Silvopastoral systems are a kind of agroforestry system in which trees or shrubs are combined with animals and pastures. Silvopastoral systems are important to intensify pasture production and mitigate climate change effects. However, very few studies have been performed to adapt crop models to simulate these systems. The aim of this study was to parameterize and test the mechanistic crop models APSIM and CROPGRO for estimating Urochloa brizantha cv. BRS Piatã productivity under full sun and in a silvopastoral system, to evaluate the models\' performance to simulate tree-crop interactions, and to develop tools to improve these simulations. For this purpose, four field experiments were conducted under full sun to investigate cutting management under irrigated and rainfed conditions and grazing management under rainfed conditions with high and low N supply. Another experiment was carried out in a silvopastoral system with the trees arranged in simple rows, in East-West orientation, with 15 m between rows and 2 m between plants in the rows. This experiment was conducted under grazing management and rainfed conditions with the pasture variables, microclimate and soil water content being assessed at four distances from the North row (0.00 m, 3.75 m, 7.50 m and 11.25 m). The forage mass simulations for the pasture at full sun, performed using the APSIM-Tropical Pasture model, showed good agreement between observed and estimated data (R2 between 0.82 and 0.97, d between 0.92 and 0.98, and NSE ranging from 0.72 to 0.92), while the simulations with the CROPGRO-Perennial Forage model achieved good precision (R2 between 0.65 and 0.93) and good accuracy (d from 0.86 to 0.97, and NSE from 0.60 to 0.90), for the various managements and environmental conditions. Even considering the promising performance of both models for pastures under full sun, they already needs to be tested in other locations, climate conditions, soils, and grazing or cutting intensities, to prove its accuracy and reach enough confidence. The pasture growth simulations at the silvopastoral system indicated that the APSIM-Tropical Pasture was efficient when only competition by solar radiation was considered (R2 from 0.69 to 0.88, d from 0.90 to 0.96, and NSE between 0.51 and 0.85), but inefficient when considering only competition by soil water (R2 between 0.58 and 0.85, d between 0.58 and 0.82, and NSE from -4.07 to -0.14). The CROPGRO-Perennial Forage achieved good performance on pasture growth simulation at the distances 0.00 m, 3.75 m, and 7.50 m from the trees (R2 from 0.75 to 0.90, d from 0.93 to 0.96, NSE between 0.74 and 0.85). Despite the good results, improvements should be performed in both models for simulating all factors that affect forage growth in silvopastoral systems. / Os sistemas silvipastoris são um tipo de sistema agroflorestal em que árvores ou arbustos são combinados com animais e pastagens. Os sistemas silvipastoris são importantes para a intensificação de pastagens e para a mitigação dos efeitos das mudanças climáticas. Entretanto, poucos estudos vêm sendo realizados visando à adaptação de modelos para a simulação desses sistemas. O objetivo desse estudo foi parametrizar e testar os modelos mecanísticos APSIM e CROPGRO para estimar a produtividade de Urochloa brizantha cv. BRS Piatã a pleno sol e em um sistema silvipastoril, avaliar o desempenho dos modelos para simular as interações árvore-pastagem e desenvolver ferramentas para aprimorar tais simulações. Para isso, foram conduzidos quatro experimentos de campo, a pleno sol, para avaliar diferentes manejos da pastagem: corte, em irrigado e sequeiro; e pastejo, em sequeiro e com alto ou baixo suprimento de nitrogênio. Outro experimento foi conduzido em um sistema silvipastoril com as árvores arranjadas em renques simples, com orientação Leste-Oeste, com espaçamento de 15 m entre renques e 2 m entre plantas nos renques. Esse experimento foi conduzido sob pastejo e em sequeiro, com avaliações das variáveis da pastagem, microclima e água no solo em quatro distâncias em relação ao renque Norte (0,00 m; 3,75 m; 7,50 m and 11,25 m). As estimativas de massa de forragem a pleno sol, realizadas com o modelo APSIM-Tropical Pasture, apresentaram boa concordância entre os dados observados e os estimados (R2 entre 0,82 e 0,97, d entre 0,92 e 0,98 e NSE de 0,72 a 0,92), enquanto que, as estimativas geradas pelo modelo CROPGRO-Perennial Forage alcançaram boa precisão (R2 entre 0,65 e 0,93) e boa exatidão (d entre 0,86 e 0,97 e NSE de 0,60 a 0,90), para os diferentes manejos e condições ambientais. Mesmo considerando o desempenho promissor de ambos os modelos para simular pastagens a pleno sol, para confirmar a acurácia e a eficiência destes, são necessários testes em outros locais, condições climáticas, tipos de solo e intensidades de corte ou pastejo. As simulações do crescimento da pastagem no sistema silvipastoril indicaram que o modelo APSIM-Tropical Pasture, foi eficiente quando somente a competição por radiação solar foi considerada (R2 de 0,69 a 0,88, d entre 0,90 e 0,96 e NSE de 0,51 a 0,85), mas ineficiente quando somente a competição por água no solo foi considerada (R2 entre 0,58 e 0,85, d entre 0,58 e 0,82 e NSE de -4,07 a -0,14). O modelo CROPGRO-Perennial Forage atingiu bom desempenho na simulação do crescimento da pastagem para as distâncias 0,00 m, 3,75 m e 7,50 m em relação às árvores (R2 de 0,75 a 0,90, d entre 0,93 e 0,96, NSE de 0,74 a 0,85). Apesar dos bons resultados, ambos os modelos devem ser melhorados para simular todos os fatores que afetam o crescimento de pastagens em sistemas silvipastoris.

