Development of chia plants in field conditions at different sowing-date

The objective of this study was to characterize the development of chia plants sown at different dates, and to determine the relation between the duration of the development cycle and the final number of leaves and the leaf appearance rate on the main stem. A field experiment was conducted in the agricultural year of 2016/2017 in five sowing dates (09/22/16, 10/28/16, 01/03/17, 02/08/17 and 03/24/17) in the edaphoclimatic conditions of the central region of the RS, Brazil. A randomized block design with four replicates was used. For each sowing date, the duration of the vegetative and reproductive phases in days and in °C day (Tb = 11 °C), the final number of leaves and the phyllochron of the main stem were determined. The duration of the vegetative phase of chia plants in days and in ºC day varies between the sowing dates, with shorter duration in late sowings in response to the photoperiod reduction. The vegetative phase represents the largest part of the total development cycle in early sowing dates, being overcome by the reproductive phase in late sowing dates (02/08/17 and 03/24/17). The phyllochron for chia varies from 36.23 (very late sowing) to 59.88 ºC day (early sowing). Later sowing has a smaller final number of leaves accumulated in the main stem due to the shorter duration of the vegetative phase.The objective of this study was to characterize the development of chia plants sown at different dates, and to determine the relation between the duration of the development cycle and the final number of leaves and the leaf appearance rate on the main stem. A field experiment was conducted in the agricultural year of 2016/2017 in five sowing dates (09/22/16, 10/28/16, 01/03/17, 02/08/17 and 03/24/17) in the edaphoclimatic conditions of the central region of the RS, Brazil. A randomized block design with four replicates was used. For each sowing date, the duration of the vegetative and reproductive phases in days and in °C day (Tb = 11 °C), the final number of leaves and the phyllochron of the main stem were determined. The duration of the vegetative phase of chia plants in days and in ºC day varies between the sowing dates, with shorter duration in late sowings in response to the photoperiod reduction. The vegetative phase represents the largest part of the total development cycle in early sowing dates, being overcome by the reproductive phase in late sowing dates (02/08/17 and 03/24/17). The phyllochron for chia varies from 36.23 (very late sowing) to 59.88 ºC day (early sowing). Later sowing has a smaller final number of leaves accumulated in the main stem due to the shorter duration of the vegetative phase

Uma atualização de novas cultivares de arroz irrigado por inundação no modelo SimulArroz

The objective of this work was to model, in the SimulArroz model, the three flood-irrigated rice (Oryza sativa) cultivars currently most grown in the state of Rio Grande do Sul, Brazil. The experiments to calibrate and validate the model were conducted in the municipalities of Cachoeirinha, Santa Maria, Uruguaiana, Santa Vitória do Palmar, and Cachoeira do Sul during four crop seasons. The number of leaves, phenology, aboveground dry matter biomass, and yield of each cultivar were evaluated. The results showed a slight overestimate of the R1, R4, and R9 stages; however, overall, the SimulArroz model had a good performance in simulating rice phenology for the three studied genotypes. Furthermore, the model had a reasonable accuracy in simulating aboveground dry matter and yield. The root-mean-square error (RMSE) for aboveground dry matter (leaves, stems, panicles, and grains) ranged from 0.5 to 3.0 Mg ha-1. For yield, the RMSE ranged from 0.8 to 1.3 Mg ha-1. The calibration of the SimulArroz model is efficient in simulating the growth, development, and grain yield of the most important flood-irrigated rice cultivars in Southern Brazil and can be used to estimate harvest forecast and yield potential, as well for yield gap studies.O objetivo deste trabalho foi modelar, no modelo SimulArroz, as três cultivares de arroz (Oryza sativa) irrigado atualmente mais cultivadas no Estado do Rio Grande do Sul. Os experimentos para calibrar e validar o modelo foram conduzidos nos municípios de Cachoeirinha, Santa Maria, Uruguaiana, Santa Vitória do Palmar e Cachoeira do Sul, durante quatro safras. Foram avaliados o número de folhas, a fenologia, a biomassa da matéria seca da parte aérea e a produtividade de cada cultivar. Os resultados mostraram uma leve superestimativa dos estádios R1, R4 e R9; no entanto, no geral, o modelo SimulArroz apresentou bom desempenho na simulação da fenologia do arroz para os três genótipos estudados. Além disso, o modelo teve uma precisão razoável em simular matéria seca da parte aérea e produtividade. A raiz quadrada do erro quadrático médio (RMSE) para matéria seca da parte aérea (folhas, caules, panículas e grãos) variou de 0,5 a 3,0 Mg ha-1. Para produtividade, a RMSE variou de 0,8 a 1,3 Mg ha-1. A calibração do modelo SimulArroz é eficiente em simular o crescimento, o desenvolvimento e a produtividade de grãos das cultivares de arroz irrigado mais importantes no Sul do Brasil e pode ser utilizada para estimar a previsão de safra e o potencial de produtividade, bem como para estudos de lacunas de produtividade

Forecasting the rice yield in Rio Grande do Sul using the SimulArroz model

O objetivo deste trabalho foi avaliar um método de previsão de safra para arroz irrigado por inundação no estado do Rio Grande do Sul, Brasil, por meio do modelo SimulArroz. Utilizou-se a versão 1.1 desse modelo e dados meteorológicos históricos, com seis cenários compostos pelos seguintes níveis de informação em campo: datas de semeadura (1 a 4) e número de cultivares e/ou ciclos de desenvolvimento (1 a 3) durante quatro safras (2014/2015 a 2017/2018). A raiz quadrada média do erro (RQME), para comparação da produtividade real com a produtividade simulada para o Rio Grande do Sul, foi de 618,3 e 1.024,8 kg ha-1, isto é, de 8 e 13%, respectivamente. A previsão de safra de arroz com aplicação do modelo SimulArroz e dados meteorológicos históricos para o Rio Grande do Sul apresenta boa capacidade preditiva quanto à produtividade, e o cenário recomendado para a previsão é o complex 1, com uso de três épocas de semeadura por local e das três cultivares mais representativas por região.The objective of this work was to evaluate a flooded-rice yield forecasting method for the state of Rio Grande do Sul, Brazil, using the SimulArroz model. Version 1.1 of this model and historical meteorological data were used, with six different scenarios composed of the following levels of field information: number of sowing dates (1 to 4) and number of cultivars and/or development cycles (1 to 3) during four growing seasons (2014/2015 to 2017/2018). The root mean square error (RMSE) for comparing the actual yield with the simulated yield for Rio Grande do Sul was of 618.3 and 1,024.8 kg ha-1, i.e., of 8 and 13%, respectively. The forecast of rice yield by applying the SimulArroz model and historic meteorological data for Rio Grande do Sul shows a good predictability, and the recommended scenario is complex 1, using three sowing dates per site and the three most representative rice cultivars per region