Estimating Emission of Leaves Seedlings Forest in Different Shading Levels, at Conditions of Transition Amazon-Cerrado, Brazil

Emanoeli Borges Monteiro, Cátia Cardoso da Silva, Andréa Carvalho da Silva, Adilson Pacheco de Souza

Institute of Agricultural and Environmental Sciences, Federal University of Mato Grosso, Sinop, Brazil.

DOI: 10.4236/ajps.2014.515247                

Abstract

This study determined the thermal requirements of forest native seedlings (Hymenolobium petraeum and Parkia pendula) and exotic seedlings (Adenanthera pavonina and Cassia fistula) all belonging to Fabaceae family, in three shading conditions (full sun, 50% and 65% of global radiation attenuation by poliefinas black screens). Also they were estimated of leaf emergence by Phyllochron and the Wang and Engel models, on climatological conditions at Sinop (Region of Transition Amazon-Cerrado), Mato Grosso State, Brazil, for winter period (between June and August of 2012). The minimum (T_b) and maximum (T_B) basal temperatures and the optimum temperature (T_opt) of growth of each species were estimated by regressions between relative growth rates and minimum, maximum and average temperatures, respectively. The values of the estimated T_b were 15.0°C, 16.4°C, 14.5°C and 14.6°C; to T_B were 39.7°C, 37.1°C, 38.6°C and 40.1°C; and to T_opt were 24.4°C, 24.9°C, 24.9°C and 25.1°C to A. pavonina, C. fistula, H. petraeum and P. pendula, respectively. The Phyllochron model showed highest efficiency in the estimation of leaf appearance when compared to Wang and Engel method.

Keywords

Vegetative Growth, Thermal Sum, Degree-Days, Statistical Indicatives

Table 1. Meteorological parameters collected by meteorological automatic station during period form 06/06 to 14/08/2012, at Sinop, Mato Grosso State, Brazil (11.98˚S and 55.56˚W).

DAT: days after transplantation; ETo: daily reference evapotranspiration.

Table 2. Values of optimal temperatures (T_opt), minimum (T_b) and maximum (T_B) basal temperatures estimated for forest species.

Figure 1. Correlations between daily mean temperatures (˚C) measured at full sun and under the covers at 50% and 65% shading by nylon black shade-screen (p = 0.01).

In the literature are reported the thermal requirements for perennials crops, especially Eucalyptus saligna species, whose values of T_b, T_B and T_opt are 8.0˚C; 35.0˚C and 25.0˚C, respectively [21] [46] ; Eucalyptus grandis are 10.0˚C; 36.0˚C and 27.0˚C [21] [47] ; whose for fig tree (Ficus carica), the values of T_b and T_B are 8.0˚C and 36.0˚C [38] ; coffee (Coffea arabica) in implementation phase are 12.9˚C and 32.4˚C [48] ; and finally, the olive tree (Olea europaea L.) T_b is 8.5˚C [49] . The values of optimum temperatures (T_opt) provides the higher development rates and hardly found in the literature for native species. However, it is noted that T_opt values to H. peatrum and P. pendula are close to those determined for Eucalyptus species, while the values of T_b and T_B were higher than, in view that they are originate from tropical regions and two are Amazonian.

As to the shading levels effect on the seedlings development, it was observed that the highest values of RGR occurred in 50% shade coverage for all species, indicating that this percentage can be considered suitable for accommodate the evaluated species seedlings. Based on the basal temperatures and daily average temperatures estimated at each cultivation condition, were obtained the STa values for the experimental period at the different treatments (Table 3), being observed small values of standard deviation of STa between the different coverage for all species.

The estimated Phyllochron values for the four forest species had low standard deviation between treatments, being the average values 11.40˚C day leaf⁻¹; 19.54˚C day leaf⁻¹; 26.72˚C day leaf⁻¹ and 30.30˚C day leaf⁻¹ for A. pavonina, C. fistula, H. petraeum and P. pendula. From these values, it is noteworthy that the higher Phyllochron value is the greater quantity of STa needed for leaf issuance, and thus, the species with the highest thermal demand to issue one leaf organ was P. pendula.

