No description available.

Orientador: João Carlos Cury Saad / Banca: Antonio Evaldo Klar / Banca: Antônio de Pádua Sousa / Banca: Glauber José de Castro Gava / Banca: Maritane Prior / Resumo: A indústria canavieira exerce papel fundamental no âmbito nacional, sendo de vital importância saber como a quantidade e a qualidade de matéria prima produzida é afetada pelo clima, pelos tratos culturais e pela região. Dentre os tratos culturais mais importantes e mais discutidos está a adubação nitrogenada. Entretanto nem sempre é possível obter dados reais, por várias razões, tempo, custo, dificuldade de acesso, entre outros. Neste contexto, surgem os modelos de simulação. Assim, este trabalho teve como objetivos comparar a utilização de água e de N-Fertilizante em soqueira de cana de açúcar nos manejos irrigados e de sequeiro, verificar o potencial de produção da soqueira de cana-de-açúcar com diferentes doses de N-fertilizante no manejo irrigado por gotejamento subsuperficial, utilizar e validar um modelo de simulação de crescimento de cana-de-açúcar e realizar estimativas (simulações) de acúmulo da biomassa e produtividade em soqueira de cana, nos manejos irrigados e de sequeiro com diferentes doses de N-fertilizante. O delineamento experimental utilizado foi o de blocos ao acaso, com quatro repetições para cada experimento, sendo os tratamentos: T1 (irrigado sem dose de nitrogênio (N)), T2 (irrigado com dose de 70 kg ha-1 de N), T3 (irrigado com dose de 140 kg ha-1 de N), T4 (irrigado com dose de 210 kg ha-1 de N), T5 (não irrigado sem dose de N) e T6 (não irrigado com dose de 140 kg ha-1 de N); todas as doses de N foram aplicadas na forma de Uréia. Para avaliar a produtividade da cultura realizou-se análise de variáveis biométricas, tecnológicas, biomassa seca e produtividade. Foram realizadas comparações de produtividade da cultura, toneladas de cana por hectare (TCH), toneladas de açúcar por hectare (TPH), peso da matéria seca da parte aérea (PA) e do colmo (C)... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract : Due to sugarcane industry has been playing a crucial role in national ambit it is vital to understand how the quantity and quality of raw material produced is affected by climate, crop handling and region. Among the crops handling, nitrogen is the most important and most discussed. However it is not always possible to obtain real data for several reasons: time, cost, difficulty of access, and others. Simulation models are used to respond to these variables. Therefore this study aimed to: compare the use of water and N-fertilizer in sugarcane ratoon in irrigated and rainfed conditions, verify the production potential of sugarcane ratoon with different doses of N-fertilizer in subsurface drip-irrigation management, use and validate a simulation model of sugarcane growth and make estimations (simulations) of biomass accumulation and sugarcane ratoon productivity in irrigated and rainfed conditions with different doses of N-fertilizer. The experimental design was a randomized block with four replications for each experiment, and the treatments: T1 (Irrigated without nitrogen dose (N)), T2 (irrigated with a dose of 70 kg ha-1 N) T3 (irrigated with a dose of 140 kg ha-1 N), T4 (irrigated with a dose of 210 kg ha-1 N), T5 (non-irrigated without N) and T6 (non-irrigated with a dose of 140 kg ha-1 N), all doses of N from urea. To evaluate the sugarcane productivity, the biometrical and technological variable were analysed, and also the dry biomass and the yield were accomplished. Comparisons were made with crop productivity, tons of cane per hectare (TCH), tons of sugar per hectare (TPH), and dry weight of shoot (PA) and stem (C). The program APSIM® (System simulator agricultural production) was applied to perform the simulations. The results showed that the irrigation system in combination with the N-fertilizer... (Complete abstract click electronic access below) / Doutor

In arid countries both water scarcity and salinity represent the key factors which drastically limit crop yield in irrigated agriculture. In addition, relatively poor management practices with pretty low water productivity (WP) seriously aggravate the situation. In order to get “more crop per drop', i.e., to substantially improve water use efficiency, this thesis proposes the novel strategy NEMO (Nested Experimental, Modeling, and Optimization Strategy) for reliably evaluating an optimal irrigation schedule. The proposed methodology relies upon a close interaction between in-depth field investigations and physically based process modeling. It is tailored specifically to fit the requirements in resource-restricted regions. Comprehensive field experiments, on site measurements as well as various laboratory analyses provide a representative database for characterizing the relevant environmental parameters as e.g. the soil properties at the considered location and the prevailing climate. A substantial part of the data obtained from the field experiments provided the input for the internationally recognized SVAT software DAISY1 or APSIM2, both physically based irrigation models which have already been successfully applied in arid regions. APSIM - which is used in the advanced parts of the study - includes not only a process based model for soil moisture transport but also a plant physiological model which describes the plant behavior under specific irrigation