ABSTRACT
Abstract: Climatic variation throughout the day influences the ecophysiological performance of plants at different growth stages and phases. Therefore, this work aimed to evaluate the effect of climatic variation on ecophysiological aspects of T. roseoalba and H. heptaphyllus at different hours of the day and indicate the ideal time for measuring ecophysiological variables in these species. The research was carried out in a greenhouse at the forest nursery of the Federal University of Paraíba, Campus II, in the municipality of Areia, Paraíba state, Northeastern Brazil. The experimental design was completely randomized, consisting of 10 evaluation times throughout the day (from 8 am to 5 pm), with 1 h hour interval between each evaluation. Temperature and air relative humidity inside and outside the greenhouse were evaluated to understand the effect on gas exchange (net assimilation rate of CO2, stomatal conductance, transpiration rate, internal concentration of CO2, and vapor-pressure deficit) and chlorophyll a fluorescence (initial, maximum, and variable fluorescence, photochemical quenching, and electron transport rate). Data were submitted to canonical correlation analysis and principal component analysis to verify the relationship between climatic and ecophysiological variables. For both species, higher correlation was found between internal and external relative humidity with all the ecophysiological variables analyzed, except for initial fluorescence. Thus, climatic factors influenced the photosynthetic performance of T. roseoalba and H. heptaphyllus plants, and 8 am to 9 am is indicated for carrying out ecophysiological evaluations in both species.
ABSTRACT
Estimating leaf area using non-destructive methods from regression equations has become a more efficient, quick, and accurate way. Thus, this study aimed to propose an equation that significantly estimates the leaf area of Psychotria colorata (Rubiaceae) through linear leaf dimensions. For this purpose, 200 leaves of different shapes were collected, and length (L), width (W), product of length by width (L.W), and real leaf area (LA) of each leaf blade were determined. Then, equations were adjusted for predicting leaf area using simple linear, linear (0.0), quadratic, cubic, power, and exponential regression models. The proposed equation was selected according to the coefficient of determination (R²), Willmott's agreement index (d), Akaike's information criterion (AIC), mean absolute error (MAE), mean squared error (RMSE) and BIAS index. It was noted that the equations adjusted using L.W met the best criteria for estimating leaf area, but the equation LA = 0.59 * L.W from linear regression without intercept was the most suitable. This equation predicts that 59% of leaf area is explained by L.W. Concluding, the leaf area of P. colorata can be estimated using an allometric equation that uses linear leaf blade dimensions.
Subject(s)
Plant Leaves , PsychotriaABSTRACT
Erythroxylum citrifolium is a neotropical plant species recorded in all regions of Brazil. Determining leaf area is of fundamental importance to studies related to plant propagation and growth. The objective was to obtain an equation to estimate the leaf area of E. citrifolium from linear dimensions of the leaf blade (length and width). A total of 200 leaf blades were collected in Parque Estadual Mata do Pau-Ferro in the municipality of Areia, state of Paraíba, Northeast Brazil. The models evaluated were: linear, linear without intercept, quadratic, cubic, power and exponential. The best model was determined by the criteria of: high coefficient of determination (R²), low root mean square error (RMSE), low Akaike information criterion (AIC), high Willmott concordance index (d) and a BIAS index close to zero. All of the models constructed satisfactorily estimated the leaf area of E. citrifolium, with coefficients of determination above 0.9050, but the power model using the product between length and width (L*W) y = 0.5966 * LW1.0181 was the best, with the highest values of R² and d, low values of RMSE and AIC, and a BIAS index closest to zero.
Erythroxylum citrifolium é uma espécie de planta neotropical com registros em todas as regiões do Brasil. A determinação da área foliar é de fundamental importância em estudos relacionados a propagação e crescimento vegetal. O objetivo foi obter uma equação que permita estimar a área foliar de E. citrifolium a partir de dimensões lineares do limbo foliar (comprimento e largura). Foram coletados 200 limbos foliares no Parque Estadual Mata do Pau-Ferro, Areia, Paraíba, Nordeste do Brasil. Os modelos empregados foram: linear, linear sem intercepto, quadrático, cúbico, potencial e exponencial. Os critérios utilizados para escolher o melhor modelo, teve como base o maior coeficiente de determinação (R²), menor raiz do quadrado médio do erro (RMSE), menor critério de informação de Akaike (AIC), maior índice de concordância de Willmott (d) e índice BIAS mais próximo de zero. Todos os modelos construídos podem estimar satisfatoriamente a área foliar de E. citrifolium, com coeficientes determinação acima de 0,9050, porém o modelo potencial utilizando o produto entre comprimento e largura (L*W) y = 0,5966 * LW1,0181 é o mais indicado, com os maiores valores de R² e d, menores valores de RMSE e AIC, e índice BIAS mais próximo de zero.
Subject(s)
Biometry , ErythroxylaceaeABSTRACT
Determining leaf area is important for studies involving plant growth and development. The aim of the present study was to obtain models for estimating leaf area of Psychotria carthagenensis and Psychotria hoffmannseggiana using linear measurements of leaf blades (length and width). Two hundred leaf blades of each species were collected in Parque Estadual Mata do Pau-Ferro in the municipality of Areia, Paraíba, Northeast Brazil. The equations evaluated for producing potential models included the following: linear, quadratic, potential and exponential. The criteria used to determine the best model(s) were as follows: high coefficient of determination (R²), low root-mean-square error (RMSE), low Akaike information criterion (AIC), high Willmott concordance index (d) and a BIAS ratio close to zero. All evaluated models satisfactorily estimated leaf area for the two species, but the equation ŷ = 0.6373 * LW0.9804 was the most appropriate for P. carthagenensis, while ŷ = 0.6235 * LW0.9712 was the most appropriate for P. hoffmannseggiana.