Prediction of fresh and dry matter of the aerial part of the plant teosinte as a function of morphological traits

Authors

DOI:

https://doi.org/10.29327/2537114.12.3-2

Keywords:

Zea mays ssp. mexicana, multiple linear regression, regression tree, forage plant

Abstract

The objective of this work was to verify whether the fresh and dry matter of the aerial part of the teosinte plant can be estimated as a function of morphological traits. An experiment was conducted in the agricultural year 2021/2022, in nine sowing dates. The following morphological traits were measured: stem length of the main stem (CC, cm); length of the main stem tassel (CP, cm); number of leaves on the main stem (NF); and number of tillers of the plant (NPF) and the productive ones: fresh mass of the aerial part of the plant (MFPA, g) and dry mass of the aerial part of the plant (MSPA, g). The parameters of the multiple linear regression model and the coefficient of determination were estimated considering the variables MFPA and MSPA as dependent and the other (CC, CP, NF, NPF) as independent. The parameters of the regression tree algorithm for predicting MFPA and MSPA were estimated as a function of the other variables (CC, CP, NF, NPF). The fresh and dry mass of the aerial part of the teosinte plant can be estimated as a function of morphological characters. The MFPA can be estimated by the following regression model: MFPA= -740.42 + 3.38(CC) + 9.70(CP) + 41.05(NF) + 85.70(NPF). While the MSPA can be estimated by the following regression model: MSPA= -84.33 + 0.85(CC) + 0.27(CP) + 3.67(NF) + 19.46(NPF). Plants with NPF greater than 8 and CC greater than 154 cm show the highest production of MFPA and MSPA.

Author Biographies

  • Alberto Cargnelutti Filho, Federal University of Santa Maria

    Docente do curso de Agronomia

  • Murilo Vieira Loro, Federal University of Santa Maria

    Discente do curso de doutorado em Agronomia

  • Mikael Brum dos Reis, Federal University of Santa Maria

    Discente do curso de Agronomia

  • Vithória Morena Ortiz, Federal University of Santa Maria

    Discente do curso de mestrado em Agronomia

  • João Augusto Andretta, Federal University of Santa Maria

    Discente do curso de Agronomia

  • Bruno Raul Schuller, Federal University of Santa Maria

    Discente do curso de Agronomia

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Published

2023-08-16

Issue

Vol. 12 No. 3 (2023): Special issue: 67th RBRAS and 20th SEAGRO

Section

Applied Statistics

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How to Cite

Prediction of fresh and dry matter of the aerial part of the plant teosinte as a function of morphological traits. (2023). Sigmae, 12(3), 10-17. https://doi.org/10.29327/2537114.12.3-2