Browsing by Autor "Roberto Miranda"

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A semi-quantitative approach for modelling crop response to soil fertility: evaluation of the AquaCrop procedure
(Cambridge University Press, 2014) Hanne Van Gaelen; Berhanu Abraha Tsegay; Nicole Delbecque; Nirman Shrestha; María Cruz García-González; Héctor Fajardo; Roberto Miranda; Eline Vanuytrecht; Berhanu Abrha; Jan Diels
SUMMARY Most crop models make use of a nutrient-balance approach for modelling crop response to soil fertility. To counter the vast input data requirements that are typical of these models, the crop water productivity model AquaCrop adopts a semi-quantitative approach. Instead of providing nutrient levels, users of the model provide the soil fertility level as a model input. This level is expressed in terms of the expected impact on crop biomass production, which can be observed in the field or obtained from statistics of agricultural production. The present study is the first to describe extensively, and to calibrate and evaluate, the semi-quantitative approach of the AquaCrop model, which simulates the effect of soil fertility stress on crop production as a combination of slower canopy expansion, reduced maximum canopy cover, early decline in canopy cover and lower biomass water productivity. AquaCrop's fertility response algorithms are evaluated here against field experiments with tef ( Eragrostis tef (Zucc.) Trotter) in Ethiopia, with maize ( Zea mays L.) and wheat ( Triticum aestivum L.) in Nepal, and with quinoa ( Chenopodium quinoa Willd.) in Bolivia. It is demonstrated that AquaCrop is able to simulate the soil water content in the root zone, and the crop's canopy development, dry above-ground biomass development, final biomass and grain yield, under different soil fertility levels, for all four crops. Under combined soil water stress and soil fertility stress, the model predicts final grain yield with a relative root-mean-square error of only 11–13% for maize, wheat and quinoa, and 34% for tef. The present study shows that the semi-quantitative soil fertility approach of the AquaCrop model performs well and that the model can be applied, after case-specific calibration, to the simulation of crop production under different levels of soil fertility stress for various environmental conditions, without requiring detailed field observations on soil nutrient content.
Caracterización del sistema de producción agrícola y evaluación de la calidad del suelo en el cultivo de soja (Glycine max) en tierras bajas de Bolivia
(2021) M. A. Lugo López; Vladimir Orsag; Roberto Miranda; Ligia García
La agricultura en Bolivia cuenta con varios sistemas de producción agrícola, donde el presente trabajo caracteriza las condiciones de producción agropecuaria en tierras bajas de Bolivia, identificando el manejo y deterioro de sus suelos. Así mismo, se cuenta con el índice de calidad de suelos el cual permite identificar el estado y las condiciones de los suelos de las tierras bajas. La investigación fue realizada en tres comunidades del municipio de Yapacani, Santa Cruz. El objetivo fue determinar el efecto del sistema de producción del cultivo de la soja, sobre el comportamiento de las propiedades físicas, químicas y biológicas, en áreas naturales y en parcelas de 3, 8, 12 y 23 años con la soja. Para la determinación del sistema de producción se realizó una serie de encuestas y entrevistas a los productores, identificando, las prácticas agronómicas, manejo de agroquímicos, entre otros. Para determinar el índice de calidad de suelos se analizó las propiedades físicas, químicas y biológicas, donde se realizó una ponderación de cada uno de ellas, llevándolos a una escala de 0 a 1. Los resultados obtenidos identifican que las comunidades cuentan con un sistema de producción agropecuario mixto extensivo. Donde los suelos son de textura franco limosa, arcillosa limosa y franco, a la vez existe una variación en la compactación del suelo y en la porosidad, contenido de nutrientes y producción de CO2, al determinar este índice, se demuestra una tendencia de reducción de los valores, donde las áreas naturales de 3 y 8 años de producción, cuentan con valores de 0.65, 0.67 y 0.66 y las parcelas de 12 y 23 años, obtuvieron valores menores (entre 0.58 y 0.49).