A determinação da quantidade ideal de palha sobre o solo é uma das questões mais discutidas pelo setor sucroenergético, visto que este resíduo vegetal pode ser considerado um subproduto da cana-de-açúcar destinado à produção de etanol celulósico e cogeração de energia elétrica. Para estabelecer estes valores é necessário considerar as necessidades da cultura, juntamente com características físico-químicas e biológicas do solo. Os modelos de culturas baseados em processos (MCPs), especificamente o APSIM-Sugar, capaz de simular a matéria orgânica sobre o solo, pode ser utilizado em conjunto com experimentos de campo, para auxiliar as tomadas de decisão sobre quais as quantidades ideais de palha em cada sistema de produção de cana-de-açúcar no Brasil. Os MCPs devem ser utilizados para simular o desenvolvimento e o crescimento da cultura, além do balanço de água, nitrogênio e carbono no solo, o que possibilitaria a aplicação dos resultados experimentais em outras regiões de interesse, permitindo visão e compreensão mais amplas das principais questões do setor. Neste contexto, este estudo comparou dois tratamentos: manutenção de 100% da palha (CP) e remoção de 100% da palha (SP) em um experimento irrigado conduzido com a primeira soca da cultivar RB867515, cultivada na região meridional do Brasil, no município de Piracicaba, Estado de São Paulo, Lat. 22,67° S and Long. 47,64° W. Foram realizadas avaliações biométricas mensais, referentes as variáveis, perfilhamento, altura e diâmetro de colmos, índice de área foliar (IAF) e número de folhas verdes, assim como avaliações sobre as massas frescas e secas de folhas, colmos e palmitos. A evapotranspiração da cultura (ETc), foi obtida pelo método da razão de Bowen (MRB) e a partir da reflectometria no domínio da frequência (FDR). O fluxo de seiva pelo método do balanço de calor foi assumido como a transpiração (Tp). Comparando os tratamentos, observou-se diferenças significativas apenas para no IAF e na massa seca de folhas (MSF). A ETc mostrou valores entre 3 e 8 mm dia-1, dependendo das condições climáticas e do estágio da cultura. O coeficiente de cultivo (Kc) apresentou relação inversa com a evapotranspiração de referência (ETo), de tal forma que quando ETo < 2 mm, o Kc(SP) = 1,8 e o Kc(CP) = 1,5, e para situações com ETo > 6mm foram observados Kc(CP) = 1,3 e Kc(SP) = 1,2. O modelo de cultura APSIM-Sugar foi aplicado para diferentes regiões brasileiras, visando a determinação das melhores estratégias de manejo, tanto de água, quanto de solo. As simulações mostraram que, para todas as regiões, a manutenção de no mínimo 50% da palha e a reposição de 25% do total de irrigação, resultou nas maiores taxas de incremento da produtividade da cana-de-açúcar. / Determining the optimal amount of trash blankets above ground is one of the most discussed issues by the sugarcane industry, since this residue can be considered a byproduct of sugarcane due to cellulosic ethanol and electricity cogeneration. To establish these values, it is necessary to consider the crop needs together with physical, chemical and biological soil characteristics. The process based crop models (PBCMs), specifically APSIM-Sugar, able to simulate the soil organic matter, can be used in conjunction with field experiments to support the decision making about the optimum amounts of trash blanket for Brazilian sugarcane farming systems. PBCMs might be used to simulate the crop development and growth, water, nitrogen and carbon soil balances, and make the experiment data applicable for other regions allowing for a broader view and understanding on the key questions. In this context, this study compared two treatments: maintenance of 100% of the trash (CP) and removal of 100% of the trash (SP) in an experiment carried out with an irrigated first ratoon of RB867515 cultivar in Southern Brazil, at city of Piracicaba, State of São Paulo, Lat. 22,67° S and Long. 47,64° W. Monthly biometric evaluations were performed regarding the variables, tillering, stalk\'s height and diameter, leaf area index (LAI) and number of green leaves, as well as fresh and dry mass of leaves, cabbages and stalks. Crop evapotranspiration (ETc) were assessed by Bowen ratio method (MRB) and frequency domain reflectometry (FDR). Sap flow measured by heat balance method was assumed to be the crop transpiration (Tp). APSIM-Sugar crop model was calibrated based on these experimental data, and such model was applied for different Brazilian regions for evaluating the best water-trash management strategies for each region. Comparing both treatments there were just significant differences for leaf area index (LAI) and leaves dry mass (MSF). ETc was ranged from 3 to 8 mm day-1, depending on the weather conditions and crop stage. Crop coefficient (Kc) showed an inverse linear relationship with reference evapotranspiration (ETo), in such way that when ETo < 2 mm, the Kc(SP) = 1,8 and Kc(CP) = 1,5, and for ETo > 6mm it was observed Kc(CP) = 1,3 and Kc(SP) = 1,2. APSIM-Sugar simulations showed that, in the most part of cases, the keeping at least 50% of trash blanket and 25% of total irrigation requirement, resulted on the highest yield rates.

