DEEP LEARNING-BASED RECONSTRUCTION OF SPATIOTEMPORALLY FUSED SATELLITE IMAGES FOR SMART AGRICULTURE APPLICATIONS IN A HETEROGENEOUS AGRICULTURAL REGION

Abstract. Remote sensing offers spatially explicit and temporally continuous observational data of various land surface parameters such as vegetation index, land surface temperature, soil moisture, leaf area index, and evapotranspiration, which can be widely leveraged for various applications at different scales and contexts. One of the main applications is agricultural monitoring, where a smart system based on precision agriculture requires a set of satellite images with a high resolution, both in time and space to capture the phenological stages and fine spatial details, especially in landscapes with various spatial heterogeneity and temporal variation. These requirements sometimes cannot be provided by a single sensor due to the trade-off required between spatial and temporal resolutions and/or the influence of cloud cover. The data availability of new generation multispectral sensors of Landsat-8 (L8) and Sentinel-2 (S2) satellites offers unprecedented options for such applications. Given this, the current study aims to display how the synergistic use of these optical sensors can efficiently support such an application. Herein, this study proposes a deep learning spatiotemporal data fusion method to fill the need for predicting a dense time series of vegetation index with fine spatial resolution. The results show that the developed method creates more accurate fused NDVI time-series data that were able to derive phenological stages and characteristics in single-crop fields, while keeps more spatial details in such a heterogeneous landscape. </jats:p

Effet du régime hydrique sur le rendement et la qualité de la clémentine de Berkane: vers une agrumiculture de précision

This study consists on identifying the optimal amount of irrigation water to ensure better productivity of Berkane clementine by using deficit irrigation method. Three degrees of irrigation restriction, compared to a control one, were studied. The amount of irrigation water used in the control treatment is estimated from the historical average reference evapotranspiration of the region, updated from the climate data of the current season (farmer's strategy). The amounts of irrigation water used for the three other treatments correspond to 80%, 60% and 50% of that used for the control. Presented results were obtained from an experimental study carried out on a young citrus orchard in Triffa plain (province of Berkane, Morocco) during two contrasting campaigns in term of annual rainfall: Rainy season (2017-2018) and dry season (2018 -2019). Obtained results showed that the amount of irrigation water has a significant effect on the different studied variables (yield, weight of the fruit, produced juice and total soluble solids). Also, reducing the amount of irrigation water by 20% compared to the control had no significant effect on the above-mentioned variables. Finally, this study showed that drought affects the size of the fruit despite the citrus grower's strategy contesting to increase the amount of irrigation water during the period of April-July. This strategy should therefore be reviewed to avoid losses due to fruits size at the packing stations. Continuous monitoring of soil moisture in the trees root zone and the exploitation of the new solutions offered by smart agriculture should help citrus growers to improve their decision-making strategies.Cette étude consiste à identifier la quantité d’eau d’irrigation optimale pour assurer une meilleure productivité du clémentinier de Berkane en utilisant la méthode d’irrigation déficitaire continue. Trois doses d’irrigation réduites par rapport à un témoin ont été étudiées. Dans le cas du témoin, la quantité d'eau d’irrigation utilisée est estimée à partir de l’évapotranspiration de référence moyenne historique de la région et mise à jour à partir des données climatiques de la saison en cours (stratégie de l’agriculteur). Les trois doses étudiées correspondent à 80%, 60% et 50% de celle utilisée pour le témoin. Les résultats présentés dans cet article sont obtenus à partir d’expérimentations réalisées en plein champs au niveau d’un jeune verger d’agrumes dans la plaine de Triffa (province de Berkane) pendant deux campagnes contrastées en termes de la pluviométrie : une campagne pluvieuse (2017-2018) et une autre au-dessous de la moyenne (2018-2019). Les résultats obtenus montrent que la réduction de la dose de l’irrigation a un effet significatif sur les différentes variables étudiées (rendement par arbre, poids et calibre du fuit, jus produit et taux de sucre). La réduction de 20% de la dose d’irrigation par rapport au témoin n’a pas d’effet significatif sur les variables précitées. Cette étude montre aussi que la sécheresse de la campagne agricole affecte le calibre du fruit malgré la stratégie de l’agrumiculteur qui consiste à augmenter la dose d’irrigation pendant les mois d’avril, mai, juin et juillet. Cette stratégie doit donc être revue pour éviter les pertes dues aux écarts de triage au niveau des stations de conditionnement. Le control continu de l’humidité du sol au niveau de la zone racinaire des arbres et l’exploitation des nouvelles solutions offertes par l’agriculture de précision devraient aider les agrumiculteurs à améliorer leurs stratégies de prise de décision

Effect of water stress on Berkane clementine yield and fruits quality: Towards a precision citrus growing

