Modelos de Determinação Não Destrutiva de Área Foliar de Feijão Caupi Vigna unguiculata (L.)

Oliveira, Raimundo Leonardo Lima de; Moreira, Antonio Robson; Costa, Antonia Vanderlane Albuquerque da; Souza, Leane Castro de; Lima, Layla Gerusa Souza; Silva, Raimundo Thiago Lima da

doi:10.14688/1984-3801/gst.v8n2p17-27

Cited by 16 publications

(5 citation statements)

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“…An efficient way to evaluate vegetative growth is by the length and width variables. The use of linear leaf measurements allows the monitoring of leaf development in the field without the need to collect the leaf, implying a simple and less costly procedure, and these two characteristics are efficient in estimating leaf area (OLIVEIRA et al, 2016). According to Sachet et al (2015), the joint analysis of these two variables allows obtaining better coefficients of determination when compared with other methods.…”

Section: Resultsmentioning

confidence: 99%

Leaf area estimation of Anacardium humile

et al. 2020

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The Anacardium humile A. St.- Hil. fruit tree has productive potential, being their fruits appreciated in the Cerrado region for having characteristic flavor, however, this species is still exploited in an extractive way, being necessary studies for its domestication. The aim of this work was to estimate the leaf area of Anacardium humile. One hundred leaves were collected in the biological collection from a genetic resources field and evaluated for length, width and fresh weight, and scanned at resolution of 300 dpi to determine the leaf area with the aid of the ImageJ image analysis program. Subsequently, a leaf disc with a diameter of 22.27 mm was detached at the basal portion of each leaf, in which the fresh weight of the discs was obtained. Data were submitted to descriptive analysis and the relationship among the features explained by Pearson’s correlation with the software Rbio. The data were also subjected to regression analysis to explain the relationship between leaf area and measurements of width, length and leaf weight, and to fit the proper statistical model with the software Origin. It was concluded that leaf area can be determined by image analysis software and linear measurements are correlated to leaf area.

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Section: Resultsmentioning

confidence: 99%

Leaf area estimation of Anacardium humile

et al. 2020

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“…(Candido, Coelho, Maia, Cunha, & Silva, 2013), Acrocomia aculeata Jacq. (Mota, Leite, & Cano, 2014), Merremia aegyptia (L.) Urban (Assis, Linhares, Souza, Pereira, & Almeida, 2015), and for cultivated species, such as Ananas comosus L. (Merrill) (Francisco, Diotto, Folegatti, Silva, & Piedade, 2014), Vigna unguiculata (L.) (Oliveira et al, 2015), Mangifera indica L. (Silva, Cabanez, Mendonça, Pereira, & Amaral, 2015), Prunus persica (L.) (Sachet, Penso, Pertille, Guerrezii, & Citadin, 2015), Smallanthus sonchifolius (Poepp.) H. Rob.…”

Section: Resultsmentioning

confidence: 99%

Leaf area estimation for <i>Psychotria carthagenensis</i> and <i>Psychotria hoffmannseggiana</i> as a function of linear leaf dimensions

Ribeiro¹,

Coêlho

Figueiredo

et al. 2019

Acta Sci. Biol. Sci.

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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 * LW 0.9804 was the most appropriate for P. carthagenensis, while ŷ = 0.6235 * LW 0.9712 was the most appropriate for P. hoffmannseggiana.

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“…Therefore, the following were considered: Pearson's correlation coefficient (R), coefficient of determination (r 2 ) and the concordance index d (Willmott et al, 1985). In addition, the following statistical errors were estimated: mean absolute error (MAE) and root mean of the square error (SRMSE) (quoted by Oliveira et al, 2015) and the c performance coefficient of Camargo and Sentelhas (Camargo & Sentelhas, 1997).…”

Section: Model Used For Adjustment Of the Species Biomass Variablesmentioning

confidence: 99%

Partitioning and Modeling of Biomass in Caatinga Legume Seedlings in Different Water Conditions

et al. 2019

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The accumulation of dry biomass, its partitioning and the adjustment of equations were assessed for the initial growth of Piptadenia stipulacea (Benth) Ducke and Anadenanthera colubrina (Vell.) Brenan under water availability variation. The experiment was conducted in pots arranged in a completely randomized design with three replicates. Water conditions were evaluated using the percentages of reference evapotranspiration. Samples of the biomass were taken at 10-day intervals and used for the achievement of partitioning data and model adjustments. The short period of water scarcity in the initial growth phase of P. stipulacea and A. colubrina does not affect the establishment of these species, but different water regimes alter their root growth dynamics. The A. colubrina allocates more dry matter to the roots, while P. stipulacea sends more dry matter to the aerial part. The Gaussian, Lorentzian, Log-Normal and Gompertz models had excellent adjustments for the biomass variables of the P. stipulacea species, whereas for A. colubrina, we recommend the Exponential model.

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Modelos de Determinação Não Destrutiva de Área Foliar de Feijão Caupi Vigna unguiculata (L.)

Cited by 16 publications

References 0 publications

Leaf area estimation of Anacardium humile

Leaf area estimation of Anacardium humile

Leaf area estimation for <i>Psychotria carthagenensis</i> and <i>Psychotria hoffmannseggiana</i> as a function of linear leaf dimensions

Partitioning and Modeling of Biomass in Caatinga Legume Seedlings in Different Water Conditions

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