Poor agricultural productivity and food security remain challenging problems for the majority of smallholder famers in Sub-Saharan Africa, including semi-arid Eastern Kenya. However, there is a general consensus that there is urgent need to significantly increase food production to meet the growing demand aligned with the continuing population growth. Furthermore, the intensification and stabilization of agricultural productivity of small-scale farming systems in Sub-Saharan Africa holds a key position to contribute to the economic development and reduce poverty. The major driver for declining or stagnating agricultural productivity in many parts of Sub-Saharan Africa, such as semi-arid Eastern Kenya, is the decline in soil fertility. Food production is not keeping pace with rapid population growth, forcing farmers to change their traditional farming systems characterized by shifting cultivation, fallow and the use of animal manure. Land and labour restrictions, as well as an increased limited resource endowment further impose the mainly smallholder farmers to focus on the production of staples, such as maize in Eastern Kenya. The investment in soil fertility management strategies remains low and the change from traditionally diverse farming systems to cereal-based monocultures has further increased the susceptibility of the fragile production systems, in particular, to impacts of climate change and variability. The predicted increase in temperature as well as inter- and intra-seasonal rainfall variability will additionally challenge the largely rainfed smallholder farming systems to sustain their productivity in the future. The integration of legumes within the farming system has been part of traditional soil fertility management strategies since legumes are able to fix atmospheric nitrogen and yields of cereal crops are generally better if grown in rotation or intercropped with legumes. In particular grain legumes are highly valued components in smallholder farming systems due to their direct contribution to food and nutrition security. Moreover, legumes display a great agro-morphological diversity with great potential for challenging environments. Challenges aligned with climate change, such as increased rainfall variability, and restricted short growing periods, make short-season grain legumes a viable option as their adaption strategy of completing their life cycle before the onset of terminal drought seems to be advantageous for cropping with frequent droughts in semi-arid areas. However, to understand the temporal and spatial resource use and use efficiency of potential short-season grain legumes, especially in respect to light and water, it is of fundamental importance to design strategies for climate smart agriculture in risky environments, including areas of semi-arid Eastern Kenya. Furthermore,quantifying possible magnitudes of yield increase of different grain legumes can be useful in identifying niches in smallholder farming systems to increase overall farm productivity and sustainability. In order to explore the potential of certain crops and cropping strategies in diverse smallholder farming systems, the development and application of crop growth simulation models proved to be an excellent tool. Since African farming systems are highly heterogeneous and dynamic simulation models manage to address the complexity of these systems which is difficult to address through classical agronomic experiments alone. Simulation models are able to capture interactions between climatic conditions, soil type and nutrient dynamics. One of the most applicable models to better understand the complexities of plant growth in response to the environment has been the Agricultural Production System sIMulator (APSIM) framework, which has been successfully used for numerous farming system analyses in semi-arid areas in the past already. Against this background the objectives of this PhD thesis were, first, to compare growth and development of three promising short-season grain legumes (common bean, cowpea and lablab) in response to plant density and water regime to evaluate their production potential and resource capture in semi-arid environments (research chapter II). This was undertaken by the implementation and analysis of comprehensive field experiments carried out over two season 2012/13 and 2013/14 in Machakos, Eastern Kenya. Additionally to this comparative study of three legume species, the photo-thermal response of early-flowering lablab types were examined in a more detail from a combination of field experiments in South Africa and controlled environments studies conducted in Göttingen, Germany with the aim to evaluate their potential adaption to (sub)-tropical environments as a climate smart farming practice (chapter I). During the field experiments conducted in Machakos Kenya crop development, biomass and yield accumulations as well as leaf area index (LAI) were measured intensively throughout the growing period to determine import agronomic and physiological parameters, such as biomass partitioning coefficient, harvest index (HI) and radiation use efficiency (RUE) for the short-season legumes common bean, cowpea and lablab (chapter II). The output derived from the field experiments was further used to quantify essential cultivar-specific parameters to better calibrate (and later validate) APSIM to simulate growth and development of short-season grain legumes under semi-arid conditions (chapter III). Finally the agro-climatic conditions and changes as well as associated risk for rainfed crop production along the Machakos-Makueni transect in semi-arid Eastern Kenya was characterized in detail to identify possible niches for short-season grain legumes. For that purpose growth and development, as well as water use and use efficiency were simulated along the environmental gradient using APSIM (chapter IV). Within the first research chapter (chapter I) a comprehensive analysis of three datasets derived from field experiments in South Africa (different sites and sowing dates) and growth chamber experiments in Germany with a combination of two temperature and four daylength regimes were analysed to evaluate the response of temperature and photoperiod on flowering time of ten promising short-season lablab accessions (CPI 525313, CPI 52533, CPI 52535, CPI 52535, CPI 52552, CPI 52554, CPI 60795, CPI 81364, CQ 3620, Q 6880B). Hence, knowledge of phenological development and, in particular, time to flowering is crucial information needed for estimating the possible production success of new accessions in new and challenging environments, such as semi-arid Eastern Kenya. Therefore, the photoperiod sensitivity was quantified using the triple-plane rate model of flowering response with time to flowering expressed in thermal time (Tt, °Cd). Additionally, piecewise regression analysis was conducted to estimate the critical photoperiod ( ) above which time to flowering was delayed significantly. Relatively high variation of time to flowering among and within accessions in days after planting (DAP) was observed, ranging from 60 to 120 DAP depending on the site, sowing date or daylength/temperature regime. Furthermore, a clear positive effect of temperature on growth and development of the tested accessions was found and time to flowering, expressed as thermal time, were relative consistent for the tested accessions, ranging from 600 to 800 °Cd for daylength &lt;13.5 h. Only at daylength of ≥13.5 h and temperatures above 28 °C development towards flowering was delayed significantly for accessions CPI 52513, CPI 52535, CPI 52554 and CPI 60795 with vegetative growth continuing for &gt;110 DAP. The tested lablab accessions are, therefore, considered only weak photoperiod responsive and are classified as short-day plants (SDP). Since daylength does not exceed 13 h between latitude 30°N to 30°S covering the semi-arid tropical regions, these lablab accessions can be recommend for further evaluation of their adaption to, and productivity under, on-farm conditions. However, not only lablab offers a great potential for farming in semi-arid areas, legumes in general have proved to be a promising option in small-scale farming systems by combining benefits for the farmer, soil and environment. Therefore, effects of plant density and drought on growth and development of three promising short-season grain legumes including common bean, cowpea and lablab were quantified in detail to evaluate their agricultural production potential for semi-arid areas (chapter II). Two comprehensive field experiments; a plant density trial (three different plant densities; low, medium, high) and a water response trial (three different irrigation level: rainfed, partly irrigated (total 50 mm of water per week with supplementary irrigation till bud formation, i.e., onset of flowers), fully irrigated (total of 50 mm of water per week with supplementary irrigation throughout the growing period) were conducted to quantify the effect of plant density and water