Modelos de simulação da cultura do milho - uso na determinação das quebras de produtividade (&lt;em&gt;Yield Gaps&lt;/em&gt;) e na previsão de safra da cultura no Brasil

Duarte, Yury Catalani Nepomuceno

doi:10.11606/d.11.2018.tde-15052018-104958

Cited by 3 publications

(7 citation statements)

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“…There was superiority in the performance of strategies that used fewer average climate variables in the simulations, and strategy S1 (c = 0.92, MAE = 204 kg ha -1 , RMSE = 58 kg ha -1 ) was the best, followed by strategy S2 (c = 0.86, MAE = 267 kg ha -1 , RMSE = 76 kg ha -1 ). These results are similar to those found by Duarte (2018), who used a historical series of meteorological data from 1980 to 2010 and average data for 30 years for each day and tested harvest forecast strategies for first and second maize harvests with average data at 5, 25, 45, 65, and 85 days from harvest. The best performing strategy was 5 days, and the worst was 85 days.…”

Section: Resultssupporting

confidence: 86%

“…The worst productivity performance was observed for strategies S1 and S2. Strategies S4, S5, S6, and S7 showed a strong flattening of variability and amplitude due to the use of a high amount of average meteorological data, as also observed by Duarte (2018). These results differ from those of Martins (2007), who used the ETA climate forecast model combined with climate data from the years of their simulations and suggested that the maize yield forecast can be satisfactorily made between 45 and 60 days before harvest.…”

Section: Resultsmentioning

confidence: 55%

“…One of the management practices to increase productivity is the selection of an optimal sowing time, which has a significant impact on the productive potential of the crop, particularly in rainfed agriculture. Adjusting the sowing date to a more favorable time for a specific location is a cost-effective way for farmers to improve their yields Crout;Hoogenboom, 2013;Andarzian et al, 2015;Duarte, 2018).…”

Section: Introductionmentioning

confidence: 99%

“…Forecasting agricultural production is critical for harvest planning, storage, and marketing (Duarte, 2018), and helps farmers increase their efficiency. By forecasting the productivity of crops before harvest, farmers can plan for their transportation and storage, optimize their sales strategies, and reduce or avoid potential losses related to production.…”

Section: Introductionmentioning

confidence: 99%

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Off-Season Maize Yield Forecasting for Different Sowing Dates

Bongiovani,

Costa,

Quiloango-Chimarro

et al. 2023

EnergAgric

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Brazil is the world's third-largest maize producer. Its yield is influenced by climate, soil conditions, management and their interactions. Identifying the most suitable sowing window and using yield forecasting systems allows for increased yields and better harvest management. Crop simulation models can be used to assess crop responses to various conditions. This study aimed to identify the most favorable planting date for off-season maize by using the DSSAT CSM-CERES-Maize model for Jataí, Goiás state. Using meteorological data from 1986 to 2015, eight productivity forecasting strategies were tested. The results of the model application at different sowing dates indicated that the dates in January tended to present a more favorable attainable yield (Ya), i.e., values closer to the potential yield (Yp) of the crop, whereas in February, Ya were affected by lower precipitation from April to June. The best date for maize sowing was January 25th. The simulations indicated the possibility of predicting the off-season maize productivity in Jataí with high precision and accuracy up to 30 days prior to harvest (R² ≥ 0.81, d ≥ 0.90, and c ≥ 0.81).

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Section: Resultssupporting

confidence: 86%

Section: Resultsmentioning

confidence: 55%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Off-Season Maize Yield Forecasting for Different Sowing Dates

Bongiovani,

Costa,

Quiloango-Chimarro

et al. 2023

EnergAgric

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“…A abordagem que tem sido recomendada em resposta a essa questão é o uso de modelos em conjunto ("ensemble"), que considera a média entre os modelos, tendo como objetivo minimizar as incertezas associadas a cada um dos modelos quando estes são empregados individualmente (ASSENG et al, 2013;BASSU et al, 2014;GRASSINI et al, 2015, BATTISTI; SENTELHAS; BOOTE, 2017) e a avaliar a sensibilidade dos modelos à variações do clima (MARIN et al, 2015;LI et al, 2015). O uso do "ensemble" tem se mostrado relevante na estimativa da produtividade de diferentes culturas (ASSENG et al, 2013;MARTRE et al, 2014;DUARTE, 2018) e na compreensão das respostas dos modelos às condições de clima (BATTISTI; SENTELHAS; BOOTE, 2017; BENDER, 2017).…”

Section: Introductionunclassified

Mudanças climáticas, seus impactos na cultura da mandioca no Semiárido Brasileiro e estratégias de manejo para mitigação das perdas

