Number of leaves and phenology of rice hybrids simulated by the SimulArroz model

Abstract

A B S T R A C TProcess-based-models can predict leaf and reproductive development of agricultural crops. The objective of this study was to calibrate and evaluate the SimulArroz model in simulating the number of leaves on the main culm and the phenology of three hybrid rice cultivars in Rio Grande do Sul, Brazil. Field experiments were conducted in Santa Maria, Cachoeirinha, Uruguaiana and Santa Vitória do Palmar, in Rio Grande do Sul state, in two growing seasons. Observations were made to determine the number of leaves in the main culm through the Haun scale and the phenology of three hybrid cultivars (PRIME CL, INOV CL and QM 1010 CL) and a conventional rice cultivar used as a control (IRGA 424). The calibration of the SimulArroz model was efficient for simulating the number of leaves and phenology as a function of the sowing date and maturity group of three hybrid rice cultivars in Rio Grande do Sul.Número de folhas e fenologia de híbridos de arroz simulado pelo modelo SimulArroz R E S U M O Modelos matemáticos baseado em processos podem prever o desenvolvimento folhar e reprodutivo de cultivos agrícolas. Objetivou-se, com este trabalho, calibrar e avaliar o modelo SimulArroz em simular o número de folhas e a fenologia de três cultivares de arroz híbrido no Rio Grande do Sul. Foram conduzidos experimentos de campo em Santa Maria, Cachoeirinha, Uruguaiana e Santa Vitória do Palmar, no Rio Grande do Sul, em dois anos agrícolas. Foram realizadas observações para determinar o número de folhas do colmo principal através da escala da Haun e a fenologia de três cultivares híbridas (PRIME CL, INOV CL e QM 1010 CL) e uma convencional de arroz usada como testemunha (IRGA 424). A calibração do modelo SimulArroz utilizada foi eficiente em simular o número de folhas e a fenologia em função da época de semeadura e do grupo de maturação de três cultivares híbridas de arroz irrigado no Rio Grande do Sul.

An update of new flood-irrigated rice cultivars in the SimulArroz model

“…The maximum appearance rates of the first and second leaves were similar for the Guri INTA CL, Puitá INTA-CL, and IRGA 424 RI cultivars ( Table 2), indicating that leaf appearance did not differ among these three genotypes. For total thermal time necessary to complete the sowing-emergence phase, the duration of the emergence-panicle differentiation and panicle differentiation-anthesis phases was shorter for the cultivars from the early maturity group (Table 2), as also verified for rice hybrids by Ribas et al (2017). In addition, the values obtained for radiation use efficiency and the leaf area index for the Puitá INTA-CL cultivar and for radiation use efficiency for Guri INTA CL were higher than those for IRGA 424 RI, indicating greater efficiency in converting light energy (solar radiation) into chemical energy (photosynthesis).…”

“…The genetic parameters calibrated in the SimulArroz model were: maximum rate of the appearance of the first and second leaves; cumulative number of leaves on the main stem; development rates; total thermal time necessary to complete the sowing-emergence phase; total thermal time necessary to complete the emergence-panicle differentiation phase; total thermal time necessary to complete the panicle differentiationanthesis phase; total thermal time necessary to complete the anthesis-maturation phase; radiation use efficiency; aboveground dry matter biomass; assimilate partitioning factors; leaf area index; spike formation factor; and maximum grain weight. The calibration approach was the same as in Rosa et al (2015) and Ribas et al (2017).…”

“…In Rio Grande do Sul, the SimulArroz model is adopted for studies on irrigated rice modeling , since it has already been calibrated for rice cultivars and technological farming. The model is used for a variety of applications at farm and regional levels, aiming to evaluate, for example, on a real-time basis, the impact of current weather on flood-irrigated rice yield potential Ribas et al, 2017). As a result, the SimulArroz model was selected for updating the agricultural zoning for rice in that state; this is the first time a process-based model is being used for agricultural zoning in Brazil (Brasil, 2019).…”

“…However, the latest version of the SimulArroz model (Ribas et al, 2017) does not include the IRGA 424 RI, Puitá INTA-CL, and Guri INTA CL cultivars, which are currently the most grown in the state of Rio Grande do Sul. This is crucial for those estimates (Cassman et al, 2003;Lobell et al, 2009;Ittersum et al, 2013), in order to provide information about the yield potential and gap for flood-irrigated rice in Southern Brazil.…”

Observed and estimated leaf appearance of landrace and improved maize cultivars

“…The WE already was included on the SimulArroz model, and the error observed for rice hybrid and varieties was equal to 0.98 leaf (RIBAS et al, 2017). For gladiolus plants, the WE is part of the PhenoGlad model with an error of 0.5 leaf (UHLMANN et al, 2017).…”