Calendário agrícola para a cultura do milho em Sinop (MT)

García, Ricardo Hernández; Dallacort, Rivanildo; Krause, Willian; Serigatto, Edenir Maria; Júnior, Cleonir Andrade Faria

doi:10.1590/s1983-40632013000200014

Cited by 4 publications

(3 citation statements)

References 10 publications

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“…The Central-West region, for example, ranks first nationally in corn and soybean production, with the State of Mato Grosso as the main producer of both crops, producing approximately 64% of maize and 60% of soybeans, with more than 4,498,000 and 9,518,000 hectares planted, respectively (CONAB, 2019). According to Garcia et al (2013), in a study carried out in the Sinop region (MT), the best growing season indicated for maize crop corresponds to the wet season during spring and summer, which favors high water availability to the soil due to rainfall and less probability of occurrence of consecutive dry days. The authors also affirm that in order to obtain a good income from the agricultural activity, it is important to know the conditions of the environment and the culture, from before planting until postharvest, as the rainfall and the temperature of the air, together with the photoperiod, are the main meteorological variables for productivity.…”

Section: Introductionmentioning

confidence: 99%

Distribution of rainfall probability in the Tapajos River Basin, Amazonia, Brazil

Santos¹,

Blanco²,

Júnior³

2019

Rev. ambiente água

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Studies on the probability of rainfall and its spatiotemporal variations are important for the planning of water resources and optimization of the calendar of agricultural activities. This study identifies the occurrence of rain by first-order Markov Chain (MC) and by two states in the Tapajos River Basin (TRB), Amazon, Brazil. Cluster analysis (CA), based on the Ward method, was used to classify homogeneous regions and select samples for checking the probability of rainfall occurrence by season. The historical series of daily rainfall data of 80 stations were used for the period 1990-2014. The CA technique identified 8 homogeneous regions and their probability of occurrence of rainfall, helping to determine which regions and periods have greater need of irrigation. Results of the probability of occurrence of dry and rainy periods in the TRB were used to define the dry (May thru September) and rainy seasons (October thru April). Elements of the matrix transition probabilities showed variability in relation to time and, in addition, the influence of geographical position of seasonal rainfall in determining dry and rainy periods at specific sites in the TRB.

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Section: Introductionmentioning

confidence: 99%

Distribution of rainfall probability in the Tapajos River Basin, Amazonia, Brazil

Santos¹,

Blanco²,

Júnior³

2019

Rev. ambiente água

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“…The reference ET data on Zenodo was previously published [ 33 ]. Dias et al, 2021 [ 33 ] calculated reference Et using a modified Penman-Monteith method [ [34] , [35] , [36] ] and weather data from INMET. Gray mold is the number one pest of castor production worldwide.…”

Section: Methodsmentioning

confidence: 99%

A site suitability analysis for castor (Ricinus communis L.) production during Brazil's second harvest incorporating disease prediction

Witt

Flynn

Zóz³

et al. 2023

Heliyon

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“…The knowledge of forecasting the probability of rainfall favors better agricultural planning and aids in the farmer's decision-making, which in turn reduces the risks in crop productivity (Garcia et al, 2013;Defiesta & Rapera, 2014;Barreto et al, 2015;Nyadzi et al, 2019), particularly in arid and semi-arid areas where water scarcity affects livelihoods and food security, as most of the available water comes from rainfall during the rainy season or groundwater close to the earth's surface (Abdalla et al, 2017). In this context, the objective was to analyze the probability of occurrence of monthly and annual rainfall, applying the probabilistic model Gama for the municipality of Chimoio, Mozambique.…”

Section: Introductionmentioning

confidence: 99%

Temporal dynamics of rainfall using the gamma distribution for the municipality of Chimoio, Mozambique

Cangela

Silva

Júnior

et al. 2023

Rev. Bras. Geog. Fis.

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Knowledge of rainfall patterns improves agricultural planning and assists in the development of public policies. Thus, the objective was to estimate the monthly and annual rainfall patterns for the municipality of Chimoio, Mozambique. For this, we apply to a series of 32 years (1989-2020) of monthly and annual scale data, the Gamma probability distribution function (GPD). The estimate of rain occurrence was performed at levels of 25, 30, 40, 50, 70, 75, 80, and 90% probability. We performed the adequacy of the GPD using the Kolmogorov-Smirnov (KS) adherence tests; Chi-square and Shapiro-Wilk, at 1% significance. Our study showed that the GPD met the KS test, indicating that it can be used to estimate rainfall patterns. Historically, the rainy season in Chimoio comprises December to March, and the months from April to November correspond to the dry season. We also show that there is a 75% probability of rainfall between 30 and 100 mm in the rainy season, with higher values in December (104.3 mm) and January (133.33 mm). Annually, the average rainfall is 1027.7 mm, with a probability of 40 and 50% of rainfall equal to 1065.3 and 990.1 mm, respectively. In the period studied, we noticed that 1997 (1724 mm) and 2006 (546.6 mm) were the wettest and driest years, respectively, showing the great variability of local rainfall patterns. The GPD adequately expressed the probability of rainfall in Chimoio, and can be an important tool for agricultural planning and public policy development in the municipality.

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Calendário agrícola para a cultura do milho em Sinop (MT)

Cited by 4 publications

References 10 publications

Distribution of rainfall probability in the Tapajos River Basin, Amazonia, Brazil

Distribution of rainfall probability in the Tapajos River Basin, Amazonia, Brazil

A site suitability analysis for castor (Ricinus communis L.) production during Brazil's second harvest incorporating disease prediction

Temporal dynamics of rainfall using the gamma distribution for the municipality of Chimoio, Mozambique

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