Skip to main content

Advertisement

SpringerLink
Log in

Empirical models to predict LAI and aboveground biomass of Coffea arabica under full sun and shaded plantation: a case study of South of Minas Gerais, Brazil

  • Published:
Agroforestry Systems Aims and scope Submit manuscript

Abstract

Leaf area index (LAI) and above ground biomass (AGB) are two parameters that are difficult to measure but very useful. In this paper we investigated the relationship between coffee biophysical properties and LAI and AGB in two coffee production systems: full sun (FS) and shaded with macadamia nuts (SH). The paper proposes an empirical relationship for calculating coffee AGB and coffee LAI which avoids destructive methods, using simple field measurements and agrometeorological data. Here, we reported that LAI is related to canopy structure but subject to strong seasonal variations, which can be identified using water requirements satisfaction index (WRSI). Coffee LAI answers to the decreased WRSI with 1 month lag (WRSI-1) and LAI values decreases more for FS systems than for SH systems during dry periods. The best empirical model to predict LAI for FS coffee production system was based on canopy height (ch) and WRSI-1 value. For SH systems, the best model used ch, WRSI-1 and the height of the first pair of branches. Coffee AGB values were measured using destructive analyses and an empirical equation was developed. Both coffee production systems stocked carbon, whereas the SH system stocked an increased carbon amount provided by the macadamia trees that contributed with 15 % of the total carbon above ground. Both systems can be considered mitigation techniques since they are able to remove atmospheric carbon and stock it in the biomass, which has been largely proposed as a compensation mechanism for greenhouse gas emissions.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Similar content being viewed by others

References

  • Andrade HJ, Ibrahim M (2003) ¿Cómo monitorear el secuestro de carbono en los sistemas silvopastoriles? Agrofor Am 10:109–116

    Google Scholar 

  • Asner GP, Scurlock JMO, Hicke JA (2003) Global synthesis of leaf area index observations: implications for ecological and remote sensing studies. Glob Ecol Biogeogr 12:191–205. doi:10.1046/j.1466-822X.2003.00026.x

    Article  Google Scholar 

  • Asner GP, Powell GVN, Mascaro J, Knapp DE, Clark JK, Jacobson J, Kennedy-Bowdoin T, Balaji A, Paez-Acosta G, Victoria E, Secada L, Valqui M, Hughes RF (2010) High-resolution forest carbon stocks and emissions in the Amazon. Proc Natl Acad Sci USA 107:16738–16742. doi:10.1073/pnas.1004875107

    Article  CAS  PubMed Central  PubMed  Google Scholar 

  • Assad ED, Pinto HS, Zullo J Jr, de Ávila AMH (2004) Impacto das mudanças climáticas no zoneamento agroclimático do café no Brasil. Pesqui Agropecu Bras 11:1057–1064. doi:10.1590/S0100-204X2004001100001

    Article  Google Scholar 

  • Band LE, Patterson P, Nemani R, Running SW (1993) Forest ecosystem processes at the watershed scale: incorporating hillslope hydrology. Agric For Meteorol 63:93–126. doi:10.1016/0168-1923(93)90024-C

    Article  Google Scholar 

  • Barbosa J, Martins G, Ferreira R, Pennacchi J, Souza V, Soares A (2012) Estimativa do IAF de cafeeiro a partir do volume de folhas e arquitetura da planta. Coffee Sci 7:267–274

    Google Scholar 

  • Barradas VL, Fanjul L (1986) Microclimatic characterization of shaded and open-grow coffee (Coffea arábica L.) plantations in Mexico. Agric For Meteorol 38:101–112

    Article  Google Scholar 

  • Beer J, Muschler R, Kass D, Somarriba E (1998) Shade management in coffee and cacao plantations. Agrofor Syst 38:139–164

    Article  Google Scholar 

  • Bernardes T, Moreira MA, Adami M, Giarolla A, Rudorff BFT (2012) Monitoring biennial bearing effect on coffee yield using MODIS remote sensing imagery. Remote Sens 4:2492–2509. doi:10.3390/rs4092492

    Article  Google Scholar 

  • Boulay M, Somarriba E, Olivier A (2000) Calidad de Coffea arabica bajo sombra de Erythrina poeppigiana a diferentes elevaciones en Costa Rica. Agrofor Am 7:40–42

    Google Scholar 

  • Breda N (2003) Ground-based measurements of leaf area index: a review of methods, instruments and current controversies. J Exp Bot 54:2403–2417. doi:10.1093/jxb/erg263

    Article  CAS  PubMed  Google Scholar 

  • Breuer L, Eckhardt K, Frede HG (2003) Plant parameter values for models in temperate climates. Ecol Model 169:237–293. doi:10.1016/S0304-3800(03)00274-6

