Fábio Ricardo Marin

CONSTRUÇÃO E AVALIAÇÃO DE PSICRÔMETRO ASPIRADO DE TERMOPAR

The construction of a low cost aspirated thermocouple psychrometer made of PVC tubes is described. The instrument can easily be connected to dataloggers. The aspiration is made by fans used in microcomputers and temperatures measured with cooper-constantan thermocouples. A cotton string was used to make the wet junction. Its perfomance was evaluated in comparison to an Assman aspirated psychrometer and a Vaisala Inc. capacitive higrometer, in natural and controlled environments. The results show a good agreement between measures, allowing air vapour, relative humidity, temperature and specific humidity gradients to be determined using the proposed psychrometer.

Parametrização e avaliação do modelo DSSAT/Canegro para variedades brasileiras de cana‑de‑açúcar

The objective of this work was to parameterize and to evaluate the DSSAT/Canegro model for five Brazilian sugarcane varieties. The parameterization was done using biometric and growth data from the varieties CTC 4, CTC 7, CTC 20, RB 86‑7515, and RB 83‑5486, obtained in five Brazilian locations. Local sensitivity analysis was performed for the main parameters. Model parameterization was done using the generalized likelihood uncertainty estimation (Glue) method. The predictions were evaluated using the coefficient of determination (R²), Willmotts D‑index, and the root mean square error (RMSE) as statistical indexes. CTC varieties showed D values ranging from 0.870 to 0.944 for leaf area index, stalk height, tillering, and sucrose content. The RB 83-5486 variety showed similar results for sucrose content and fresh matter mass of stalks, whereas the RB 86-7515 variety showed values ranging from 0.665 to 0.873 for all variables analyzed.

Sugarcane model intercomparison

Sugarcane is one of the worlds main carbohydrates sources. We analysed the APSIM-Sugar (AS) and DSSAT/CANEGRO (DC) models to determine their structural differences, and how these differences affect their predictions of crop growth and production. The AS model under predicted yield at the hotter sites, because the algorithm for computing the degree-days is based in only one upper cardinal temperature. The models did not accurately predict canopy and stalk development through time using growth parameters values developed from observed data, in combination with previously determined RUE for the cultivars. In response to elevated CO2, both predicted higher yields, although AS showed higher sensitivity to CO2 concentration, rainfall and temperature than DC. The Mean of simulations from both models produced better estimations than predictions from either model individually. Thus, applying the two models (in their current form) is likely to give the more accurate predictions than focusing on one model alone. APSIM-Sugar and DSSAT/CANEGRO under predicted biomass when calibrated with crop growth data, but keeping previous RUE values.AS showed higher sensitivity to rainfall, CO2 and temperature reduction than DC.The mean of simulations from both models produced better estimations than predictions from either model individually.Applying?two models is likely to give more accurate predictions than focusing on one model alone.

EVAPOTRANSPIRATION AND IRRIGATION REQUIREMENTS OF A COFFEE PLANTATION IN SOUTHERN BRAZIL

Crop evapotranspiration (ETc) was measured as evaporative heat flux from a drip-irrigated coffee ( Coffea arabica ) plantation with 5-year-old trees using the Bowen ratio-energy balance technique. Crop transpiration (T) was determined with the stem heat balance method. Irrigation requirements were determined by comparing the ETc and T with reference evapotranspiration (ETo) derived from the Penman-Monteith equation and expressed as the ETc/ETo (Kc) and T/ETo (Kcb) ratios. Also, relationships were established between ETc and T and class A pan evaporation (ECA). The influence of inter-row vegetation on ETc was analysed, since the measurements were taken in a period of transition between dry-wet seasons. The average Kc value obtained was 1.00. The strong coupling of coffee plants to atmospheric conditions and high sensitivity of coffee plants to large vapour pressure deficits and air/leaf temperatures caused variations in Kcb in relation to ETo. Kcb ranged from 0.67, when ETo exceeded 4 mm d −1 , to 1.27 when ETo was less than 2 mm d −1 . When vegetation did not occupy the inter-row ground spaces, T represented about 0.87ETc, but 0.68ETc when ground vegetation filled the inter-row spaces.

Radiation balance of coffee hedgerows

A radiacao, tanto de ondas curtas como de ondas longas, absorvida por um renque de plantas de uma cultura que cobre de forma descontinua o solo, e uma variavel importante para os estudos das trocas de massa e de energia com a atmosfera. Este trabalho apresenta um dispositivo que movimenta oito saldo-radiometros dispostos em torno de um renque. O movimento de ida e volta ao longo de um trecho de um renque, permite a integracao do saldo de radiacao na superficie de um cilindro nocional de medidas, representando o balanco de radiacao (Rnc) do trecho amostrado. O equipamento apresentou um bom desempenho quando empregado em dois cafezais, mostrando potencial para a realizacao de medidas de campo, com valores medidos confiaveis. Foram obtidas boas correlacoes entre Rnc e a irradiância solar global e, tambem, entre Rnc e o saldo de radiacao medido sobre gramado e sobre o cafezal, para dados obtidos em intervalos de 15 minutos, diurnos e diarios. Uma adaptacao da Lei de Beer tambem foi avaliada para modelagem de Rnc, resultando valores superestimados em 10% em relacao aos valores integrados em 15 minutos pelo dispositivo movel , mas para os integrados no periodo diurno a concordância entre dados estimados e medidos nao foi boa.