It was found out in NL estimates for A. pavonina, C. fistula and P. pendula in all treatments that the Phyllochron method overestimated the NL average, while the WE model propitiated under estimations. To H. petraeum, both models underestimated the NL with minimal values of 2.9 and 6.9 leaves to Phyllochron and WE, respectively (Figure 2). For all species and treatments, the standard deviation for Phyllochron method were higher than those presented by WE model. Analyzing the observed and estimated data (Figure 3) noted that for H. petraeum, the Phyllochron method approached the 1:1 line (simple linear regression with passage through the origin), indicating better accuracy of the estimate. For the other species, this behavior was given by the WE model, which presented values of determination coefficients (R²) higher than those adjusted for Phyllochron model.

The RMSE values were better in the WE method and lower those presented by Phyllochron method (except

Figure 2. Means of accumulated leaves observed and estimated by two methods (Phyllochron and WE) for forest species at 50% and 65% shading by nylon black shade-screen.

Figure 3. Number of accumulated leaves (NL) observed and NL estimated by two models (phyllochron and WE) for forest seedlings species at 50% and 65% shading by nylon black shade-screen.The solidlineisthe 1:1 linecross.

for H. petraeum in 50% shading), varying from 0.741 to 2.924 for WE and 1.418 to 8.891 for Phyllochron. In relation to correlation coefficient (r), performance index (c) and concordance index (dw), the Phyllochron method showed be superior than the WE method. Regarding the statistical indicatives (Table 4), it was observed

Table 3 . Accumulated thermal sum (STa, in ˚C∙day⁻¹) estimated for forest species at 50% and 65% shading by nylon black shade-screen.

Table 4. Empirical values of the statistics used to classify Phyllochron (PHY) and Wang and Engel (WE) methods for four species in each treatment (0%, 50% and 65% shading).

The values in parentheses below each statistic relate to weights assigned second method of statistical weighted scores (V_p), where 1 refers to the best model and 2, to worst.

that the Phyllochron method showed lowest of V_p values when compared with the WE method for all species and treatments, being this way, indicated as the best method to estimate the leaf appearance.

Finally, the BIAS index indicated that the Phyllochron method excelled over WE, considering that for the species H. petraeum and A. pavonina, the first was superior in estimating the NL in all treatments, while the second was greater only in the full sun treatment for C. fistula and P. pendula. For the mentioned index, the values ranged from −0.021 to 0.519 and −0.229 to Phyllochron to −0.127 for WE.

The results were different from the observations for E. saligna and E. grandis, since for these species the best NL estimates given by WE method with nonlinear responses of LAR as a temperature function [14] . In general, the Phyllochron method criticized by considering the leaf emission response linear to temperature, what not accepted from the biological viewpoint. Streck [22] and Xue et al. [20] affirm that the linearity of responses (development) obtained only in the proximity of basal temperatures. However, this method is widely used to estimate crop development, mainly agricultural [20] , and which for forest species, the studies of this nature are not frequent.

4. Conclusions

The thermal requirements estimated for the species Adenanthera pavonina, Cassia fistula, Hymenolobium petraeum and Parkia pendula were respectively 15.0˚C, 16.4˚C, 14.5˚C and 14.6˚C, for the minimum basal temperatures; 39.7˚C, 37.1˚C, 38.6˚C and 40.1˚C, for the maximum basal temperatures; 24.4˚C, 24.9˚C, 24.9˚C and 25.1˚C, for optimum temperatures for development; and accumulated thermal sums (STa) averages are 682.15˚C∙day⁻¹; 584.96˚C∙day⁻¹; 715.14˚C∙day⁻¹ and 707.06˚C∙day⁻¹.

The Phyllochron model presented best estimates of leaf appearance of forest seedlings in shaded conditions and full sun.

References

NOTES

^*Corresponding authors.

