Browsing by Subject "Precision agriculture"

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    Development of an application to make knowledge available to the farmer: Detection of the most suitable crops for a more sustainable agriculture
    (IOS Press, 2020) Cadenas Figuerero, J.M.; Garrido Carrera, María del Carmen; Martínez España, R.; Ingeniería de la Información y las Comunicaciones
    Precision agriculture has different strategies to collect, process and analyze data of different types and nature to be able to make decisions that improve the efficiency, productivity, quality, profitability and sustainability of an agricultural production. Specifically, crop sustainability is directly related to reducing costs for farmers and minimizing environmental impact. In this paper an application to help in the decision making about the most convenient type of crop to plant in a certain zone is developed, taking into account the climate conditions of that zone, in order to make the crop sustainable. This application is integrated within an Internet of Things system, which is adaptable and parameterized for any type of crop and zone. The components of the Internet of Things system are described in detail and a fuzzy clustering model is proposed for the intelligent module of the system. This fuzzy model focuses on making a grouping of zones (zone management), taking into account the climatic conditions of a zone. The model manages fuzzy data, which allows for more extensive information and more natural treatment of the data. Finally, a real study case for the application proposed is presented using data from Region of Murcia (Spain). For this study case it has been described the whole deployed Internet of Things system. Also, the intelligent fuzzy clustering model to create similar areas in terms of meteorology has been validated and evaluated. In addition, the recommendation and decision support module has been implemented, taking into account real production data and resources needed for the crops in the Region of Murcia (Spain).
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    Effects of saline reclaimed waters and deficit irrigation on Citrus physiology assessed by UAV remote sensing
    (Elsevier, 2016-09-21) Romero Trigueros, Cristina; Nortes, Pedro A.; Alarcón, Juan J.; Hunink, Johannes E.; Parra, Margarita; Contreras, Sergio; Droogers, Peter; Nicolás, Emiliano; Ingeniería Química
    The aim was to assess the usefulness of spectral data to detect structural and physiological changes in Citrus crops under water and saline stress. Multispectral images were acquired from a fixed-wing Unmanned Aerial Vehicle (UAV) while concomitant measurements of gas exchange, plant water status, leaf structural traits and chlorophyll were taken in a commercial farm located in southeast Spain with two Citrus species, grapefruit and mandarin irrigated for eight years with saline reclaimed water (RW) combined with regulated deficit irrigation (RDI). Measurements at leaf scale and airborne flights were carried outtwice a day, at 7 and 10 GMT. Irrigation with RW decreased gas exchange and leaf dry mass per unit area (LMA) ongrapefruit.However, salinity fromRWresultedinanincrease inpressurepotential(P) onmandarinandallowedmaintainingnetphotosynthesis (A) andstomatal conductance (gs) whenvapour pressure deficit increased. On both crops, leaf total chlorophyll (ChlT) concentrations were significantly reduced by RW. Moreover, RDI decreasedA, gs and stem water potential(s) on grapefruit, independently of water quality. Regarding spectral data, red wavelength (R) was significantly correlated with Chl T (p < 0.001), except when mandarin was subjected to stressful climatic conditions (at 10 GMT); since R was influenced, in addition to Chl T, by the plant water and gas exchange status. Near infrared (NIR) was a useful indicator of s, A and gs on both crops. The normalized difference vegetation index (NDVI) was clearly related to gas exchange in both species and to s only on mandarin. Finally, we combined data from both Citrus species and the best indicators were NIR and R. The novelty of this study was to show that diurnal changes in physiological and structural traits of Citrus irrigated with RW combined with RDI can be determined by multispectral images from UAVs.
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    Making decisions for frost prediction in agricultural crops in a softcomputing framework
    (ScienceDirect, 2020) Cadenas Figueredo, J.M.; Garrido Carrera, María del Carmen; Martínez España, R.; Guillén-Navarro, M.A.; Ingeniería de la Información y las Comunicaciones
    Nowadays, there are many areas of daily life that can obtain benefit from technological advances and the large amounts of information stored. One of these areas is agriculture, giving place to precision agriculture. Frosts in crops are among the problems that precision agriculture tries to solve because produce great economic losses to farmers. The problem of early detection of frost is a process that involves a large amount of wheather data. However, the use of these data, both for the classification and regression task, must be carried out in an adequate way to obtain an inference with quality. A preprocessing of them is carried out in order to obtain a dataset grouping attributes that refer to the same measure in a single attribute expressed by a fuzzy value. From these fuzzy time series data we must use techniques for data analysis that are capable of manipulating them. Therefore, first a regression technique based on k-nearest neighbors in a Soft Computing framework is proposed that can deal with fuzzy data, and second, this technique and others to classification are used for the early detection of a frost from data obtained from different weather stations in the Region of Murcia (south-east Spain) with the aim of decrease the damages that these frosts can cause in crops. From the models obtained, an interpretation of the provided information is performed and the most relevant set of attributes is obtained for the anticipated prediction of a frost and of the temperature value. Several experiments are carried out on the datasets to obtain the models with the best performance in the prediction validating the results by means of a statistical analysis.