Comment on Araya et al.: “Simulating yield response to water of Teff (Eragrostis tef) with FAO's AquaCrop model” [Field Crops Research (2010) 116, 196–204]
(Elsevier BV, 2010) Sam Geerts; Dirk Raes; Ligia García; Roberto Miranda; Jorge Cusicanqui; Cristal Taboada; Jorge Mendoza; Ruben Huanca; Armando Mamani; Octavio Condori
Could deficit irrigation be a sustainable practice for quinoa (Chenopodium quinoa Willd.) in the Southern Bolivian Altiplano?
(Elsevier BV, 2008) Sam Geerts; Dirk Raes; Ligia García; Octavio Condori; Judith Mamani; Roberto Miranda; Jorge Cusicanqui; Cristal Taboada; Edwin Yucra; Jean Vacher
Introducing deficit irrigation to stabilize yields of quinoa (Chenopodium quinoa Willd.)
(Elsevier BV, 2008) Sam Geerts; Dirk Raes; Ligia García; Jean Vacher; Richard Mamani; Jorge Mendoza; Ruben Huanca; Bernardo Morales; Roberto Miranda; Jorge Cusicanqui
Modeling the potential for closing quinoa yield gaps under varying water availability in the Bolivian Altiplano
(Elsevier BV, 2009) Sam Geerts; Dirk Raes; María Cruz García-González; Cristal Taboada; Roberto Miranda; Jorge Cusicanqui; Teddious Mhizha; Jean Vacher
Rendimiento y acumulación de nitrógeno en la quinua (Chenopodium quinoa Willd) producida con estiercol y riego suplementario
(2012) Roberto Miranda; Reimar Carlesso; Maria Huanca; Pablo Mamani; Alex Borda
El rendimiento de un cultivo es una funcion de varios factores como el clima, manejo y adecuada oferta de nutrientes, entre ellos el Nitrogeno, que determina el contenido de proteina en el grano de quinua ( Chenopodium quinoa Willd). El objetivo del presente trabajo fue determinar el rendimiento de la quinua y la extraccion de nitrogeno por el grano y la planta, sometido a diferentes niveles de abono organico. El estudio fue llevado a cabo en las comunidades de Irpani y Callapa del Altiplano Sur y Central de Bolivia, durante la gestion 2007-2008 y 2008-2009. Se realizaron dos experimentos: en Irpani, el diseno experimental utilizado fue el de bloques aleatorizados con niveles de 0, 4, 8 y 12 Mg. ha -1 de estiercol y en condicion de riego suplementario durante la floracion y grano lechoso. En Callapa se utilizo un diseno de bloques aleatorizados con dosis de 0, 15 y 30 Mg. ha -1 de estiercol aplicado. La quinua mostro adecuada respuesta a la dosis de estiercol y a la aplicacion de agua, pese a ello, factores climaticos, como la ocurrencia de heladas determinaron su productividad. El contenido de nitrogeno en el grano tuvo una alta correlacion con el rendimiento de grano, tanto para el Altiplano Sur y Central. Palabras clave: Nitrogeno total; Chenopodium quinoa Willd; rendimiento; abonamiento organico; riego suplementario; Bolivia. Abstract The crop yield is a function of several factors such as climate, management and adequate supply of nutrients, including nitrogen, which determines the protein content in the grain of quinoa ( Chenopodium quinoa Willd). The aim of this study was to determine the yield of quinoa and nitrogen concentration in grain and plant, under different levels of organic fertilizer. The study was done in the communities of Callapa and Irpani located in South and Central Altiplano of Bolivia, respectively, during the periods 2007-2008 and 2008-2009. Two experiments were conducted: in Irpani, the experimental design was a randomized block with 0, 4, 8 and 12 Mg ha -1 of manure and supplementary irrigation conditions during flowering and tender grain. In Callapa, we used a randomized block design with doses of 0, 15 and 30 Mg ha -1 of manure. Quinoa showed adequate response to the dose of manure and water application, nevertheless, climatic factors, such as frosts determined the yield. The nitrogen concentration in grain was highly correlated with grain yield for both the South and Central Altiplano. Key words: Total Nitrogen; Chenopodium quinoa Willd; yield; organic fertilization, supplementary irrigation; Bolivia.
