiber optic interferometer. Fiber Lasers XVI: Technology and Systems. 2019; 10897 ():108972E.
Chicago/Turabian StyleEnrique Delacruz-Mendoza; Daniel Jáuregui-Vázquez; Juan M. Sierra-Hernández; Luis M. Morales-Villagómez; Miguel A. Bello-Jiménez; Abraham Gastélum-Barrios; Julián M. Estudillo-Ayala; Roberto Rojas-Laguna; Luis A. Herrera-Piad. 2019. "Multi-wavelength ring fiber laser cavity based on loop modal fiber optic interferometer." Fiber Lasers XVI: Technology and Systems 10897, no. : 108972E.
Lycopene content is the most important antioxidant in tomatoes by the use in the cancer prevention. It was developed a portable system based in image processing and CIE L* a* b* color analysis, with the capability to sort tomato samples according to six ripeness grades and estimate lycopene content in mg/kg with a correlation coefficient of 0.99 and 0.98 respectively. This study shows that the image processing method is an attractive quantitative method for ripeness grade and lycopene content in tomatoes in a non-invasive assay.
Abraham Gastélum-Barrios; Juan Fernando Garcia-Trejo; Genaro Martin Soto-Zarazua; Gonzalo Macias-Bobadilla; Manuel Toledano-Ayala. Portable System to Estimate Ripeness and Lycopene Content in Fresh Tomatoes Based on Image Processing. 2018 XIV International Engineering Congress (CONIIN) 2018, 1 -5.
AMA StyleAbraham Gastélum-Barrios, Juan Fernando Garcia-Trejo, Genaro Martin Soto-Zarazua, Gonzalo Macias-Bobadilla, Manuel Toledano-Ayala. Portable System to Estimate Ripeness and Lycopene Content in Fresh Tomatoes Based on Image Processing. 2018 XIV International Engineering Congress (CONIIN). 2018; ():1-5.
Chicago/Turabian StyleAbraham Gastélum-Barrios; Juan Fernando Garcia-Trejo; Genaro Martin Soto-Zarazua; Gonzalo Macias-Bobadilla; Manuel Toledano-Ayala. 2018. "Portable System to Estimate Ripeness and Lycopene Content in Fresh Tomatoes Based on Image Processing." 2018 XIV International Engineering Congress (CONIIN) , no. : 1-5.