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1]	Whitehead, D. and Beadle, C.L. (2004) Physiological Regulation of Productivity and Water Use in Eucalyptus: A Review. Forest Ecology and Management, 193, 113-140. http://dx.doi.org/10.1016/j.foreco.2004.01.026
[2]	Monteith, J.L. (1965) Light Distribution and Photosynthesis in Field Crops. Annals of Botany, 29, 17-37.
[3]	Chory, J. (1997) Light Modulation of Vegetative Development. The Plant Cell, 9, 1225-1234. http://dx.doi.org/10.1105/tpc.9.7.1225
[4]	Taiz, L. and Zieger, E. (2004) Fisiologia Vegetal. 3rd Edition, Artmed, Porto Alegre, 719 p.
[5]	Engel, V.L. and Poggiani, F. (1991) Study of Foliar Chlorophyll Concentration and Its Light Absorption Spectrum as Related to Shading at the Juvenile Phase of Four Native Forest Tree Species. Revista Brasileira de Fisiologia Vegetal, 3, 39-45.
[6]	Dias-Filho, M.B. (1997) Physiological Response of Solanum crinitum Lam. to contrasting Light Enviroments. Pesquisa Agropecuária Brasileira, 32, 789-796.
[7]	Naves, V.L., Alvarenga, A.A. and Oliveira, L.E.M. (1994) Stomatal Behavior of Seedlings of Three Tree Species Subjected to Different Levels of Photosynthetically Active Radiation. Ciência e Prática, 18, 408-414.
[8]	Oliari, I.C.R., Umburanas, R.C., Eschemback, V. and Kawakami, J. (2010) Effect of Restriction of Solar Radiation and Increases of Temperature on the Growth of Radish Plants. Applied Research and Agrotechnology, 3, 83-88.
[9]	Larcher, W. (2000) Ecophysiological Plant. Rima, São Carlos, 531 p.
[10]	Snyder, R.L., Spano, D., Cesaraccio, C. and Duce, P. (1999) Determining Degree-Day Thresholds from Field Observations. International Journal of Biometeorology, 42, 77-182. http://dx.doi.org/10.1007/s004840050102
[11]	Souza, A.P., Leonel, S. and Silva, A.C. (2011) Basal Temperature and Thermal Sum in Phonological Phases of Nectarine and Peach Cultivars. Pesquisa Agropecuária Brasileira, 46, 1588-1596.
[12]	Severino, L.S., Vale, L.S. and Beltrão, N.E.M. (2007) A Simple Method for Measurement of Jatropha curcas Leaf Area. Revista Brasileira Oleaginosas e Fibrosas, 11, 9-14.
[13]	Severino, L.S., Cardoso, G.D., Vale, L.S. and Santos, J.W. (2004) A Method for Castor Beanleaf Area Estimation. Revista Brasileira de Oleaginosas e Fibrosas, 8, 753-762.
[14]	Martins, F.B. and Streck, N.A. (2007) Leaf Appearance in Seedlings of Eucalyptus Estimated by Two Models. Pesquisa Agropecuária Brasileira, 42, 1091-1100. http://dx.doi.org/10.1590/S0100-204X2007000800005
[15]	Amir, J. and Sinclair, T.R. (1991) A Model of Water Limitation on Spring Wheat Growth and Yield. Field Crops Research, 29, 59-96. http://dx.doi.org/10.1016/0378-4290(91)90074-6
[16]	Wang, E. and Engel, T. (1998) Simulation of Phonological Development of Wheat Crops. Agricultural Systems, 58, 1-24. http://dx.doi.org/10.1016/S0308-521X(98)00028-6
[17]	Streck, N.A., Bellé, R.A. and Schuh, M. (2005) Estimating Leaf Appearance Rate and Phyllochron in Safflower (Carthamus tinctorius L.). Ciência Rural, 35, 1448-1450. http://dx.doi.org/10.1590/S0103-84782005000600036
[18]	Streck, N.A., Weiss, A., Xue, Q. and Baezinger, P.S. (2003) Incorporating a Chronology Response Function into the Prediction of Leaf Appearance Rate in Winter Wheat. Annals of Botany, 92, 181-190. http://dx.doi.org/10.1093/aob/mcg121