availability on canopy development, biomass accumulation and partitioning to evaluate resource use and use-efficiency of the different legumes. Therefore, biomass accumulation, leaf area index (LAI) and fractional radiation interception were measured repeatedly during the growing period while grain yield were measured at maturity. From the data collected, harvest index (HI), biomass partitioning coefficient and radiation use efficiency (RUE) were calculated. It was found that clear differences in temporal and spatial development and growth among the evaluated grain legumes are the major drivers for the observed variance in the fraction of intercepted radiation, biomass accumulation and grain yield. Moreover, the response of RUE to plant density and moisture availability differed among the three legumes. Common bean had a very short growing period (10 weeks), limiting the overall production potential (1000-1900 kg ha-1) under favourable conditions through limited source-sink dynamics in terms of time and space. Nevertheless, the short life cycle and the comparatively high RUE of common bean could be advantageous in environments with very short cropping windows. Cowpea showed a high phenological plasticity and potential to respond to favourable water supply in wet years by out-yielding the other legumes and reaching yields up to 3000 kg ha-1 under non water limited conditions. However, leaf development was observed to be sensitive to drought leading to decreased biomass development and consequently yield accumulation. The RUE of both common bean and cowpea was relatively low under rainfed conditions reaching only 0.49 and 0.54 g MJ-1, respectively, but more than doubled with supplementary irrigation. In contrast, lablab displayed stable RUE values (0.76 - 0.92 g MJ-1), and was not affected by limiting water availability, resulting in yields of 1200 to 2350 kg ha-1 across all water regimes. Nevertheless the growing period length of lablab was by far the longest (~100 days) compared to common bean and cowpea. The information revealed from the field experiments conducted in semi-arid Eastern Kenya was used to determine genetic coefficients and site-specific soil characterization to parameterize APISM for short-season legumes and semi-arid conditions (chapter III). The models were validated against data from the plant density and water regime trial conducted for two season (2012/13 and 2013/14) including observed data on soil moisture, phenology, biomass accumulation and yield development. Further, the adapted APSIM legume models were used in a long-term simulation experiment to evaluate the yield potential of the different short-season legumes under various management practices. The model accuracy to predict flowering time and time of physiological maturity was excellent and with a mean root squares of derivation (RMSD) of 5 days and less. For the different plant density and water regime treatments model predictions of biomass and grain yield were satisfactory reaching RMSD values expressed in % of the observed mean of about 12 for common bean biomass and grain yield and 23.5 and 26.0 and 20.8 and 25.1 for cowpea and lablab biomass and grain yield respectively. A good relationship between simulated yield and in-crop rainfall highlighted the importance of taking a water-limited potential yield into account when management practices are designed. To further quantify the potential of different short-season grain legumes in semi-arid areas where water is the most limiting factor for agricultural production the fourth research chapter aimed to examine the water use and water-use efficiency of short-season grain legumes along an environmental gradient in semi-arid Eastern Kenya (chapter IV). First, the climate variability along this transect was characterized in great detail including the analysis of annual and seasonal temperature development, inter- and intraseasonal rainfall variability as well as the analysis of the dry spell probability throughout the year. Second, growth and development of the short season grain legumes was simulated along the transect using APISM to assess the overall performance of the short-season legumes at different sites (potential rainfall areas) and evaluate the impact of various soil types to estimate their overall agricultural production potential. The analysis of long-term weather data from the Machakos – Makueni transect in semi-arid Eastern Kenya revealed large inter-annual as well as inter- and intra-seasonal variation in rainfall. Further trends showed that the growing season rainfall slightly decreased within the last decades. A decrease in mean rainfall intensity (rainfall per rain day) was observed for the past years as well. Regarding temperature development a slight increase in mean minimum and maximum temperatures was observed over the last decades, associated with an increase in days with maximum temperatures over 25 °C. Further analysis indicated an increased probability of long dry spells within the growing periods along the Machakos - Makueni transect and highly variable start and length of growing periods - creating a risky production environment. The observed variability of determined WUE of the different short-season grain legumes in terms of dry matter and grain yield production from the long-term simulations can be attributed to the effects of both the amount of rainfall and its distribution through the growing period. Water-potential yield of common bean was relatively stable (1000 kg ha-1), independent of total in-crop rainfall and soil conditions. Cowpea growth and development was, however, very responsive to in-crop rainfall. This is obvious as in wet years cowpea yield is very high (3000 kg ha-1), whereas in drier years grain yields (&gt;500 kg ha-1) are even lower than common bean grain yields. Lablab yields instead, were fairly robust (1000 – 3000 kg ha-1) and higher than those observed for common bean, even at low in-crop rainfall levels. Determined WUE in terms of biomass production was highest for cowpea and lablab (8 – 12 kg ha-1 mm-1 Et) in comparison to common bean (6 – 8 kg ha-1 mm-1 Et), but in terms of grain yield production only lablab (4 - 6 kg ha-1 mm-1 Et) achieved higher values compared to common bean (3 - 5 kg ha-1 mm-1 Et) and cowpea (2 - 4 kg ha-1 mm-1 Et). The magnitude of the soil impact on crop growth and development as well as water use and use efficiency differed with texture and water-holding capacity of the soil, soil evaporation and the interaction between these factors, rainfall pattern, crop canopy architecture and management. The current results revealed that resource capture of the studied legumes was primarily outlined by their characteristic phenological development and further determined by phenological plasticity related to water deficit and the ability to respond to environmental conditions. Pronounced spatial and temporal differences in water use and use efficiency of the studied legumes were therefore first driven by the varying phenological development and secondly by species-specific morphological and physiological characteristics and mechanisms. However, the ability of the legumes to respond to environmental conditions and the degree of phenological plasticity have evolved different strategies to cope with challenging conditions in semi-arid areas. To consider the pronounced temporal and spatial differences in resource use and growth characteristics is fundamental to better design strategies for climate smart agriculture in the smallholder farming systems of Eastern Kenya. The calibrated and validated APSIM legume models can be used to make appropriate management decisions to provide smallholder farmers in semi-arid with alternative options to better integrate short-season legumes to improve the overall farm productivity and sustainability. Crop models such as APSIM allow to account for necessary complexity but at the same time manage to address high location specificity. This is particular important in diverse smallholder farming systems in semi-arid areas to adequately address their individual needs and opportunities. The variability in phenological development and resource use and use efficiency observed for the different legumes and their different adaption mechanism to semi-arid areas offer great potential for small-scale farming systems in challenging environments. APSIM seems to be a great tool to explore their site-specific agricultural production potential and the impact of different management strategies is semi-arid Eastern Kenya. However, socio-economic constraints including labour requirements and market opportunities need to be assed in more detail to better channel agricultural recommendations to increase the possible adaption among farmers. Furthermore, long-term aspects of better integrated legumes towards improved farm sustainability and increased eco-efficiency need to be determined with the help of multidimensional whole farm analysis tools in order to proceed beyond crop and plot level in the future.