scenarios for a selected crop throughout a growing season. The adaption of the irrigation model to local conditions and its preliminary parameterization firstly follows available guidelines and data for areas with similar climate and soil conditions. Reference data and deterministic weather data served to build up DAISY’s basic model files. DAISY is then used within the framework of the custom made and problem oriented optimization software GET-OPTIS for evaluating the corresponding optimal irrigation schedule for a first preliminary series of experiments (IrrEx1). A second series of field experiments (IrrEx2) was accompanied by transient soil moisture measurements, which served for evaluating the soil hydraulic parameters, while the obtained yield was used for calibrating the plant physiological model of APSIM. Taking still into account the stochastic nature of weather phenomena, a stochastic optimization with GET-OPTIS was then applied not only for the traditional full irrigation but also for the most important deficit irrigation and the irrigation with saline water. The obtained optimal irrigation schedules are subsequently used for a final series of rigorous irrigation experiments (IrrEx3) which specifically focused on: (1) full irrigation for high yields with most economic water application, (2) deficit irrigation aiming at a maximum yield with only a limited amount of irrigation water, and (3) full irrigation with saline irrigation water for maximum yield. At the harvesting time, the observed crop yield and the water productivity were compared - together with other plant characteristics - with the corresponding calculated values. The agreement between calculated and measured crop data was excellent. All the field experiments have been performed following a parallel use of the common traditional FAO class A-Pan method and the novel NEMO technology. Based on the outcome of the field experiments, the NEMO applications demonstrated a striking superiority throughout all scenarios as compared to the FAO method as regards economic efficiency and sustainable use of irrigation water in both aspects water quantity and salt accumulation. Contrary to common practice, the optimal NEMO irrigation schedule - which relies on stochastic weather data - has an extended validity. Together with the use of physical data and adequate process models, the developed methodology features a highly promising potential for generalizing the experimental findings for other, environmentally similar, regions. NEMO thus opens wide possibilities for a cost effective and sustainable long-term application to other arid or semi-arid areas.

In the 400-600 mm annual rainfall zone of the Sahel, soil fertility is the main determinant of yield in rainfed millet cropping systems in all but the driest years. Numerous on-farm and on-station experiments have addressed the issue of improving soil fertility. Yet the widespread use of the experimental results is restricted by the highly site specific millet response to fertility management practices due to high spatially variable soil properties as well as high intra- and inter-annual rainfall variability. Mathematical soil-crop growth simulation models could therefore suitably complement experimental research to support decision making regarding soil fertility under variable rainwater supply conditions. The objective of this thesis was therefore to develop the biophysical basis for the use of crop-soil models in decision support regarding water and soil fertility management and risk mitigation strategies in rainfed millet-based systems of Sahelian Niger. Because farmers rely on multiple cultivars with variable length of growing cycle due to sensitivity to temperature and photoperiod as part of their risk management strategies we first characterized seven Sahelian millet genotypes and parameterized the Agricultural Production Systems Simulator (APSIM-millet model). The cultivars include three improved cultivars (CIVT, ICMV-IS-89305, ZATIB) and four landraces (Ankoutes, Hainikirey, Maewa and Zongo). Our research showed that only one of the cultivars, Maewa, was very photosensitive contrary to the six others. The majority of the agronomic state variables (leaf number, leaf area, biomass and grain yield) were negatively affected by late sowing (associated with lower air temperatures). This characterization enabled to compute for the first time in the Sahel the principal eco-physiological or genetic millet parameters (thermal times of development phases, leaf area dynamics) of crop growth models (e.g. APSIM, DSSAT). To gain confidence in the use of the APSIM model for decision support in the Sahelian environment, it was successfully tested to reproduce the agronomic state variables under non-limiting water and nutrient supply conditions. Moreover the APSIM model satisfactorily reproduced the millet CIVT cultivar response to water x N interaction from the combined application of crop residue, cattle manure and mineral fertilizer during two years and for contrasted rainfall conditions. Using the model with site and cultivar specific parameterization, we implemented two applications for decision support. A 23-year, long term factorial numerical experiment showed that a moderate N application of 15 kg N/ha is more appropriate for smallholder, subsistence farmers than the usual 30 kg N/ha recommendation. Although it implies a lower long term