Article ; Online: Agrometeorological models for predicting seedlings development of two native forest species
Scientia Agricola, Vol 79, Iss
2021 Volume 4
Abstract: ABSTRACT Models of development are tools that connect the effects of development on the environment, allowing their applications in several studies. Nevertheless, studies are scarce on models of development for native forest species in Brazil. This study ...
Abstract | ABSTRACT Models of development are tools that connect the effects of development on the environment, allowing their applications in several studies. Nevertheless, studies are scarce on models of development for native forest species in Brazil. This study aimed to predict the development of two native forest species - Citharexylum myrianthum Cham. and Bixa orellana L. - with two agrometeorological models, being one linear (Phyllochron) and another nonlinear (Wang and Engel, 1998). Both models predict the cumulative leaf number (CLN) on a daily basis, which generates the seedling phase duration (SPD) when integrated to time. Data were used from two years of experiments conducted during 2015 and 2016 growing seasons and 12 sowing dates in Itajubá, Minas Gerais State, Brazil. These species × sowing dates × years experiments provided a rich dataset for calibrating and evaluating both models. Although both models used in the study allowed predicting the dynamics of leaf development, CLN, and SPD in two native forest species, the Wang and Engel model provided a more accurate prediction of CLN and SPD for C. myrianthum species, with an overall root mean square error (RMSE) of 1.82 leaves (CLN) and 5.9 days (SPD). For B. orellana, the Phyllochron model was slightly better, with an overall RMSE of 1.48 leaves (CLN) and seven days (SDP). |
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Keywords | Bixa orellana L ; Citharexylum myrianthum Cham ; air temperature ; leaf appearance ; phenology ; Agriculture (General) ; S1-972 |
Subject code | 580 |
Language | English |
Publishing date | 2021-07-01T00:00:00Z |
Publisher | Universidade de São Paulo |
Document type | Article ; Online |
Database | BASE - Bielefeld Academic Search Engine (life sciences selection) |
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