Cette étude consiste à identifier la quantité d’eau d’irrigation optimale pour assurer une meilleure productivité du clémentinier de Berkane en utilisant la méthode d’irrigation déficitaire continue. Trois doses d’irrigation réduites par rapport à un témoin ont été étudiées. Dans le cas du témoin, la quantité d'eau d’irrigation utilisée est estimée à partir de l’évapotranspiration de référence moyenne historique de la région et mise à jour à partir des données climatiques de la saison en cours (stratégie de l’agriculteur). Les trois doses étudiées correspondent à 80%, 60% et 50% de celle utilisée pour le témoin. Les résultats présentés dans cet article sont obtenus à partir d’expérimentations réalisées en plein champs au niveau d’un jeune verger d’agrumes dans la plaine de Triffa (province de Berkane) pendant deux campagnes contrastées en termes de la pluviométrie : une campagne pluvieuse (2017-2018) et une autre au-dessous de la moyenne (2018-2019). Les résultats obtenus montrent que la réduction de la dose de l’irrigation a un effet significatif sur les différentes variables étudiées (rendement par arbre, poids et calibre du fuit, jus produit et taux de sucre). La réduction de 20% de la dose d’irrigation par rapport au témoin n’a pas d’effet significatif sur les variables précitées. Cette étude montre aussi que la sécheresse de la campagne agricole affecte le calibre du fruit malgré la stratégie de l’agrumiculteur qui consiste à augmenter la dose d’irrigation pendant les mois d’avril, mai, juin et juillet. Cette stratégie doit donc être revue pour éviter les pertes dues aux écarts de triage au niveau des stations de conditionnement. Le control continu de l’humidité du sol au niveau de la zone racinaire des arbres et l’exploitation des nouvelles solutions offertes par l’agriculture de précision devraient aider les agrumiculteurs à améliorer leurs stratégies de prise de décision.This study consists on identifying the optimal amount of irrigation water to ensure better productivity of Berkane clementine by using deficit irrigation method. Three degrees of irrigation restriction, compared to a control one, were studied. The amount of irrigation water used in the control treatment is estimated from the historical average reference evapotranspiration of the region, updated from the climate data of the current season (farmer's strategy). The amounts of irrigation water used for the three other treatments correspond to 80%, 60% and 50% of that used for the control. Presented results were obtained from an experimental study carried out on a young citrus orchard in Triffa plain (province of Berkane, Morocco) during two contrasting campaigns in term of annual rainfall: Rainy season (2017-2018) and dry season (2018 -2019). Obtained results showed that the amount of irrigation water has a significant effect on the different studied variables (yield, weight of the fruit, produced juice and total soluble solids). Also, reducing the amount of irrigation water by 20% compared to the control had no significant effect on the above-mentioned variables. Finally, this study showed that drought affects the size of the fruit despite the citrus grower's strategy contesting to increase the amount of irrigation water during the period of April-July. This strategy should therefore be reviewed to avoid losses due to fruits size at the packing stations. Continuous monitoring of soil moisture in the trees root zone and the exploitation of the new solutions offered by smart agriculture should help citrus growers to improve their decision-making strategies

Deploying low-cost and full edge-IoT/AI system for optimizing irrigation in smallholder farmers communities

International Conference on Intelligent Environments, Biarritz, FRA, 20-/06/2022 - 23/06/2022About 35% of the world's food are produced in small-scale farms while only occupying about 12% of all agricultural land. However, smallholder farmers usually face a number of constraints and the water resource is one of the major constraints. The usage of smart technologies and especially sensor systems in so-called Smart Farming Technologies can be applied to the optimization of irrigation. Regardless of the irrigation technique, soil sensors are promising in providing data that can be used to further reduce the usage of water. However, despite all these possibilities, the smallholder community are still reluctant to step into technology-based systems. There are various reasons but prohibitive cost and complexity of deployment usually appear overwhelming. The PRIMA INTEL-IRRIS project has the ambition to make digital and smart farming technologies attractive & more accessible to these communities by proposing the intelligent irrigation 'in-the-box' concept. This paper describes the low-cost and full edge-IoT/AI system targeting the smallholder farmers communities and how it can provide the intelligent irrigation 'in-the-box' concept

Novel enantiopure cyclopentadienyl Ti(IV) oximato compounds as potential anticancer agents

The synthesis and characterization of new enantiopure cyclopentadienyl titanium oximato compounds (S,R)-[(η(5)-C(5)H(5))Ti{κ(2)NO,(R)NH·HCl}Cl(2)] (R = Ph (phenyl) 1a·HCl, Bn (benzyl) 1b·HCl, 2-pic (2-picolyl) 1c·HCl), (S,R)-[(η(5)-C(5)H(5))TiCl(2){κ(2)NO,(Ph)NH}] (1a) and (S,R)-[(η(5)-C(5)H(5))(2)TiCl{κ(2)NO,(R)NH}] (R = Ph 2a, Bn 2b, 2-pic 2c), along with studies on their behaviour in D(2)O at different pD values are reported. The structure of previously described ammonium-oxime (2S,5R)-{NOH,(Bn)NH·HCl} (b·HCl) and novel titanium derivative 1a have been determined by single crystal X-ray crystallography. The effect of the compounds on cytotoxicity, cell adhesion and migration of the androgen-independent prostate cancer PC-3 cells has been assessed. Compounds 2b and 2c are more cytotoxic than additive doses of titanocene dichloride and free oxime proligand, probing the synergistic effect of these novel compounds. The cytotoxicity of 2b and 2c has been further evaluated against human renal Caki-1, colon DLD-1 and triple negative breast MDA-MB-231 cancer cell lines. The activity found for 2c on PC-3 and Caki-1 is higher than that of highly active Titanocene Y (bis-[(p-methoxybenzyl)cyclopentadienyl]titanium(IV) dichloride), while showing selectivity against renal cancer when compared to a non-tumorigenic human renal (HEK-293T) cell line. Compounds 2b and especially 2c are apoptotic in Caki-1 cancer cell lines. Cell adhesion and wound-healing assays confirmed that derivatives 1c·HCl, 2b and 2c affect the adhesion and migration patterns of the PC-3 cell line. Interactions of the novel compounds with plasmid (pBR322) DNA have also been studied, showing that the oximato Ti(IV) derivatives have a weak or no interaction with DNA at physiological pH