average yield than at 30 kg N/ha, the application of 15 kg N/ha guarantees both a higher minimum yield in extreme dry years and a lower inter-annual variability, thereby increasing food security and reducing farmers vulnerability. In the second model application, we integrated GIS information (land tenure, spatially distributed weather data, fertility management) and the APSIM model in a 12-year yield simulation to show that the spatial dispersion of fields of a household throughout the village territory (farmer risk management strategy) leads to more uniform yields across households and reduces the inter-annual yield variability in the Fakara region of Niger. Our research breaks the ground for several other applications of the use of crop-soil simulation models in millet-based systems in the Sahel, e.g. climate change impact and food crisis mitigation. / Dans la zone Sahélienne avec 400 à 600 mm de précipitation annuelle, la fertilité des sols est le principal facteur déterminant des rendements du mil pluvial hormis lors des années plus sèches. De nombreuses expérimentations au champ et en station ont abordé la question de l’amélioration de la fertilité des sols. Cependant, l’extrapolation de ces résultats, et a forciori leur utilisation par les agriculteurs, est limitée par le fait que la réponse du mil à ces pratiques de fertilité dépend fortement des propriétés des sols très variables dans l’espace ainsi que de la pluviométrie annuelle et sa répartition intra-annuelle. Les modèles mathématiques et dynamiques de simulation de la croissance des plantes peuvent donc utilement compléter la recherche expérimentale pour l’aide à la décision en ce qui concerne la gestion de la fertilité des sols dans diverses conditions d’alimentation hydrique. L’objectif de cette thèse était donc de développer les bases biophysiques pour l’utilisation de modèles de croissance des cultures en vue de leur utilisation comme outils d’aide à la décision en matière de gestion de l’eau et la fertilité des sols dans les systèmes de culture à base de mil en zone sahélienne du Niger. Puisque les paysans utilisent de multiples variétés de mil avec des cycles de croissance variables en tant qu’élément dans leurs stratégies de gestion des risques, nous avons d’abord caractérisé sept génotypes de mil Sahelien en vue de la paramétrisation du model dynamique APSIM (Agricultural Production Systems Simulator). Trois variétés améliorées (CIVT, ICMV-IS-89305, ZATIB) et quatre variétés locales paysannes (Ankoutes, Hainikirey, Maewa et Zongo) ont été étudiées. Notre recherche a montré que seule une des variétés, l’écotype Maewa, est très photosensible contrairement aux six autres. La majorité des variables agronomiques (nombre de feuille, surface foliaire, biomasse et rendement en grain) ont été négativement affectées par un semis tardif (associés à des températures de l’air plus faibles). Cette caractérisation a permis de calculer pour la première fois au Sahel les principaux paramètres éco-physiologiques du mil (durée thermique des phases de développement, dynamique de la surface foliaire), indispensables aux modèles dynamiques de croissance des plantes tels qu’APSIM et DSSAT. Le modèle APSIM a permis de reproduire avec succès les variables agronomiques de 6 des 7 variétés de mil en condition nonlimitante d’apport en eau et en nutriments. De plus, le modèle APSIM a reproduit de manière satisfaisante la réponse de la variété améliorée CIVT à l’interaction de l’eau et de l’azote suite à l’apport combiné de résidus de récolte, de fumier de bétail et d’engrais minéral sur deux années ayant des pluviométries contrastées. Ceci a permis de renforcer la confiance dans l’utilisation du modèle APSIM comme outil d’aide à la décision dans l’environnement Sahélien. Sur base du modèle APSIM ainsi paramétrisé pour des conditions spécifiques de site et de variété, nous avons développé deux applications en matière d’aide à la décision. Une expérimentation factorielle numérique à long terme (23 ans) a révélé que l’application d’une dose modérée d’azote (15 kg N/ha) est plus appropriée dans le contexte d’une agriculture de subsistance que la recommandation habituelle de 30 kg N/ha. Bien qu’elle implique un rendement moyen à long terme inférieur à celui obtenu avec 30 kg N/ha, l’application de 15 kg N/ha garantit un plus grand rendement minimum pendant les années sèches extrêmes et une variabilité inter-annuelle plus faible, ce qui permet de garantir une meilleure sécurité alimentaire tout en réduisant la vulnérabilité des paysans. Dans la deuxième application du modèle, nous avons intégré des données SIG (parcellaire villageois, données climatiques et de pratiques de gestion de fertilité distribuées dans l’espace) et le modèle APSIM dans une simulation de rendement de mil sur 12 années. Ceci a permis de montrer que la dispersion spatiale des champs d’un ménage dans le terroir villageois (stratégie paysanne de gestion du risque) permet l’obtention de rendements plus uniformes entre ménages au sein du même village et de réduire la variabilité inter-annuelle des rendements de chaque ménage dans la région de Fakara au Niger. Notre recherche ouvre la voie à plusieurs autres applications de l’utilisation des modèles dynamiques de croissance des plantes dans les systèmes à base de mil au Sahel, par exemple dans l’étude de l’impact des changements climatiques et de prévention des crises alimentaires.