Simulating Yield Response of Quinoa to Water Availability with AquaCrop
(Wiley, 2009) Sam Geerts; Dirk Raes; Ligia García; Roberto Miranda; Jorge Cusicanqui; Cristal Taboada; Jorge Mendoza; Ruben Huanca; Armando Mamani; Octavio Condori
The modeling of yield response to water is expected to play an increasingly important role in the optimization of crop water productivity (WP) in agriculture. During 3 yr (2004–2007), field experiments were conducted to assess the crop response to water stress of quinoa ( Chenopodium quinoa Willd.) in the Bolivian Altiplano (4000 masl) under different watering conditions (from rain fed, RF, to full irrigation, FI). Crop physiological measurements and comparisons between simulated and observed soil water content (SWC), canopy cover (CC), biomass production, and final seed yield of a selected number of fields were used to calibrate the AquaCrop model. Subsequently, the model was validated for different locations and varieties using data from other experimental fields and from farmers' fields. Additionally, a sensitivity analysis was performed for key input variables of the parameterized model. AquaCrop simulated well the decrease of the harvest index (HI) of quinoa in response to drought during early grain filling as observed in the field. Further‐on, the procedure for triggering early canopy senescence was deactivated in the model as observed in the field. Biomass WP (g m −2 ) decreased by 9% under fully irrigated conditions compared with RF and deficit irrigation (DI) conditions, most probably due to severe nutrient depletion. Satisfactory results were obtained for the simulation of total biomass and seed yield [validation regression R 2 = 0.87 and 0.83, and Nash‐Sutcliff efficiency (EF) = 0.82 and 0.79, respectively]. Sensitivity analysis demonstrated the robustness of the AquaCrop model for simulation of quinoa growth and production, although further improvements of the model for soil nutrient depletion, pests, diseases, and frost are also possible.
Soil Salinity Mapping of Plowed Agriculture Lands Combining Radar Sentinel-1 and Optical Sentinel-2 with Topographic Data in Machine Learning Models
(Multidisciplinary Digital Publishing Institute, 2024) Diego Tola; Frédéric Satgé; Ramiro Pillco Zolá; Humberto Sainz; Bruno Condori; Roberto Miranda; Elizabeth Yujra; Jorge Molina‐Carpio; Renaud Hostache; Raúl Espinoza-Villar
This study assesses the relative performance of Sentinel-1 and -2 and their combination with topographic information for plow agricultural land soil salinity mapping. A learning database made of 255 soil samples’ electrical conductivity (EC) along with corresponding radar (R), optical (O), and topographic (T) information derived from Sentinel-2 (S2), Sentinel-1 (S1), and the SRTM digital elevation model, respectively, was used to train four machine learning models (Decision tree—DT, Random Forest—RF, Gradient Boosting—GB, Extreme Gradient Boosting—XGB). Each model was separately trained/validated for four scenarios based on four combinations of R, O, and T (R, O, R+O, R+O+T), with and without feature selection. The Recursive Feature Elimination with k-fold cross validation (RFEcv 10-fold) and the Variance Inflation Factor (VIF) were used for the feature selection process to minimize multicollinearity by selecting the most relevant features. The most reliable salinity estimates are obtained for the R+O+T scenario, considering the feature selection process, with R2 of 0.73, 0.74, 0.75, and 0.76 for DT, GB, RF, and XGB, respectively. Conversely, models based on R information led to unreliable soil salinity estimates due to the saturation of the C-band signal in plowed lands.