Com o objetivo de calibrar e avaliar o modelo ORYZA-APSIM para o arroz de terras altas no Brasil, foram conduzidos dezessete experimentos pela EMBRAPA Arroz e Feijão, em quatro regiões brasileiras (Santo Antônio de Goiás-GO, Sorriso-MT, Gurupi-TO e Teresina-PI) produtoras de arroz de terras altas, entre as safras de 2005/2006 e 2008/2009. O modelo foi calibrado e avaliado para a variedade cultivada de arroz de terras altas BRS-Primavera. Os dados da calibração foram obtidos de dois experimentos realizados na área experimental da EMBRAPA Arroz e Feijão, localizada no município de Santo Antônio de Goiás-GO, conduzidos em duas datas de semeadura durante a safra 2008/2009. As seguintes variáveis foram definidas na calibração: (i) unidades de calor efetivo diário, (ii) taxas de desenvolvimento fenológico para cada estádio, (iii) frações de massa de matéria seca das folhas, colmos, órgãos de armazenagem e colmos de reserva durante diferentes fases de desenvolvimento da cultura, (iv) taxa de crescimento inicial da área foliar e (v) parâmetros utilizados para determinar a área foliar específica. Na avaliação do modelo, foram comparados valores simulados com valores observados da massa de matéria seca total da parte aérea (MST) e de folhas verdes (MSF), índice de área foliar (IAF), produtividade e duração (número de dias) do período entre a emergência e o florescimento da cultura de arroz de terras altas. O modelo não apresentou desempenho satisfatório na simulação da duração das diferentes fases fenológicas de desenvolvimento para a região de Teresina-PI (os números de dias simulados foram, em média, oito dias superiores aos valores observados). O IAF, a MST e a MSF foram avaliados para as condições dos dois experimentos utilizados na calibração. As simulações do IAF diferiram dos valores observados nos dois experimentos, nos quais os valores finais da MST simulada foram semelhantes aos observados, mas diferiram dos observados durante a fase entre o florescimento e o ponto de maturidade fisiológica. A MSF simulada apresentou bom desempenho no primeiro experimento, mas regular no segundo experimento. No segundo experimento de campo, as variações da MSF, MST e o IAF foram causadas por um período de estresse hídrico simulado no modelo. O efeito do estresse hídrico foi superestimado no modelo. Comparando os valores simulados e observados de produtividade, por intermédio de uma regressão linear, verificou-se que o modelo (ORYZAAPSIM) pode determinar a ordem de grandeza da produtividade do arroz de terras altas ao nível de significância de 10%. / With the purpose of calibrating and evaluating the ORYZA-APSIM model for the upland rice in Brazil, seventeen field experiments were carried out at EMBRAPA Arroz e Feijão, in four upland rice Brazilian regions (Santo Antônio de Goiás-GO, Sorriso-MT, Gurupi and Teresina-PI), from 2005/2006 to 2008/2009 seasons. The model was calibrated and evaluated for an upland rice, cultivar BRS-Primavera. The calibration data were obtained from two field experiments carried out at the experimental area of EMBRAPA Arroz e Feijão, located at Santo Antônio de Goiás-GO, performed at two sowing dates during the 2008/2009 season. The following variables were defined in the calibration: (i) the effective heat daily units, (ii) phenological development rates at each crop stage, (iii) fractions of the dry matter of leaves, stems, storage organs and stems of reserves during the developmental crop stages, (iv) initial growth rate of leaf area and (v) parameters used to define the specific leaf area. In the model evaluation, simulated values were compared with observed values of total dry matter of shoot (DMS), dry matter of green leaves (DMGL), leaf area index (LAI), yield and duration (number of days) of the period from emergence to flowering of upland rice crop. The model did not present satisfactory performance to simulate the duration of different phenological phases of development for the Teresina-PI region (the numbers of simulated days were, in average, eight days greater than the observed values). The LAI, DMS and DMGL values were evaluated for the conditions of the two experiments used for calibration. The LAI simulations differed from the values observed in both experiments, where the final DMS simulated values were similar to those observed, but differed during the phase between flowering and physiological maturity point. The simulated DMGL showed a better performance in the first experiment, but regular in the second experiment. In the second field experiment, the DMS, DMGL and LAI variations were due to a period of drought stress simulated in the model. The model greatly penalized the growth of the culture under conditions of drought stress. The water stress effect was overestimated in the model. Comparing the simulated and observed values of yield, using a linear regression, it was verified that the model (ORYZA-APSIM) can define the magnitude order of upland rice productivity at 10% of significance level.

