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Proximal remote sensing devices are novel tools that enable the study of plant health status through the measurement of specific characteristics, including the color or spectrum of light reflected or transmitted by the leaves or the canopy. The aim of this study is to compare the RGB and multispectral data collected during five years (2016–2020) of four fruiting vegetables (melon, tomato, eggplant, and peppers) with trial treatments of non-grafted and grafted onto resistant rootstocks cultivated in a Meloidogyne incognita (a root-knot nematode) infested soil in a greenhouse. The proximal remote sensing of plant health status data collected was divided into three levels. Firstly, leaf level pigments were measured using two different handheld sensors (SPAD and Dualex). Secondly, canopy vigor and biomass were assessed using vegetation indices derived from RGB images and the Normalized Difference Vegetation Index (NDVI) measured with a portable spectroradiometer (Greenseeker). Third, we assessed plant level water stress, as a consequence of the root damage by nematodes, using stomatal conductance measured with a porometer and indirectly using plant temperature with an infrared thermometer, and also the stable carbon isotope composition of leaf dry matter.. It was found that the interaction between treatments and crops (ANOVA) was statistically different for only four of seventeen parameters: flavonoid (p < 0.05), NBI (p < 0.05), NDVI (p < 0.05) and the RGB CSI (Crop Senescence Index) (p < 0.05). Concerning the effect of treatments across all crops, differences existed only in two parameters, which were flavonoid (p < 0.05) and CSI (p < 0.001). Grafted plants contained fewer flavonoids (x¯ = 1.37) and showed lower CSI (x¯ = 11.65) than non-grafted plants (x¯ = 1.98 and x¯ = 17.28, respectively, p < 0.05 and p < 0.05) when combining all five years and four crops. We conclude that the grafted plants were less stressed and more protected against nematode attack. Leaf flavon, Y.H. acknowledges the support of the Tunisian government from the Ministery of Higher Education and Scientific Research. J.L.A. acknowledges support from the Institució Catalana d’Investigació i Estudis Avançats (ICREA) Academia, Generalitat de Catalunya, Spain. S.C.K. is supported by the Ramon y Cajal RYC-2019-027818-I research fellowship from the Ministerio de Ciencia e Innovación, Spain. Thanks are also given to the Spanish Ministry of Economy and Competitiveness (MINECO) and the European Regional Development Fund (FEDER) for funding the project AGL2013-49040-C2-1-R and to the Ministry of Science and Innovation from the Spanish Government for funding the AGL2017-89785-R, and to the European Regional Development Fund (FEDER) AGL2017-89785-R, and for providing the FPI grant PRE2018-084265 to AMF. This research was also supported by the COST Action CA17134 SENSECO (Optical synergies for spatiotemporal sensing of scalable ecophysiological traits) funded by COST (European Cooperation in Science and Technology, www.cost.eu accessed on 29 April 2022)., Postprint (published version)

En este trabajo se detalla el proceso de desarrollo de una aplicación que permite realizar análisis de sensibilidad de una red logística de transporte de gas de forma paralela en varias máquinas y a través de la red. Esto incluye tanto la creación de una aplicación de escritorio que permita enviar los datos con los que se quiere realizar el análisis como un servicio web que ejecuta el resolutor IBM ILOG CPLEX y que realiza efectivamente el cálculo. En las siguientes secciones se procederá a explicar primero que es y como funciona y se modela una de estas redes de gas. Seguidamente pasaremos a comentar como usamos CPLEX y cual es el método para solucionar los modelos. A continuación se hará una breve introducción a ciertos conceptos que se necesitan conocer para poder comprender como funciona el paralelismo de la aplicación. Finalmente entraremos a fondo en la implementación de la aplicación para acabar con las conclusiones que hemos extraído, incluyendo posibles ampliaciones del proyecto. [ABSTRACT] In this work we detail the developing process of program which allows sensitivity analysis of a gas distribution network. These analysis are made in parallel on multiple computers and across thenet. This incudes the creation of a desktop application that can send the data you want to perform the analysys with and a web sevice that runs IBM ILOG CPLEX solver and that actually performs the calcullation. The following sections will explain what is and how one of this gas networks works and is modeled. After that, we will talk about how we use CPLEX and the algorith it uses to solve the models. Next, we will briefly introduce certain concepts needed to understand how the application exploits paralelism. Finnally we will enter fully in the implementation, ending with the conclusions we have obtained, including possible extensions of the project.