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--- opensci:2023:rdatanal:model:modiza [2023/05/16 20:58] – izael
+++ opensci:2023:rdatanal:model:modiza [2024/03/23 20:17] (atual) – edição externa 127.0.0.1
@@ Linha 1: / Linha 1: @@
-The exploratory analysis shown an increase in sugarcane harvest area after the year of 2000, which also increase the sugarcane production in Brazil. However, the yield does not follow this variation ([[http://guarani.esalq.usp.br/dokuwiki/doku.php?id=opensci:2023:rdatanal:explor:expiza| Exploratory analysis]]).
+The exploratory analysis showed an increase in the sugarcane harvest area after the year of 2000, which also increase the sugarcane production in Brazil. However, the yield does not follow this variation ([[http://guarani.esalq.usp.br/dokuwiki/doku.php?id=opensci:2023:rdatanal:explor:expiza| Exploratory analysis]]).
-Therefore, modeling the yield values by municipality with year (Figure 1) shown that since the start of the database an increase in yield. The model is significative (p<0.001) and with positive slope (a= 0.369) showing the positive correlation. However, the mean values of each year had more variation. This, the mean values shown a decrease in yield after the year 2010 (Figure 1).
+Therefore, modeling the yield values by municipalities with the year (Figure 1) shows that since the start of the database an increase in yield. The model is significative (p<0.001) and with positive slope (a= 0.369) showing a positive correlation. However, the mean values of each year had more variation. This, the mean values show a decrease in yield after the year 2010 (Figure 1).
 {{:opensci:2023:rdatanal:model:yield_x_season_br.png?600|}}
-Figure 1. Relationship between sugarcane yield data by municipality with the season.
+Figure 1. Relationship between sugarcane yield data by municipalities with the season. The red line represents the fitted curve, and the blue line represents the mean yield of each season.
+This decrease in yield after 2010, was followed by an increase in yield between 2000 and 2009. Thus, with we split the linear model in two periods before 2000 and after 2000. These results show that in general, after 2000 there is also an increase in yield, with significance (p<0.001). However, in this case, the slope of equation (a=0.28), after 2000, is lower than the model considering the yield before 2000 (a=0.334) (Figure 2). With that, after 2000 the rate of yield increases by season was lowered.
+{{:opensci:2023:rdatanal:model:yield_x_season_br_split.png?600|}}
+Figure 2. Relationship between sugarcane yield data by municipalities with the season, split in two periods. 0 represents before 2000 and 1 after 2000.
+São Paulo had the higher sugarcane planted area since the start of the database analysis, and had a production representing more than 40% of the Brazilian production. Thus, deep analyzing this variation in yield, plotting the variation in yield, split by periods, only for the state of São Paulo, shows that after 2000 there is a trend to decrease of yield, due to an equation's slope negative (a=0.127) which represents a negative correlation. Different from the model considering all municipalities.
+This point raises a hypothesis that the increase in yield after 2000 was caused by the frontier municipalities, that began the production of sugarcane near the season of 2000. These frontier areas are more susceptible to a yield increase due to the input of technology.
+{{:opensci:2023:rdatanal:model:yield_x_season_br_split_sp.png?600|}}
+Figure 3. Relationship between sugarcane yield data by municipalities with the season split into two periods. 0 represents before 2000 and 1 after 2000, for the state of São Paulo.
+{{:opensci:2023:rdatanal:model:compare_estabilished_frontier.png?600|}}