In Limpopo Province of South Africa, poor soil fertility and low crop yields are serious problems facing resource poor smallholder farmers. A survey of over 60 farmers in 2 villages (Gabaza and GaKgoroshi) found that most of the smallholder farmers were women (68%), elderly (50% above 68 years of age) and had not attended school or only attended up to the primary level (80%). Very few farmers kept livestock (usually in small numbers) and most grew cereal and legume crops (on 1ha of land) for home consumption and livestock feed, with legumes being planted on 13% of the land. The study showed that 80% of farmers were not fully aware of the benefits of legumes in fixing nitrogen (N) and improving yield. A field study at the survey village of Gabaza found that the application of fertiliser N and grass mulch combination and fertiliser N plus guarbean mulch significantly increased plant height and maize shoot growth at 4 and 8 weeks after planting. However, when grass mulch was without N fertiliser, there was no increase in maize growth relative to the control (0N). A farming systems simulation model (Agricultural Production Systems sIMulator - APSIM) was used to simulate this field study as well as over the long-term (1971 to 2008). Simulation analysis showed poor average maize yield (<3000 kg ha⁻ ¹) with the application of grass residues even when used with 30 kg N fertiliser. However, the application of guarbean residues as mulch with or without N fertiliser and as green manure increased maize yields to >4000 kg ha⁻ ¹. Simulation showed that the grass mulch with or without the addition of N fertiliser reduced water stress and soil water evaporation but increased N stress during the reproductive phase of the crop in most seasons. When guarbean mulch was used as green manure by itself, or mulch plus N fertiliser, N stress was reduced but water stress and soil water evaporation were increased which could have been due to faster decomposition of legume mulch as compared to grass mulch. Addition of N fertiliser reduced N stress to maize but increased water stress and soil water evaporation similar to the guarbean mulch because of high soil evaporation. APSIM analysis clearly showed the importance of N x soil water interactions in determining maize growth and yield at Gabaza. Therefore, two studies were undertaken in the laboratory in Australia to determine the dynamics of carbon (C) and N where residues of different qualities [canola (C:N 43), wheat (26), pea (9) and mucuna (14)] were applied to clay loam (Tarlee) or sandy (Waikerie) soils. In experiment 1, where residues were incorporated into the two soils, the cumulative CO₂-C evolution for the wheat and canola treatments at the end of the incubation period were fairly similar but significantly higher than for pea, mucuna and the control. In general, the application of residues increased microbial biomass C more than the control, with highest increases up to 1.48 and 1.56 mg C g⁻ ¹ soil for canola and wheat in Tarlee soil, respectively and 0.82 mg C g⁻ ¹ soil for pea in Waikerie soil. Even though the Tarlee soil showed greater C release than Waikerie soil, the C turnover from the residues between the 2 soils was not significantly different except for pea residues. Canola and wheat residues were found to immobilise N whereas N content increased in both soils with the application of legumes (pea and mucuna). In experiment 2, mucuna, pea and wheat residues were either incorporated or applied as surface mulches on Waikerie soil. Initially the CO₂-C release was higher for incorporated than mulched residues and CO₂-C released was higher for pea residues. However, at the end of the incubation more CO₂-C was released with the application of wheat residue indicating differences between residue types in the pattern of soil respiration. Microbial biomass C was higher for incorporated than mulched residue treatments; pea residue showed the highest biomass C for incorporated (0.78 mg C g⁻ ¹ soil) whereas mucuna had the highest microbial biomass (0.11 mg C g⁻ ¹ soil) treatments. The method of residue application resulted in a significant difference in C turnover between residues, with pea residue showing significant increase in C utilisation than mucuna and wheat. The pea residues, which had the lowest C:N, increased soil mineral N more than other treatments in both incorporated and mulched treatments. Lower mineralisation of N observed in residues of high C:N ratio compared to the control could be due to immobilisation of N. Therefore, understanding the nutrient dynamics of different crop residues could play an important role in the management of residues in different soil types. Based on these results it can be concluded that legume residues have the potential to improve soil fertility and crop yields in dryland farmers’ fields in Limpopo. Extension programs aimed at increasing farmers’ knowledge of the benefits of N fixation by legumes may increase their adoption and thereby improve soil fertility and maize yield. / Thesis (M.Ag.Sc.) -- University of Adelaide, School of Agriculture, Food and Wine, 2010

In Limpopo Province of South Africa, poor soil fertility and low crop yields are serious problems facing resource poor smallholder farmers. A survey of over 60 farmers in 2 villages (Gabaza and GaKgoroshi) found that most of the smallholder farmers were women (68%), elderly (50% above 68 years of age) and had not attended school or only attended up to the primary level (80%). Very few farmers kept livestock (usually in small numbers) and most grew cereal and legume crops (on 1ha of land) for home consumption and livestock feed, with legumes being planted on 13% of the land. The study showed that 80% of farmers were not fully aware of the benefits of legumes in fixing nitrogen (N) and improving yield. A field study at the survey village of Gabaza found that the application of fertiliser N and grass mulch combination and fertiliser N plus guarbean mulch significantly increased plant height and maize shoot growth at 4 and 8 weeks after planting. However, when grass mulch was without N fertiliser, there was no increase in maize growth relative to the control (0N). A farming systems simulation model (Agricultural Production Systems sIMulator - APSIM) was used to simulate this field study as well as over the long-term (1971 to 2008). Simulation analysis showed poor average maize yield (<3000 kg ha⁻ ¹) with the application of grass residues even when used with 30 kg N fertiliser. However, the application of guarbean residues as mulch with or without N fertiliser and as green manure increased maize yields to >4000 kg ha⁻ ¹. Simulation showed that the grass mulch with or without the addition of N fertiliser reduced water stress and soil water evaporation but increased N stress during the reproductive phase of the crop in most seasons. When guarbean mulch was used as green manure by itself, or mulch plus N fertiliser, N stress was reduced but water stress and soil water evaporation were increased which could have been due to faster decomposition of legume mulch as compared to grass mulch. Addition of N fertiliser reduced N stress to maize but increased water stress and soil water evaporation similar to the guarbean mulch because of high soil evaporation. APSIM analysis clearly showed the importance of N x soil water interactions in determining maize growth and yield at Gabaza. Therefore, two studies were undertaken in the laboratory in Australia to determine the dynamics of carbon (C) and N where residues of different qualities [canola (C:N 43), wheat (26), pea (9) and mucuna (14)] were applied to clay loam (Tarlee) or sandy (Waikerie) soils. In experiment 1, where residues were incorporated into the two soils, the cumulative CO₂-C evolution for the wheat and canola treatments at the end of the incubation