Export file:

Format

  • RIS(for EndNote,Reference Manager,ProCite)
  • BibTex
  • Text

Content

  • Citation Only
  • Citation and Abstract

Leaf area estimation in Jatropha curcas (L.): an update

1 Plant Physiology Laboratory, Federal University of Pernambuco, Department of Botany, CCB, Recife, PE, Brazil, 50670901
2 Faculty of Agricultural Science, University of Córdoba, Montería, Colombia

Special Issues: Biofuels: how they can improve the world

We aimed to propose a reliable and accurate model using non-destructive measurements of leaf length (L) and/or width (W) for estimating leaf area (LA) of three genotypes of purging nut (Jatropha curcas L.), i.e. Astrea and Barranca, both Colombian and a Mexican genotype. For model construction, ~500 healthy leaves were collected from at least 20 healthy plants naturally grown at each locations, and encompassed the full spectrum of measurable leaf sizes. Equations with L and/or W were generated; however, the best fit were made when product between L and W (LW). To validate these models, independent data set of 450 leaves were used. Thus, we developed a single model (Yi = β0 * LWβ1) with high precision and accuracy, random dispersion pattern of residuals and unbiased. In spite of this, a single equation, joining all the studied genotypes, was developed [LA = 0.822 * (LW)0.983; standard errors: β0 = 0.020, β1 = 0.004; R2a = 0.976], which greatly simplifies the process of measuring the leaf area of the genotypes, a fact that should be highlighted.
  Figure/Table
  Supplementary
  Article Metrics

References

1. Pecina-Quintero V, Anaya-López JL, Zamarripa-Colmenero A, et al. (2014) Genetic structure of Jatropha curcas L. in Mexico and probable centre of origin. Biomass Bioenerg 60: 147–155.

2. Silitonga AS, Hassan MH, Ong HC, et al. (2017) Analysis of the performance, emission and combustion characteristics of a turbocharged diesel engine fuelled with Jatropha curcas biodiesel-diesel blends using kernel-based extreme learning machine. Environ Sci Pollut Res 24: 25383–25405.    

3. Mardhiah HH, Ong HC, Masjuki HH, et al. (2017) Investigation of carbon-based solid acid catalyst from Jatropha curcas biomass in biodiesel production. Energy Convers Manag 144: 10–17.    

4. Alburquerque N, García-Almodóvar RC, Valverde JM, et al. (2017) Characterization of Jatropha curcas accessions based in plant growth traits and oil quality. Ind Crops Prod 109: 693–698.    

5. Corte-Real N, Endres L, Santos KPO, et al. (2016) Morphoanatomy and ontogeny of the fruit and seeds of Jatropha curcas L.: A promising biofuel plant. In: Segura-Campos MR, Betancur-Ancova D, editors. The Promising Future of Jatropha curcas: Proprieties and potential applications. Hauppauge, NY: Nova Science Publishers, Inc. pp. 141–158.

6. Heller J (1996) Physic nut. Jatropha curcas L. Promoting the conservation and use of underutilized and neglected crops. Rome: International Plant Genetic Resources Institute (IPGRI). 66 p.

7. Pandey VC, Singh K, Singh JS, et al. (2012) Jatropha curcas: A potential biofuel plant for sustainable environmental development. Renew Sust Energy Rev 16: 2870–2883.    

8. Pompelli MF, Ferreira DTRG, Cavalcante PPGS, et al. (2010) Environmental influence on the physico-chemical and physiological properties of Jatropha curcas L. seeds. Aust J Bot 58: 421–427.    

9. Contran N, Chessa L, Lubino M, et al. (2013) State-of-the art of the Jatropha curcas productive chain: From sowing to biodiesel and by-products. Ind Crops Prod 42: 202–215.    

10. Divakara BN, Upadhyaya HD, Wani SP, et al. (2010) Biology and genetic improvement of Jatropha curcas L. A review. Appl Energ 87: 732–742.    

11. Pompelli MF, Orozco AJ, Oliveira MTO, et al. (2011) Crise energética mundial e o papel do Brasil na problemática de biocombustíveis. Agronomía Colombiana 29: 361–371.

12. Openshaw K (2000) A review of Jatropha curcas: an oil plant of unfulfilled promise. Biomass Bioenerg 19: 1–15.    

13. Chel A, Kaushik G (2011) Renewable energy for sustainable agriculture. Agron Sustain Dev 31: 91–118.    

14. Gutiérrez-Antonio C, Romero-Izquierdo AG, Gómez-Castro FI, et al. (2016) Simultaneous energy integration and intensification of the hydrotreating process to produce biojet fuel from Jatropha curcas. Chem Eng Process 110: 134–145.    

15. Beaver A, Castaño AG, Díaz MS (2016) Life cycle analysis of Jatropha curcas as a sustainable biodiesel feedstock in Argentina. Chem Engin Trans 50.

16. Galati A, Crescimanno M, Gristina L, et al. (2016) Actual provision as an alternative criterion to improve the efficiency of payments for ecosystem services for C sequestration in semiarid vineyards. Agric Systems 144: 58–64.    

