Soybean Productivity and Agrometeorological Variables Assessed from the perspective of Spatial and Circular Statistics

Edilza Martins Da Silva,Alex Paludo,Priscila Pigatto Gasparin,Luciana Pagliosa Carvalho Guedes,Jerry Adriani Johann,Willyan Ronaldo Becker

doi:10.5296/jas.v9i3.18697

Abstract

Climate change can affect the development of soybean cultivation, impacting your productivity. Thus, agrometeorological information is essential in order to improve productivity strategies. The objective of the paper was to analyze the influence and occurrence of seasonality of the following agrometeorological variables on soybean productivity: mean air temperature [TMean] (ºC), accumulated rainfall value [Rain] (mm), global solar radiation [Sr] (MJ m-2 day-1), and potential evapotranspiration [ETp] (mm), in ten-day variations of the the maximum vegetative development date (MVDD), in the 2011/2012 and 2013/2014 harvest years in the state of Paraná. The study was based on spatial distribution of variables, using univariate and bivariate Global Moran’s Indexes, and multivariate clustering analysis. To verify seasonality in the time distribution of the agrometeorological variables in the ten-day variations close to soybean MVDD, we used the circular statistics, through the mean vector length (R). Result it was identified regions of the state that have higher and lower rainfall and seasonality, also have higher and lowest productivity, respectively. That the variation in soybean productivity between harvest years was correlated with the agrometeorological variables, and rainfall volume is an important factor in productivity. The other agrometeorological variables occurred uniformly, especially in 2011/2012 harvest year, in the Northwest, Central-northern and West mesoregions. Furthermore, there was clustering of regions with similar spatial distribution of the evapotranspiration and rainfall variables in 2aDMDV2d in the 2011/2012 and 2013/2014 harvest year, showed the same spatial distribution of the agrometeorological variables and the productivity variable.

Highlights

Soybean has been the protagonist in the increase of grain production in Brazil in recent years
That the variation in soybean productivity between harvest years was correlated with the agrometeorological variables, and rainfall volume is an important factor in productivity
The results showed that the variation in productivity could be explained by rainfall, where the occurrence of consecutive days without rain during the crop cycle exerted a negative impact on soybean productivity

Summary

Introduction

Soybean has been the protagonist in the increase of grain production in Brazil in recent years. Paranáis the second state with the highest soybean production, with a mean production of 15 million tons in the last 10 years and with a standard deviation of 3 million tons, that is, the mean productivity across the harvest years showed moderate dispersion; this was confirmed by the value of 20% of the variation coefficient (VC). 2021, Vol 9, No 3 the fourth largest soybean producer, with 16 million tons in the 2018/2019 harvest year, producing more than China, which totaled 15.7 million tons (USDA, 2021). The main aspects that affect soybean productivity are agrometeorological factors such as water availability, temperature, photoperiod and evapotranspiration (Klosowski, 1997), as they influence the development of plants in all their phenological phases. Water availability is one of the most critical factors for soybean development, especially during germination-emergence and flowering-filling periods. In addition to the need for an adequate water volume in these periods, it must occur uniformly throughout the crop cycle so as to reach maximum productivity, according to its genetic potential (Farias et al, 2007)

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Conclusion