period were fairly similar but significantly higher than for pea, mucuna and the control. In general, the application of residues increased microbial biomass C more than the control, with highest increases up to 1.48 and 1.56 mg C g⁻ ¹ soil for canola and wheat in Tarlee soil, respectively and 0.82 mg C g⁻ ¹ soil for pea in Waikerie soil. Even though the Tarlee soil showed greater C release than Waikerie soil, the C turnover from the residues between the 2 soils was not significantly different except for pea residues. Canola and wheat residues were found to immobilise N whereas N content increased in both soils with the application of legumes (pea and mucuna). In experiment 2, mucuna, pea and wheat residues were either incorporated or applied as surface mulches on Waikerie soil. Initially the CO₂-C release was higher for incorporated than mulched residues and CO₂-C released was higher for pea residues. However, at the end of the incubation more CO₂-C was released with the application of wheat residue indicating differences between residue types in the pattern of soil respiration. Microbial biomass C was higher for incorporated than mulched residue treatments; pea residue showed the highest biomass C for incorporated (0.78 mg C g⁻ ¹ soil) whereas mucuna had the highest microbial biomass (0.11 mg C g⁻ ¹ soil) treatments. The method of residue application resulted in a significant difference in C turnover between residues, with pea residue showing significant increase in C utilisation than mucuna and wheat. The pea residues, which had the lowest C:N, increased soil mineral N more than other treatments in both incorporated and mulched treatments. Lower mineralisation of N observed in residues of high C:N ratio compared to the control could be due to immobilisation of N. Therefore, understanding the nutrient dynamics of different crop residues could play an important role in the management of residues in different soil types. Based on these results it can be concluded that legume residues have the potential to improve soil fertility and crop yields in dryland farmers’ fields in Limpopo. Extension programs aimed at increasing farmers’ knowledge of the benefits of N fixation by legumes may increase their adoption and thereby improve soil fertility and maize yield. / Thesis (M.Ag.Sc.) -- University of Adelaide, School of Agriculture, Food and Wine, 2010

Made available in DSpace on 2014-06-11T19:32:42Z (GMT). No. of bitstreams: 0 Previous issue date: 2009-12-01Bitstream added on 2014-06-13T19:43:20Z : No. of bitstreams: 1 martinezuribe_ra_dr_botfca.pdf: 1544330 bytes, checksum: 1274ddb3255f2d39061085a14193c957 (MD5) / Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Universidade Estadual Paulista (UNESP) / 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)... / 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)

Com o objetivo de calibrar e avaliar o modelo ORYZA-APSIM para o arroz de terras altas no Brasil, foram conduzidos dezessete experimentos pela EMBRAPA Arroz e Feijão, em quatro regiões brasileiras (Santo Antônio de Goiás-GO, Sorriso-MT, Gurupi-TO e Teresina-PI) produtoras de arroz de terras altas, entre as safras de 2005/2006 e 2008/2009. O modelo foi calibrado e avaliado para a variedade cultivada de arroz de terras altas BRS-Primavera. Os dados da calibração foram obtidos de dois experimentos realizados na área experimental da EMBRAPA Arroz e Feijão, localizada no município de Santo Antônio de Goiás-GO, conduzidos em duas datas de semeadura durante a safra 2008/2009. As seguintes variáveis foram definidas na calibração: (i) unidades de calor efetivo diário, (ii) taxas de desenvolvimento fenológico para cada estádio, (iii) frações de massa de matéria seca das folhas, colmos, órgãos de armazenagem e colmos de reserva durante diferentes fases de desenvolvimento da cultura, (iv) taxa de crescimento inicial da área foliar e (v) parâmetros utilizados para determinar a área foliar específica. Na avaliação do modelo, foram comparados valores simulados com valores observados da massa de matéria seca total da parte aérea (MST) e de folhas verdes (MSF), índice de área foliar (IAF), produtividade e duração (número de dias) do período entre a emergência e o florescimento da cultura de arroz de terras altas. O modelo não apresentou desempenho satisfatório na simulação da duração das diferentes fases fenológicas de desenvolvimento para a região de Teresina-PI (os números de dias simulados foram, em média, oito dias superiores aos valores observados). O IAF, a MST e a MSF foram avaliados para as condições dos dois experimentos utilizados na calibração. As simulações do IAF diferiram dos valores observados nos dois experimentos, nos quais os valores finais da MST simulada foram semelhantes aos observados, mas diferiram dos observados durante a fase entre o florescimento e o ponto de maturidade fisiológica. A MSF simulada apresentou bom desempenho no primeiro experimento, mas regular no segundo experimento. No segundo experimento de campo, as variações da MSF, MST e o IAF foram causadas por um período de estresse hídrico simulado no modelo. O efeito do estresse hídrico foi superestimado no modelo. Comparando os valores simulados e observados de produtividade, por intermédio de uma regressão linear, verificou-se que o modelo (ORYZAAPSIM) pode determinar a ordem de grandeza da produtividade do arroz de terras altas ao nível de significância de 10%. / With the purpose of calibrating and evaluating the ORYZA-APSIM model for the upland rice in Brazil, seventeen field experiments were carried out at EMBRAPA Arroz e Feijão, in four upland rice Brazilian regions (Santo Antônio de Goiás-GO, Sorriso-MT, Gurupi and Teresina-PI), from 2005/2006 to 2008/2009 seasons. The model was calibrated and evaluated for an upland rice, cultivar BRS-Primavera. The calibration data were obtained from two field experiments carried out at the experimental area of EMBRAPA Arroz e Feijão, located at Santo Antônio de Goiás-GO, performed at two sowing dates during the 2008/2009 season. The following variables were defined in the calibration: (i) the effective heat daily units, (ii) phenological development rates at each crop stage, (iii) fractions of the dry matter of leaves, stems, storage organs and stems of reserves during the developmental crop stages, (iv) initial growth rate of leaf area and (v) parameters used to define the specific leaf area. In the model evaluation, simulated values were compared with observed values of total dry matter of shoot (DMS), dry matter of green leaves (DMGL), leaf area index (LAI), yield and duration (number of days) of the period from emergence to flowering of upland rice crop. The model did not present satisfactory performance to simulate the duration of different phenological phases of development for the Teresina-PI region (the numbers of simulated days were, in average, eight days greater than the observed values). The LAI, DMS and DMGL values were evaluated for the conditions of the two experiments used for calibration. The LAI simulations differed from the values observed in both experiments, where the final DMS simulated values were similar to those observed, but differed during the phase between flowering and physiological maturity point. The simulated DMGL showed a better performance in the first experiment, but regular in the second experiment. In the second field experiment, the DMS, DMGL and LAI variations were due to a period of drought stress simulated in the model. The model greatly penalized the growth of the culture under conditions of drought stress. The water stress effect was overestimated in the model. Comparing the simulated and observed values of yield, using a linear regression, it was verified that the model (ORYZA-APSIM) can define the magnitude order of upland rice productivity at 10% of significance level.