Eficiência da produção de cana‑de‑açúcar em duas safras no Estado de São Paulo

A conceptual framework for crop production efficiency was derived using thermodynamic efficiency concept, in order to generate a tool for performance evaluation of agricultural systems and to quantify the interference of determining factors on this performance. In Thermodynamics, efficiency is the ratio between the output and input of energy. To establish this relationship in agricultural systems, it was assumed that the input energy is represented by the attainable crop yield, as predicted through simulation models based on environmental variables. The method of FAOs agroecological zones was applied to the assessment of the attainable sugarcane yield, while Instituto Brasileiro de Geografia e Estatistica (IBGE) data were used as observed yield. Sugarcane efficiency production in Sao Paulo state was evaluated in two growing seasons, and its correlation with some physical factors that regulate production was calculated. A strong relationship was identified between crop production efficiency and soil aptitude. This allowed inferring the effect of agribusiness factors on crop production efficiency. The relationships between production efficiency and climatic variables were also quantified and indicated that solar radiation, annual rainfall, water deficiency, and maximum air temperature are the main factors affecting the sugarcane production efficiency.

Mudanças climáticas e a cana-de-açúcar no Brasil: Fisiologia, conjuntura e cenário futuro

Com base na revisao de literatura, o manuscrito analisa qualitativamente um futuro cenario para a cana-de-acucar no Brasil, com base na tendencia de expansao da cultura observada ao longo da ultima decada, a conjuntura atual do setor e as projecoes de mudancas climaticas globais regionalizadas para este seculo. O principal foco foi associar os resultados cientificos sobre a fisiologia da cana-de-acucar e suas respostas a elevacao na concentracao de dioxido de carbono atmosferico e eficiencia de uso da agua com as perspectivas socioeconomicas do setor canavieiro do Brasil. Provaveis efeitos sobre plantas daninhas, pragas e doencas da cana-de-acucar, tambem foram abordados. A base do conhecimento disponivel na literatura indica que a cana-de-acucar apresentaria uma resposta positiva em relacao aos cenarios de mudancas climaticas mais provaveis para o Brasil, tanto pela resposta direta da fotossintese a elevacao na concentracao do dioxido de carbono quanto ao aumento da eficiencia de uso da agua. Contudo, e provavel que o manejo na cultura necessite de adaptacoes uma vez que plantas daninhas e doencas poderiam ser favorecidas pelas condicoes futuras.

Simulação do efeito do manejo da palha e do nitrogênio na produtividade da cana-de-açúcar

The objective of the study was to model the growth and productivity of green and burnt sugarcane harvesting systems, under three nitrogen fertilizer levels (60, 120 and 180 kg ha-1). APSIM-Sugar crop model was previoulsy calibrated based on two field experiments conducted in Piracicaba,SP and Salinas, MG, with the cultivar SP80-1842. The sensitivity of the model was evaluated for the parameters of soil and variety, especially those related to the soil organic matter dynamics and nitrogen. The model simulated well the sugarcane growth and yield in the evaluated environments. Simulations showed that sugacarne yield being highly dependent on trash management. Trash removal from fields would ultimately decrease the crop yield. Simulations also revealed that the nitrogen doses as high as 180 kg ha-1 would not be enough to overcome the yield lost due to trash removal.

How can crop modeling and plant physiology help to understand the plant responses to climate change? A case study with sugarcane

Global climate changes are now well accepted to happen and can likely impact agriculture. Process-based dynamic crop models are able to estimate a range of crop responses to the environment and to assess the biophysical effects of future climate scenarios on crop growth and yield. They are hence scientifically accepted as a predictor of future agricultural scenarios, and the multi-model approach has shown the best performance in such prediction activities. The need of several models for such studies is mainly a consequence of the different physiological and physical approaches applied by model developers. Physiological processes are in fact essential elements for improving plant modeling, and most of the model weakness would be overcome by better understanding of the main physiological aspects related to plant growth and development. Sugarcane (Saccharum spp.) is an important crop for coping with climate change mitigation as a source of bioenergy and food. In this paper we aim to demonstrate how important is plant physiology for advancing the process-based crop models by briefly reviewing the history of the modeling along the last five decades and presenting the key physiological process considered in crop models. The paper was based in the DSSAT/CANEGRO sugarcane model and a set of field experiments for exemplifying some model responses to key climatic variables expected to vary in the following decades. Those responses were discussed under the light of plant physiology knowledge. We selected two sites in the State of Sao Paulo for an exercise of local sensitivity analysis. As air CO2 concentration is the most likely environmental variable expected to change, we stressed the CO2 effects on plant photosynthesis and water use to highlight the model strengths and opportunities for model improvements based on plant physiology findings.

Process-based simple model for simulating sugarcane growth and production

Dynamic simulation models can increase research efficiency and improve risk management of agriculture. Crop models are still little used for sugarcane (Saccharum spp.) because the lack of understanding of their capabilities and limitations, lack of experience in calibrating them, difficulties in evaluating and using models, and a general lack of model credibility. This paper describes the biophysics and shows a statistical evaluation of a simple sugarcane processbased model coupled with a routine for model calibration. Classical crop model approaches were used as a framework for this model, and fitted algorithms for simulating sucrose accumulation and leaf development driven by a source-sink approach were proposed. The model was evaluated using data from five growing seasons at four locations in Brazil, where crops received adequate nutrients and good weed control. Thirteen of the 27 parameters were optimized using a Generalized Likelihood Uncertainty Estimation algorithm using the leave-one-out cross-validation technique. Model predictions were evaluated using measured data of leaf area index, stalk and aerial dry mass, and sucrose content, using bias, root mean squared error, modeling efficiency, correlation coefficient and agreement index. The model well simulated the sugarcane crop in Southern Brazil, using the parameterization reported here. Predictions were best for stalk dry mass, followed by leaf area index and then sucrose content in stalk fresh mass.