ZONEAMENTO AGRÍCOLA DE RISCO CLIMÁTICO DA REGIÃO DO MÉDIO CURSO DO RIO PARAÍBA / ZONING OF CLIMATIC RISK OF THE MIDDLE CURSE OF RIO PARAÍBA REGION

Cotton is cultivated in the North and West of Parana State, southern Brazil, under conditions of climatic risk variable in space and time. Risks of temperature below 15ºC at the establishment period, daily average temperature below 20ºC at the stage of cotton boll opening, and soil water deficit for both plant establishment and flowering periods, were estimated to identify homogeneous zones with sowing periods of lower climatic risk. The time interval with adequate temperature, associated with minimum risks of the other factors and yield data from field experiments allowed the identification of seven distinct zones, with best sowing periods ranging from September 20 to November 20. Official credit to the farmers is conditioned by the Central Bank of Brazil upon following these recommendation of best sowing periods for each municipality.

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SMALLHOLDER FARMERS’ RESOURCE ALLOCATION DECISIONS IN A MAIZE-FARMING SYSTEM UNDER CLIMATE RISKS IN MALAWI

AGROFOR ◽

10.7251/agreng2101086m ◽

2021 ◽

Vol 6 (1) ◽

Author(s):

Ruth MAGRETA ◽

Henderson NG’ONG’OLA ◽

Julius MANGISONI ◽

Kennedy MACHILA ◽

Sika GBEGBELEGBE

Keyword(s):

Resource Allocation ◽

Smallholder Farmers ◽

Farming Systems ◽

The Body ◽

Research Station ◽

Climatic Data ◽

Climatic Risk ◽

The Impact ◽

Allocation Decisions ◽

Resource Allocation Decisions

Using household data from Lilongwe districts, along with crop phenology, agronomic management and climatic data from Chitedze Research Station, the Target-MOTAD and DSSAT-CSM models examined the resource allocation decisions of smallholder farmers in maize farming systems under climate risk in Malawi. Specific aims were to evaluate the ability of DSSAT to predict and collate DTM and non-DTM yields under climatic risk and to use a bio-economic procedure developed using DSSAT and Target-MOTAD to explore the impact of climatic risk on allocation of resources to DTM and non-DTM production. The paper argues that higher average yields observed from DTM varieties make it the most optimal maize production plan, in maximizing household incomes, food security, and minimizing deviations from the mean while meeting the set target incomes of farmers compared to non-DTM varieties. The multidisciplinary nature of this paper has contributed to the body of research by providing a powerful analytical procedure of modelling farmers’ resource allocation decisions in maize based farming systems in Malawi. This study necessitates the use of a combination of biophysical and economic procedures when evaluating promising lines prior to variety release in order to identify the high yielding variety that will continuously bring sustained profits to the farmers amidst climate change.

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Climatic risk for potato late blight in the Andes region of Venezuela

Scientia Agricola ◽

10.1590/s0103-90162008000700007 ◽

2008 ◽

Vol 65 (spe) ◽

pp. 32-39 ◽

Cited By ~ 5

Author(s):

Beatriz Ibet Lozada Garcia ◽

Paulo Cesar Sentelhas ◽

Luciano Roberto Tapia ◽

Gerd Sparovek

Keyword(s):

Late Blight ◽

Disease Risk ◽

Risk Index ◽

Disease Model ◽

Great Part ◽

Potato Late Blight ◽

Geographical Information ◽

Climatic Risk ◽

The Andes ◽

Andes Region

Potato is an important crop for Venezuelan agriculture. However, its production is highly affected by late blight (Phytophtora infestans), since weather is commonly favorable for this disease. The aim of this study was to determine the sowing dates of low climatic risk for potato late blight in the Andes region of Venezuela, with an agrometeorological disease model and geographical information system (GIS) tools. The disease model used in this study was developed by Hyre (1954) which requires daily rainfall and temperature data which were obtained from 106 weather stations, located at the States of Mérida, Táchira, and Trujillo, for a period of 31 years. Hyre's model was applied for all stations obtainig the following variables: number of disease favorable days (DFD); number of periods with ten consecutive favorable days, named disease occurrence (O); and number of sprays required for disease control (S). These variables were used to calculate the Maximum Risk Index (MRI) and the Probable Risk Index (PRI). The interpolation of these indexes was used to generate maps of climatic risk for each sowing date. MRI and PRI maps showed that the highest climatic risk for potato late blight occurrence was during the rainy season, from May to July, decreasing during dry and mid seasons. However, high disease risk variability was observed for all seasons. The maps generated by coupling an agrometeorological disease model and GIS also show that in great part of potato areas of Andes region the number of sprays could be reduced, but more investigations about that must be carried out.

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