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Thesis (Ph.D. (Plant Production)) -- University of Limpopo, 2022 / Sustainable food production has been a major challenge in the era of climate change and a growing population in the twenty-first century. However, climate change scenarios such as extreme temperatures and fluctuations in annual precipitation continue to pose a great threat to agricultural production systems. On the other hand, anthropogenic activities such as conventional farming continue to contribute to climate change through the emission of greenhouse gases while not sustaining agricultural production. The Food and Agriculture Organization of the United Nations (FAO-UN) developed the concept of Climate-Smart Agricultural (CSA) production with the idea of securing food in the face of global change. No-tillage and intercropping systems are among the traditional practices that are advocated as components of climate-smart traditional practices, especially in the semi-arid regions of Africa like the Limpopo Province. Producing sorghum and cowpeas using CSA practices such as intercropping under no-tillage is envisaged to increase productivity and soil fertility under Limpopo Province's dryland conditions. However, there is still limited information on how grain sorghum-cowpea intercrop will respond in terms of growth, physiological productivity, and carbon dioxide emissions in the system, especially under no-tillage and different growing conditions. Furthermore, more field data is required for predictions of future scenarios using simulating crop models such as the Agricultural Production system sImulator (APSIM). Hence, a no-till Randomized Complete Block Design (RCBD) in a 2 x 4 x 2 factorial arrangement was conducted at two locations (Syferkuil and Ofcolaco) in the Limpopo Province during the 2018/19 and 2020/21 cropping seasons to generate data on sorghum and cowpea growth, physiology, productivity as well as carbon dynamics under planted and simulated intercropping system. Leaf gaseous exchange and leaf area index (LAI) were measured on fully developed grain sorghum and cowpea leaves in both the binary and sole cultures of sorghum and cowpea. The CO2 measurements were taken from each plot using a GMP343 CO2 probe along with an MI70 data logger. Aboveground biomass was collected for each crop from two plants at vegetative, flowering, physiological and harvest maturity and oven-dried at 65 oC for 48 hours. In the 2020/21 cropping season, cowpea at Ofcolaco failed to produce grain. Hence, only the grain yield of the 2018/19 cropping season from Ofcolaco is presented in this thesis. Grains collected for each crop from a 2.7m2 area were taken to the laboratory to determine grain yield and yield components. Harvest index (HI) and land equivalent ratio (LER) for each crop were also determined. In the laboratory, the total nitrogen (%) and natural abundance of 15N (δ15N‰) were determined using an isotope ratio mass spectrometer with an N analyzer. Growth (biomass) and yield (grain) data obtained from APSIM were compared with data collected from a two-year field experiment at Syferkuil. Multi-variate analysis of variance (ANOVA) model to fit each response variable using the Statistical Analysis System (21 SAS version 9.4). Mean separation was done where the means were different using the least significant difference (LSD) at probability levels of p ≤ 0.05. Intercropping system and the density of the companion crop cowpea had a significant (p ≤ 0.05) effect on the physiological responses of sorghum and cowpea, cowpea yield and yield components at the two experimental sites across seasons. However, grain yield and yield components of sorghum were not affected by intercropping or the density of cowpea. Only cultivars of sorghum were significantly different for grain yield and yield components. At Syferkuil, Enforcer produced the highest grain yield of 4338 kg ha-1 in 2018/19, while NS5511 accumulated the highest grain yield of 2120 kg ha-1 during the 2020/21 cropping seasons. At Ofcolaco, Enforcer and Avenger were observed to be relatively high-yielding cultivars with a mean grain yield of 2625 kg ha- 1 and 1191 kg ha-1 during the 2018/19 and 2020/21 cropping seasons, respectively. In the 2018/19 and 2020/21 cropping seasons, respectively, cowpea accumulated about 93% and 77% more grain yield in sole compared to binary culture. At Ofcolaco, about 96% more grain yield was obtained in sole compared to binary cultures during the 2018/19 cropping season. Furthermore, cowpea accumulated over 55% and 49% of grain yield when grown at high compared to low population density at Syferkuil and Ofcolaco, respectively. The investigation on the impact of the intercropping system on CO2 emissions and soil carbon stocks revealed that in 2018/19 at Syferkuil and 2020/21 at Ofcolaco, intercropping systems emitted 11% and 19% less CO2 respectively than the sole cropping systems. In both diverse agro-ecological sites, low cowpea density consistently resulted in higher CO2 emissions than high density. The sorghum-cowpea intercropping system significantly influenced the biological nitrogen fixation of cowpea. Intercropping was found to improve the biological nitrogen fixation of cowpea if a density of 74074 plants ha-1 is used. The APSIM model was able to capture the dynamics of biomass and grain yields in the sole and intercropping system under different densities of cowpea. The findings of this study revealed some useful insights. Firstly, biomass accumulation depended on the cultivar in intercrop as well as the density of cowpea. Secondly, cowpea at a density of 74074 plants ha1 was found to be a good crop to intercrop with grain sorghum as it did not show any significant variation in terms of grain yield and yield components of sorghum. The sorghum cultivar, Enforcer and NS5511 were the best performing cultivars in terms of grain yields at Syferkuil and Ofcolaco. Thirdly, the intercropping system under high cowpea density reduced CO2 emission rates while improving soil nitrogen (N) and carbon stocks. Based on the results of this study, grain sorghum-cowpea intercrop can be adopted as a component of a climate-smart practice to improve crop growth, physiology, as well as productivity compared to sole cropping. However, the grain sorghum cultivar and the density of cowpea should be taken into consideration as they affect the productivity of the two crops. The two seasons data generated from this study was useful in simulating the productivity of intercropping practice using APSIM. However, more field and weather data is required to run long-term simulations on intercropping as a component of the climate-smart method using crop modelling techniques. / National Research Foundation (NRF), Departments of Science and Innovation (DSI) and VLIR-IUC (Belgium)