    Article  Google Scholar 

  • Breugel MV, Ransijn J, Craven D, Bongers F, Hall JS (2011) Estimating carbon stock in secondary forests: decisions and uncertainties associated with allometric biomass models. For Ecol Manag 262:1648–1657. doi:10.1016/j.foreco.2011.07.018

    Article  Google Scholar 

  • Brown S (2002) Measuring carbon in forests: current status and future challenges. Environ Pollut 116:363–372. doi:10.1016/S0269-7491(01)00212-3

    Article  CAS  PubMed  Google Scholar 

  • Brown S, Iverson LR (1992) Biomass estimation for tropical forests. World Resour Rev 4:366–384

    Google Scholar 

  • Brown S, Gillespie AJR, Lugo AE (1989) Biomass estimation methods for tropical forests with applications to forest inventory data. For Sci 35:881–902

    Google Scholar 

  • Campbell GS, Norman JM (1989) The description and measurement of plant canopy structure. In: Russell G, Marshall B, Jarvis PG (eds) Plant canopies: their growth, form, and function, vol 31. Society for Experimental Biology, Cambridge University Press, Cambridge, pp 1–19

  • Canadell JG, Raupach MR (2008) Managing forests for climate change mitigation. Science 320(5882):1456–1457. doi:10.1126/science.1155458

    Article  CAS  PubMed  Google Scholar 

  • Cannell MGR (1975) Crop physiological aspects of coffee bean yield: a review. J Coffee Res 5:7–20

    Google Scholar 

  • Chave J, Condit R, Aguilar S, Hernandez A, Lao S, Perez R (2004) Error propagation and scaling for tropical forest biomass estimates. Philos Trans R Soc B 359:409–420. doi:10.1098/rstb.2003.1425

  • Chave J, Andalo C, Brown S et al (2005) Tree allometry and improved estimation of carbon stocks and balance in tropical forests. Oecologia 145:78–99. doi:10.1007/s00442-005-0100-x

    Article  Google Scholar 

  • DaMatta FM (2004) Ecophysiological constraints on the production of shaded and unshaded coffee: a review. Field Crops Res 86:99–114. doi:10.1016/j.fcr.2003.09.001

    Article  Google Scholar 

  • DaMatta FM, Ronchi CP, Maestri M, Barros R (2007) Ecophysiology of coffee growth and production. Braz J Plant Physiol 19:485–510. doi:10.1590/S1677-04202007000400014

    Article  CAS  Google Scholar 

  • Dixon RK (1995) Agroforestry systems: sources or sinks of greenhouse gases? Agrofor Syst 31:99–116. doi:10.1007/BF00711719

    Article  Google Scholar 

  • Dixon RK, Winjum JK, Andrasko KJ, Lee JJ, Schroeder PE (1994) Integrated systems: assessment of promising agroforest and alternative land-use practices to enhance carbon conservation and sequestration. Clim Change 30:1–23. doi:10.1007/BF01098474

    Google Scholar 

  • Doorenbos J, Pruitt WO (1977) Crop water requirements. FAO Irrigation and Drainage Paper No. 24. Food and Agricultural Organization of the United Nations, Rome

    Google Scholar 

  • dos Ricci MSF, Costa JR, Pinto AN, Santos VLA (2006) Cultivo orgânico de cultivares de café a pleno sol e sombreado. Pesqui Agropecu Bras 41:569–575. doi:10.1590/S0100-204X2006000400004

    Article  Google Scholar 

  • Dossa EL, Fernandes ECM, Reid WS, Ezui K (2008) Above- and belowground biomass, nutrient and carbon stocks contrasting an open-grown and a shaded coffee plantation. Agrofor Syst 72:103–115. doi:10.1007/s10457-007-9075-4

    Article  Google Scholar 

  • Ewel JJ (1999) Natural systems as models for the design of sustainable systems for land use. Agrofor Syst 45:1–21. doi:10.1023/A:1006219721151

    Article  Google Scholar 

  • Favarin JL, Dourado-Neto D, Garcia AG et al (2002) Equações para a estimativa do índice de área foliar do cafeeiro. Pesqui Agropecu Bras 37:769–773. doi:10.1590/S0100-204X2002000600005

    Article  Google Scholar 

  • Fehrmann L, Kleinn C (2006) General considerations about the use of allometric equations for biomass estimation on the example of Norway spruce in central Europe. For Ecol Manag 236:412–421. doi:10.1016/j.foreco.2006.09.026

    Article  Google Scholar 

  • Foody GM (2003) Remote sensing of tropical forest environments: towards the monitoring of environmental resources for sustainable development. Int J Remote Sens 24:4035–4046. doi:10.1080/0143116031000103853

