Abstract

ABSTRACT: This study determined the meteorological variable that most contribute to the productivity of sugarcane stalks in the northwest and central regions of Rio Grande do Sul. The following sugarcane genotypes were used: UFSM XIKA FW, UFSM LUCI FW, UFSM PRETA FW, UFSM DINA FW, UFSM MARI FW, and IAC87-3396. The UFSM cultivars originate from a mutation process in the breeding program conducted at the Federal University of Santa Maria, Frederico Westphalen campus, and have low temperature tolerance. The productivity-associated morphological characters included in the models were average stem diameter, average stem number per meter of furrow, and average stem height. The following meteorological variables were used: minimum air temperature, precipitation, incident solar radiation, and accumulated thermal sum. Pearson’s correlation, canonical correlations, and Stepwise regression were performed between morphological characters and meteorological variables: minimum air temperature had the greatest influence on sugarcane productivity in the studied regions, and accumulated thermal sum showed the highest correlation and contributed most to stem diameter and average stem height. Thus, the models indicated that the growth of sugarcane is positively associated with the accumulated thermal sum, and sugarcane can be cultivated at the studied regions.

Highlights

  • Sugarcane (Saccharum ssp.) is one of the main crops of agronomic interest and is grown worldwide (CAPUTO et al, 2008)

  • The soil of the experimental area is classified as Latossolo Vermelho aluminoférrico, with 67% clay, 2.5% organic matter (OM), 2.8 mg dm-3 of P, 139 mg dm-3 of K, 14.1 cmolc dm-3 of chlortetracycline (CTC), and base saturation of 55.9%

  • The water deficit observed in both the locations did not coincide with the critical development periods of the crop

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Summary

Introduction

Sugarcane (Saccharum ssp.) is one of the main crops of agronomic interest and is grown worldwide (CAPUTO et al, 2008). Brazil is one of the largest producers of sugarcane, with about 8.4 million hectares (ha) of planted area, production of 642.7 million tons, and average productivity of 76.1 tons ha-1 in the 2019/2020 crop season (CONAB, 2020). Sugarcane productivity can be simulated using variables such as stem diameter, stem number per linear meter of furrow, and plant height (MARTINS & LANDELL, 1995; OLIVEIRA et al, 2007; FABRIS et al, 2013). In this context, the use of multivariate techniques such as canonical correlations allows the determination of the associations between groups of characters and identification of characteristics and important variables for analyzing the performance of crops (CARVALHO et al, 2015)

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