Bongiovani¹

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Climate change, its impacts on cassava production in Brazilian Semi-arid region and management strategies for mitigation of losses Cassava is one of the most important crops in tropical countries. Due to its tolerance to adverse weather and soil conditions, it has been cultivated as a strategic crop in semi-arid regions. With the predictions of future climate changes, it is imperative to understand in which ways cassava production might be affected in these regions, in order to anticipate crucial actions to prevent and/or attenuate possible impacts and prepare the population to deal with that. In this context, crop simulation models are effective tools to quantify the future climate effect on crop yields. The objectives of this study were: i) to calibrate and evaluate the cassava simulation models DSSAT CSM-CROPSIM-Cassava and CSM-MANIHOT-Cassava to simulate the yields of the BRS Formosa cassava cultivar and analyze the sensitivity of these models; ii) to apply the DSSAT CSM-CROPSIM-Cassava model to determine cassava yields in the Brazilian Semi-arid region (SAB), under actual (1980-2010) and future climate projections, in medium (2040-2070) and long (2070-2100) terms, for intermediate (RCP4.5) and high (RCP8.5) greenhouse gases emissions (GHGs) scenarios, and to elaborate a vulnerability index (IV) for cassava production in the region; iii) to apply the DSSAT CSM-CROPSIM-Cassava model to evaluate potential management strategies, associated to planting dates and irrigation, in order to minimize possible climate impacts, in four locations of SAB. The DSSAT CSM-CROPSIM-Cassava and CSM-MANIHOT-Cassava models presented good performance for simulating Cassava BRS Formosa yields, with mean absolute error (MAE) of 1193 and 1315 kg ha-1 , and c index of 0,87 and 0,81, respectively. The ensemble had a better performance than CSM-MANIHOT-Cassava, but worse than CSM-CROPSIM-Cassava, presenting an intermediary MAE, of 1239 kg ha-1 , and c index = 0,85. The sensitivity analysis showed that both models are sensitive to variations in mean air temperature and [CO2], in a direct and inverse way, respectively. As for the rainfall, CSM-MANIHOT-Cassava presented low sensitivity, especially for the driest region, whereas CSM-CROPSIM was very responsive. In general, the CSM-CROPSIM model presented higher yield deviations in relation to the variations of air temperature, rainfall and [CO2] than CSM-MANIHOT-Cassava model, being more suitable for evaluation of climate change impacts on cassava yield. The cassava yields were reduced in all future scenarios, reaching-29% for potential yield (PP) and-22% for attainable yield (PA), at the most pessimist one. The PA maps showed that the areas of the regions with lowest yields at the actual scenario (states of PI, CE, PE and BA) tend to remain unchanged at future scenarios, while the ones with the highest yields (Southeast of BA and North of MG) tend to be reduced. The vulnerability of cassava production in SAB to climate change was greater at long term (2070-2100), in both GHGs emission scena...

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Ácidos Húmicos/Fúlvicos E Nitrogênio Na Produtividade Da Cultura Do Milho

Batista

Adami

Ferreira

et al. 2018

Revista Brasileira De Engenharia De Biossistemas

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RESUMO O milho possui grande importância para a economia mundial, neste contexto cada vez mais busca-se alternativas para aumentar o rendimento de grãos. O objetivo do estudo foi avaliar os componentes morfológicos e a produtividade de grãos do milho cultivado em diferentes tratamentos com utilização isolada e/ou associada de nitrogênio e ácidos húmicos/fúlvicos. O estudo foi conduzido na Universidade Tecnológica Federal do Paraná, Campus de Dois Vizinhos, PR, durante a safra 2017/2018. Como fonte de nitrogênio foi utilizado uréia e de ácidos húmicos/fúlvicos um produto comercial (bioestimulante). Utilizou-se delineamento de blocos ao acaso com sete tratamentos e quatro repetições, sendo: 1: aplicação de ½ dose do bioestimulante em V4 + aplicação de ½ dose em V8; 2: aplicação de dose recomenda do bioestimulante em V4; 3: aplicação de dose recomenda do bioestimulante em V8; 4: nitrogênio; 5: nitrogênio + aplicação de dose recomenda do bioestimulante em V8; 6: nitrogênio + aplicação de dose recomenda do bioestimulante em V4; 7: sem nitrogênio e sem bioestimulante (testemunha). Os ácidos foram aplicados via foliar e o nitrogênio (N) (170 Kg ha-1) em cobertura em V4. Foram avaliados no final do ciclo da cultura as características morfológicas de planta e os componentes de rendimento. Os dados foram submetidos análise de variância e quando constado significância, aplicou-se teste de Scott-Knott a 5% de probabilidade. A utilização de ácidos húmicos/fúlvicos não interferiu nas características morfológicas das plantas, tampouco sobre os componentes de rendimento do milho e produtividade do milho, seja utilizado isoladamente ou associado com N. O uso de N via uréia em cobertura proporciona elevação do número de grãos por fileira e grãos por espiga, massa de mil grãos, produtividade por espiga e área.

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Modelos de simulação da cultura do milho - uso na determinação das quebras de produtividade (<em>Yield Gaps</em>) e na previsão de safra da cultura no Brasil

Cited by 3 publications

References 42 publications

Off-Season Maize Yield Forecasting for Different Sowing Dates

Off-Season Maize Yield Forecasting for Different Sowing Dates

Mudanças climáticas, seus impactos na cultura da mandioca no Semiárido Brasileiro e estratégias de manejo para mitigação das perdas

Ácidos Húmicos/Fúlvicos E Nitrogênio Na Produtividade Da Cultura Do Milho

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