    Article  Google Scholar 

  • Gay C, Estrada F, Conde C, Eakin H, Villers L (2006) Potential impacts of climate change on agriculture: a case of study of coffee production in Veracruz, Mexico. Clim Change 79:259–288. doi:10.1007/s10584-006-9066-x

    Article  Google Scholar 

  • Gower ST, Norman JM (1991) Rapid estimation of leaf area index in conifer and broadleaf plantations. Ecology 72:1896–1900

    Article  Google Scholar 

  • Gower ST, Reich PB, Son Y (1993) Canopy dynamics and aboveground production of five tree species with different leaf longevities. Tree Physiol 12:327–345. doi:10.1093/treephys/12.4.327

    Article  PubMed  Google Scholar 

  • Gregory PJ, Ingram JSI (2000) Global change and food and forest production: future scientific challenges. Agric Ecosyst Environ 82:3–14. doi:10.1016/S0167-8809(00)00212-7

    Article  Google Scholar 

  • Hall RJ, Davidson DP, Peddle DR (2003) Ground and remote estimation of leaf area index in Rocky Mountain forest stands, Kananaskis, Alberta. Can J Remote Sens 29:411–427. doi:10.5589/m03-012

    Article  Google Scholar 

  • Herbst M, Roberts JM, Rosier PTW, Gowing DJ (2006) Measuring and modeling the rainfall interception loss by hedgerows in southern England. Agric For Meteorol 141:244–256. doi:10.1016/j.agrformet.2006.10.012

    Article  Google Scholar 

  • Honza’k M et al (1996) Estimation of the leaf area index and total biomass of tropical regenerating forests: comparison of methodologies. In: Gash JHC, Nobre CA, Roberts JM, Victora RL (eds) Amazonian deforestation and climate. Wiley, Chichester, pp 365–381

    Google Scholar 

  • Houghton RA, Lawrence KT, Hackler JL, Brown S (2001) The spatial distribution of forest biomass in the Brazilian Amazon: a comparison of estimates. Glob Change Biol 7:731–746. doi:10.1111/j.1365-2486.2001.00426.x

    Article  Google Scholar 

  • IPCC guidelines for national greenhouse gas inventories, 2006

  • Jaramillo-Botero C, Martinez HEP, Santos RHS (2006) Características do café (Coffea arábica L.) sombreado no norte da América Latina e no Brasil: análise comparativa. Coffee Sci 1:94–102

    Google Scholar 

  • Jha S, Bacon CM, Philpott SM, Rice RA, Méndez VE, Läderach P (2011) A review of ecosystem services, farmer livelihoods, and value chains in shade coffee agroecosystems. In: Campbell BW, Lopez Ortiz S (eds) Integrating agriculture, conservation and ecotourism: examples from the field. Issues in agroecology: present status and future prospectus series, vol 1. Springer, Dordrecht, pp 141–208

    Chapter  Google Scholar 

  • Jonckheere I, Fleck S, Nackaerts K, Muys B, Coppin P, Weiss M, Baret F (2004) Review of methods for in situ leaf area index determination. Part I. Theories, sensors and hemispherical photography. Agric For Meteorol 121:19–35. doi:10.1016/j.agrformet.2003.08.027

    Article  Google Scholar 

  • Jose S (2009) Agroforestry for ecosystem services and environmental benefits: an overview. Agrofor Syst 76:1–10. doi:10.1007/s10457-009-9229-7

    Article  Google Scholar 

  • Ketterings QM, Coe R, Noordwijk MV, Ambagau Y, Palme CA (2001) Reducing uncertainty in the use of allometric biomass equations for predicting above-ground tree biomass in mixed secondary forests. For Ecol Manag 146:199–209. doi:10.1016/S0378-1127(00)00460-6

    Article  Google Scholar 

  • Kursten E (2000) Fuelwood production in agroforestry systems for sustainable land use and CO2 mitigation. Ecol Eng 16:69–72. doi:10.1016/S0925-8574(00)00054-9

    Article  Google Scholar 

  • Kuyah S, Dietz J, Muthuri C et al (2012) Allometric equations for estimating biomass in agricultural landscapes: I. Aboveground biomass. Agric Ecosyst Environ 158:216–224. doi:10.1016/j.agee.2012.05.011

    Article  Google Scholar 

  • Lagemann J, Heuveldop J (1983) Characterization and evaluation of agroforestry systems: the case of Acosta-Puriscal, Costa Rica. Agrofor Syst 1:101–115. doi:10.1007/BF00596352