[19]	Kirby, E.J.M. (1995) Environmental Factors Influencing the Phyllochron. Crop Science, 5, 11-19.
[20]	Xue, Q.W., Weiss, A. and Baenziger, P.S. (2004) Predicting Leaf Appearance in Field-Grown Winter Wheat: Evaluating Linear and Non-Linear Models. Ecological Modelling, 175, 261-270. http://dx.doi.org/10.1016/j.ecolmodel.2003.10.018
[21]	Martins, F.B., Silva, J.C. and Streck, N.A. (2007) Estimating Base Temperature for Leaf Appearance Rate and the Phyllochron in Two Eucalyptus Species during Seedling Phase. Revista árvore, 31, 373-381. http://dx.doi.org/10.1590/S0100-67622007000300002
[22]	Streck, N.A. (2002) A Generalized Nonlinear Air Temperature Response Function for Node Appearance Rate in Muskmelon (Cucumis melo L.). Revista Brasileira de Agrometeorologia, 10, 105-111.
[23]	Yan, W. and Hunt, L.A. (1999) An Equation for Modelling the Temperature Response of Plants Using only the Cardinal Temperatures. Annals of Botany, 84, 607-614. http://dx.doi.org/10.1006/anbo.1999.0955
[24]	Walter, L.C., Streck, N.A., Rosa, H.T., Alberto, C.M. and de Oliveira, F.B. (2009) Vegetative and Reproductive Development of Wheat Cultivars and Its Association with Leaf Appearance. Ciência Rural, 39, 2320-2326. http://dx.doi.org/10.1590/S0103-84782009005000169
[25]	Fagundes, L.K., Streck, N.A., Lopes, S.J., Rosa, H.T., Walter, L.C. and Zanon, A.J. (2009) Vegetative Development on Different Stems of Cassava as a Function of Planting Date. Ciência Rural, 39, 657-663. http://dx.doi.org/10.1590/S0103-84782008005000097
[26]	Mendonça, H.F.C., Calvete, E.O., Nienow, A., Costa, R.C., Zerbielli, L. and Bonafé, M. (2012) Phyllochron Estimation in Intercropped Strawberry and Monocrop Systems in a Protected Environment. Revista Brasileira de Fruticultura, 34, 15-23. http://dx.doi.org/10.1590/S0100-29452012000100005
[27]	Martins, J.D., Carlesso, R., Petry, M.T., Knies, A.E., Oliveira, Z.B. and Broetto, T. (2012) Estimating the Phyllochron in Maize Hybrids with Different Cycles of Vegetative Development. Ciência Rural, 42, 777-783.
[28]	Maldaner, I.C., Guse, F.I., Streck, N.A., Heldwein, A.B., Lucas, D.D.P. and Loose, L.H. (2009) Phyllochron, Leaf Area, and Fruit Yield in Eggplants Grown with One and Two Stems per Plant in Plastic Greenhouse. Ciência Rural, 39, 671-677. http://dx.doi.org/10.1590/S0103-84782009005000013
[29]	Streck, N.A., Lago, I., Paula, F.L.M., Bisognin, D.A. and Heldwein, A.B. (2007) Improving Predictions of Leaf Appearance in Field Grown Potato. Scientia Agricola, 64, 12-18. http://dx.doi.org/10.1590/S0103-90162007000100002
[30]	Streck, N.A., Lago, I., Gabriel, L.F. and Samboranha, F.K. (2008) Simulating Maize Phenology as a Function of Air Temperature with a Linear and a Nonlinear Model. Pesquisa Agropecuária Brasileira, 43, 449-455. http://dx.doi.org/10.1590/S0100-204X2008000400002
[31]	Martins, F.B. (2007) Development and Water Stress in Seedlings of Eucalyptus grandis (Hill ex Maiden) and Eucalyptus saligna (Smith). Dissertation Master’s in Agricultural Engineering, Federal University of Santa Maria, Santa Maria.
[32]	Assumpção Neto, A. (2008) Plastochron and Phyllochron Apparent Annual in Araucaria angustifolia (Bert.) O. Ktze., in the Municipality of Colombo-PR. Dissertation Masters in Sciences, Federal University of Paraná, Curitiba.
