17 research outputs found

    Models Fitting to Pattern Recognition in Hyperspectral Images

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    Worldwide, the concern on food safety, for example, on agriculture products, has become a topic with huge relevance. Nowadays, hyperspectral imaging systems for rapid detection of dangerous agents have emerged in response to these needs. In this research project, we proposed a new algorithm for Salmonella typhimurium detection on tomato surfaces in visible range (400–1000 nm). Gaussian model was used as a way to take out a model that could be calculated its definite integral; the final result of this algorithm is the area under curve (AUC), which gives a quantitative approach of spectral signatures. Three doses (5, 10, and 15 μL) and a control response (0 μL) were spread out on 20 tomatoes’ surface. Subsequently, it was observed that some decrease responses with higher dose; also, numerically this pattern was seen with the help of AUC value. As a last step, a single factor analysis of variance showed no significance due to doses. Despite this outcome, the algorithm provides to be a good methodology for pathogen detection

    Automation and Robotics Used in Hydroponic System

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    Hydroponic system requires periodic labor, a systematic approach, repetitive motion and a structured environment. Automation, robotics and IoT have allowed farmers to monitoring all the variables in plant, root zone and environment under hydroponics. This research introduces findings in design with real time operating systems based on microcontrollers; pH fuzzy logic control system for nutrient solution in embed and flow hydroponic culture; hydroponic system in combination with automated drip irrigation; expert system-based automation system; automated hydroponics nutrition plants systems; hydroponic management and monitoring system for an intelligent hydroponic system using internet of things and web technology; neural network-based fault detection in hydroponics; additional technologies implemented in hydroponic systems and robotics in hydroponic systems. The above advances will improve the efficiency of hydroponics to increase the quality and quantity of the produce and pose an opportunity for the growth of the hydroponics market in near future

    Characterization of Mature Cladodes of Opuntia ficus-indica L. Using Morphological and Colorimetric Descriptors

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    Mexico is the world's leading producer of Opuntia ficus-indica. This kind of prickly pear is the most widespread and most commercially important cactus in Mexico. Morphological and colorimetric descriptors are among the most important agronomic traits because these parameters affect the yield, in such a way, the objective of the present research was to present a fast and reliable methodology to obtain the functional relationship in shape and color parameters of O. ficus indica cladodes, using a smartphone, a color meter, and open-access software. The acquisition and processing of images discovered interesting relationships between the Opuntia cladode's morphological characteristics, as well as colorimetric parameters of the cladodes. The non-linear data behaviors were fitted using deterministic models and CurveExpert software. Results of the study revealed that the best morphological descriptors were Circularity vs. Perimeter (r= 0.9815) and Aspect ratio vs. Roundness  (r= 0.9999).  In addition, mean values of the L*, C, and H color parameters were displayed in a window of a computer program online. It was found that the a-C relationship of the color parameters had the highest correlation coefficient (0.999). Therefore, it can be concluded that the morphological descriptors Circularity vs. Perimeter, Aspect Rate vs. Roundness, and a*-C color parameter can predict quickly and precisely the quality of O. ficus-indica

    Performance of electrical energy monitoring data acquisition system for plant-based microbial fuel cell

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    Plant microbial fuel cell (Plant-MFC) is an emerging technology that uses the metabolic activity of electrochemically active bacteria (EABs) to continue the production of bioelectricity. Since its invention and to date, great efforts have been made for its application both in real-time and large-scale. However, the construction of platforms or systems for automatic voltage monitoring has been insufficiently studied. Therefore, this study aimed to develop an automatic real-time voltage data acquisition system, which was coupled with an ATMEGA2560 connected to a personal computer. Before the system operation started it was calibrated to obtain accurate data. During this experiment, the power generation performance of two types of reactors i.e. (i) Plant-MFC and (ii) control microbial fuel cell (C-MFC), was evaluated for 15 days. The Plant-MFC was planted with an herbaceous perennial plant (Stevia rebaudiana), electrode system was placed close to the plant roots at the depth of 20 cm. The results of the study have indicated that the Plant-MFC, was more effective and achieved higher bioelectricity generation than C-MFC. The maximum voltage reached with Plant-MFC was 850 mV (0.85 V), whereas C-MFC achieved a maximum voltage of 762 mV (0.772 V). Furthermore, the same reactor demonstrated a maximum power generation of 66 mW m¯2 on 10 min of polarization, while a power density with C-MFC was equal to 13.64 mW m¯2. S.rebaudiana showed a great alternative for power generation. In addition, the monitoring acquisition system was suitable for obtaining data in real-time. However, more studies are recommended to enhance this type of system

    Hyperspectral signatures and reflectance models related to the ripening index in four grape varieties

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    The preference for the consumption of red wine in Mexico is increasing because its components derived from the grape are attributed to health benefits. The quality of wine depends mostly on the vineyard conditions. The objective of this study was able to differentiate the physicochemical composition in the harvest stage of four varieties of red grapes that are used in the production of wine to relate their maturation with those of their hyperspectral signatures. Various parameters including pH, total soluble solids, color, weight, and morphology were determined from the bunches of grapes. Concerning the maturity index, it was observed that the grapes with the highest degree of maturity were Shiraz and Merlot at harvest time. The pH of grape juice is a measure of active acidity; the texture is considered a quick and inexpensive technique. The hyperspectral signatures reflectances versus color, total soluble solids, morphology, weight, texture, and pH for each grape variety was best fitted with Gaussian curves of order 8 to Cabernet sauvignon and Merlot, 7 to Malbec, and 5 to Shiraz with R2 above 0.99

    METALES PESADOS EN LECHE CRUDA DE BOVINO

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    Se determinó el contenido de plomo, cadmio, cobre y zinc en 120 muestras de leche cruda pertenecientes a 5 establos ubicados en municipios del noreste de Nuevo León, México. En todos los establos evaluados se detectó la presencia de plomo, cadmio, cobre y zinc. Los intervalos de concentración para plomo oscilaron entre 0.8714 y 0.5998 mg/kg y para cadmio entre 0.3142 y 0.2794 mg/kg, que superan los niveles máximos permisibles establecidos por normas internacionales para leche cruda de bovino. La concentración de cobre fluctuó entre 0.3968 y 0.4816 mg/kg y de zinc osciló entre 3.199 a 4.0177 mg/kg por lo que ambos metales se presentaron dentro de los parámetros tolerables permitidos.Palabras clave: Metales pesados, leche de bovino.Heavy metals, bovine mil

    Hyperspectral Imaging in Agriculture, Food and Environment

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    This book is about the novel aspects and future trends of the hyperspectral imaging in agriculture, food, and environment. The topics covered by this book are hyperspectral imaging and their applications in the nondestructive quality assessment of fruits and vegetables, hyperspectral imaging for assessing quality and safety of meat, multimode hyperspectral imaging for food quality and safety, models fitting to pattern recognition in hyperspectral images, sequential classification of hyperspectral images, graph construction for hyperspectral data unmixing, target visualization method to process hyperspectral image, and soil contamination mapping with hyperspectral imagery. This book is a general reference work for students, professional engineers, and readers with interest in the subject
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