17. Keesstra SD, Bouma J, Wallinga J, et al. (2016) The significance of soils and soil science towards realization of the United Nations Sustainable Development Goals. Soil 2: 111–128.    

18. Brittaine R, Lutaladio N (2010) Jatropha: A Smallholder Bioenergy Crop The Potential for Pro-Poor Development. Rome Italy: Plant Production and Protection Division FAO. 96 p.

19. Díaz S, Kattge J, Cornelissen JHC, et al. (2016) The global spectrum of plant form and function. Nature 529: 167–171.    

20. Cristofori V, Rouphael Y, Mendoza-de Gyves E, et al. (2007) A simple model for estimating leaf area of hazelnut from linear measurements. Sci Hort 113: 221–225.    

21. Pompelli MF, Antunes WC, Ferreira DTRG, et al. (2012) Allometric models for non-destructive leaf area estimation of the Jatropha curcas. Biomass Bioenerg 36: 77–85.    

22. Blanco FF, Folegatti MV (2005) Estimation of leaf area for greenhouse cucumber by linear measurements under salinity and grafting. Sci Agr 62: 305–309.    

23. Antunes WC, Pompelli MF, Carretero DM, et al. (2008) Allometric models for non-destructive leaf area estimation in coffee (Coffea arabica and Coffea canephora). Ann Appl Biol 153: 33–40.    

24. Keramatlou I, Sharifani M, Sabouri H, et al. (2015) A simple linear model for leaf area estimation in Persian walnut (Juglans regia L.). Sci Hort 184: 36–39.    

25. Liu Z, Zhu Y, Li F, et al. (2017) Non-destructively predicting leaf area, leaf mass and specific leaf area based on a linear mixed-effect model for broadleaf species. Ecol Indic 78: 340–350.    

26. Peksen E (2007) Non-destructive leaf area estimation model for faba bean (Vicia faba L.). Sci Hortic-Amsterdam 113: 322–328.    

27. Thomas B (2017) Leaf Development. In: Thomas B, Murray BG, Murphy DJ, editors. Encyclopedia of Applied Plant Sciences (Second Edition). San Diego: Elsevier. pp. 191–197.

28. Kirkman LK, Sharitz RR (1994) Vegetation disturbance and maintenance of diversity in intermittently flooded Carolina bays in South Carolina. Ecol Appl 4: 177–188.    

29. Collins SL (1987) Interaction of disturbance in tallgrass prairie: a field experiment. Ecology 68: 1243–1250.    

30. Steel M, Penny D (2000) Parsimony, likelihood, and the role of models in molecular phylogenetics. Mol Biol Evol 17: 839–850.    

31. Cumming G, Fidler F, Vaux DL (2007) Error bars in experimental biology. J Cell Biol 177: 7–11.    

32. Walther BA, Moore JL (2005) The concepts of bias, precision and accuracy, and their use in testing the performance of species richness estimators, with a literature review of estimator performance. Ecography 28: 815–829.    

33. Messier J, McGill BJ, Lechowicz MJ (2010) Ecol Lett 13: 838–848.

34. Pinheiro J, Bates D, DebRoy S, et al. (2017) nlme:Linear and Nonlinear Mixed Effects Models. R package version 3.1–131. Viena, Austria: R Foundation for Statistical Computing.

35. Achten WMJ, Maes WH, Reubens B, et al. (2010) Biomass production and allocation in Jatropha curcas L. seedlings under different levels of drought stress. Biomass Bioenerg 34: 667–676.

36. Severino LS, Vale LS, Beltrão NEM (2007) A simple method for measurement of Jatropha curcas leaf area. Rev Bras Ol Fibros 11: 9–14.

37. Ahmed N, Khan D (2011) Leaf area estimation in Jatropha curcas L. Int J Biol Biotech 8: 401–407.

38. Zuur AF, Elena NI, Elphick CS (2010) A protocol for data exploration to avoid common statistical problems. Method Ecol Evol 1: 3–14.    

39. Kandiannan K, Parthasarathy U, Krishnamurthy KS, et al. (2009) Modeling individual leaf area of ginger (Zingiber officinale Roscoe) using leaf length and width. Sci Hortic-Amsterdam 120: 532–537.    

40. Souza MC, Amaral CL (2015) Non-destructive linear model for leaf area estimation in Vernonia ferruginea Less. Braz J Biol 75: 152–156.    

41. Villar R, Ruiz-Robleto J, Ubera JL, et al. (2013) Exploring variation in leaf mass per area (LMA) from leaf to cell: an anatomical analysis of 26 woody species. Am J Bot 100: 1969–1980.    

42. Zhang L, Pan L (2011) Allometric models for leaf area estimation across different leaf-age groups of evergreen broadleaved trees in a subtropical forest. Photosynthetica 49: 219–226.    

43. Tondjo K, Brancheriau L, Sabatier SA, et al. (2015) Non-destructive measurement of leaf area and dry biomass in Tectona grandis. Trees 29: 1625–1631.    

© 2018 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution Licese (http://creativecommons.org/licenses/by/4.0)

Download full text in PDF

Export Citation

Article outline

Show full outline
Copyright © AIMS Press All Rights Reserved