[33]	Martins, F.B., Reis, D.F. and Pinheiro, M.V. (2012) Base Temperature and Phyllochron in Two Olive Cultivars. Ciência Rural, 42, 1975-1981. http://dx.doi.org/10.1590/S0103-84782012001100011
[34]	Souza, A.P., Mota, L.L., Zamadei, T., Martim, C.C., Almeida, F.T. and Paulino, J. (2013) Classificação climática e balanço hídrico climatológico no estado de Mato Grosso. Pesquisas Agrárias e Ambientais, 1, 34-43. http://dx.doi.org/10.14583/2318-7670.v01n01a07
[35]	Benincasa, M.M.P. (2003) Growth Analysis of Plants (Basics Knowledge). FUNEP, Jaboticabal, 42 p.
[36]	Pereira, L.C., Júnior, J.H.C. and Ferronato, A. (2010) Comparison of Methods for Estimating Plastochron in Cotton Plant under Tropical Weather Conditions. Pesquisa Agropecuária Tropical, 40, 213-220. http://dx.doi.org/10.5216/pat.v40i2.6716
[37]	Ometto, J.C. (1981) Vegetable Bioclimatology. Agronômica Ceres, São Paulo, 425 p.
[38]	Souza, A.P., Silva, A.C., Leonel, S. and Escobedo, J.F. (2009) Basic Temperatures and Thermal Sum for the Fig Trees Pruned in Different Months. Revista Brasileira de Fruticultura, 31, 314-322. http://dx.doi.org/10.1590/S0100-29452009000200005
[39]	Frank, A.B. and Bauer, A. (1995) Phyllochron Differences in Wheat, Barley and Forage Grasses. Crop Science, 35, 19-23. http://dx.doi.org/10.2135/cropsci1995.0011183X003500010004x
[40]	Streck, N.A., Lago, I., Buriol, G.A., Heldwein, A.B. and Tibola, T. (2006) A Non-Linear Model to Simulate Node Appearance in Muskmelon (Cucumis melo L.) Grown inside Plastic Greenhouse as a Function of Air Temperature. Revista Brasileira de Agrometeorologia, 14, 210-216.
[41]	Willmott, C.J. (1981) On the Validation of Models. Physical Geography, 2, 184-194.
[42]	Camargo, A.P. and Sentelhas, P.C. (1997) Performance Evaluation of Different Potential Evapotranspiration Estimating Methods in the State of São Paulo, Brazil. Revista Brasileira de Agrometeorologia, 5, 89-97.
[43]	Leite, H.G. and Andrade, V.C.L. (2002) A Method for Conducting Forest Inventories without Using Volumetric Equations. Revista árvore, 26, 321-328. http://dx.doi.org/10.1590/S0100-67622002000300007
[44]	Schneider, P.R. (1998) Regression Analysis Applied to Forestry. 2nd Edition, UFSM/CEPEF, Santa Maria, 236 p.
[45]	Thiersch, A. (1997) Efficiency of Diameter Distributions Prognosis for the Production of Eucalyptus camaldulensis. Dissertation Masters in Sciences Forestry, Federal University of Lavras, Lavras.
[46]	Nieto, V.M. and Rodriguez, J. (2003) Eucalyptus saligna Sm. In: Vozzo, J.A., Ed., Tropical Tree Seed Manual, USDA Forest Service, Washington DC, 468-469.
[47]	Almeida, A.C., Landsberg, J.J. and Sands, P.J. (2004) Parameterization of 3-PG Model for Fast-Growing Eucalyptus grandis Plantations. Forest Ecology and Management, 193, 179-195. http://dx.doi.org/10.1016/j.foreco.2004.01.029
[48]	Lima, E.P. and Silva, E.L. (2008) Base Temperature, Crop Coefficients and Degrees-Day for Arabic Coffee Plants in the Implantation Phase. Revista Brasileira de Engenharia Agrícola e Ambiental, 12, 266-273. http://dx.doi.org/10.1590/S1415-43662008000300007
[49]	Melo-Abreu, J.P., Barranco, D., Cordeiro, A.M., Tous, J., Rogado, B.M. and Villalobos, F.J. (2004) Modelling Olive Flowering Date Using Chilling for Dormancy Release and Thermal Time. Agricultural and Forest Meteorology, 125, 117-127. http://dx.doi.org/10.1016/j.agrformet.2004.02.009