    Article  Google Scholar 

  • Lin BB (2007) Agroforestry management as an adaptive strategy against potential microclimate extremes in coffee agriculture. Agric For Meteorol 144:85–94. doi:10.1016/j.agrformet.2006.12.009

    Article  Google Scholar 

  • Lin BB (2008) Microclimates effects on flowering success in coffee agroforestry systems. Am Eurasian J Agric Environ Sci 3:148–152

    Google Scholar 

  • Lin BB (2010) The role of agroforestry in reducing water loss through soil evaporation and crop transpiration in coffee agroecosystems. Agric For Meteorol 50:510–518. doi:10.1016/j.agrformet.2009.11.010

    Article  Google Scholar 

  • Liu WT, Kogan F (1996) Monitoring regional drought using the Vegetation Condition Index. Int J Remote Sens 17:2761–2782. doi:10.1080/01431169608949106

    Article  Google Scholar 

  • Liu J, Chen JM, Cihlar J, Park WM (1997) A process-based boreal ecosystem productivity simulator using remote sensing inputs. Remote Sens Environ 62:158–175. doi:10.1016/S0034-4257(97)00089-8

    Article  Google Scholar 

  • Lott JE, Howard SB, Black CR, Ong CK (2000) Allometric estimation of above-ground biomass and leaf area in managed Grevillea robusta agroforestry systems. Agrofor Syst 49:1–15. doi:10.1023/A:1006330830109

    Article  Google Scholar 

  • Masson V, Champeaux JL, Chauvin F, Meriguet C, Lacaze R (2003) A global database of land surface parameters at 1-km resolution in meteorological and climate models. J Clim 16:1261–1282. doi:10.1175/1520-0442-16.9.1261

    Article  Google Scholar 

  • Montagnini F, Nair PKR (2004) Carbon sequestration: an underexploited environmental benefit of agroforestry systems. Agrofor Syst 61:281–295. doi:10.1007/978-94-017-2424-1_20

    Google Scholar 

  • Monteith JL (1977) Climate and the efficiency of crop production. Philos Trans R Soc B 281:277–294

    Article  Google Scholar 

  • Nachar N (2008) The Mann–Whitney U: a test for assessing whether two independent samples come from the same distribution. Tutor Quant Methods Psychol 4:13–20

    Google Scholar 

  • Neumann HH, Den Hartog GD, Shaw RH (1989) Leaf-area measurements based on hemispheric photographs and leaf-litter collection in a deciduous forest during autumn leaf-fall. Agric For Meteorol 45:325–345

    Article  Google Scholar 

  • Overman JPM, Witte HJL, Saldarriaga JG (1994) Evaluation of regression models for aboveground biomass determination in Amazon rainforest. J Trop Ecol 10:207–218

  • Parresol BR (1999) Assessing tree and stand biomass: a review with examples and critical comparisons. For Sci 4:573–593

    Google Scholar 

  • Páscua DMS (2002) Cuantificación y valoración econômica Del servicio ambiental almacenamiento de carbono em sistemas agroflorestales de café em la Comarca Yassica Sur, Matagalpa, Nicarágua. Thesis, Centro Agronómico Tropical de Investigación y Enseñanza, Turrialba, 2002

  • Peeters LYK, Soto-Pinto L, Perales H, Montoya G, Ishiki M (2003) Coffee production, timber, and firewood in traditional and Inga-shaded plantations in Southern Mexico. Agric Ecosyst Environ 95:481–493. doi:10.1016/S0167-8809(02)00204-9

    Article  Google Scholar 

  • Perfecto I, Vandermeer J (1996) Microclimatic changes and the indirect loss of ant diversity in tropical agroecosystem. Oecologia 108:577–582. doi:10.1007/BF00333736

    Article  Google Scholar 

  • Pezzopane JRM, Marsetti MMS, Souza JM, Pezzopane JEM (2010) Condições microclimáticas em cultivo de café conilon a pleno sol e arborizado com nogueira macadâmia. Ciênc Rural 40:1257–1263. doi:10.1590/S0103-84782010005000098

    Article  Google Scholar 

  • Pezzopane JRM, de Souza PS, de Rolim GS, Gallo PB (2011) Microclimate in coffee plantation grown under Grevillea trees shading. Acta Sci Agron 33:201–206. doi:10.4025/actasciagron.v33i2.7065

    Article  Google Scholar 

  • Pinto HS et al (2008) A nova geografia da produção agrícola no Brasil. Embrapa Informática Agropecuária: Unicamp

  • Pocock MJO, Darren ME, Jane M (2010) The impact of farm management on species-specific leaf area index (LAI): farm-scale data and predictive models. Agric Ecosyst Environ 135:279–287. doi:10.1016/j.agee.2009.10.006

    Article  Google Scholar 

  • Ramirez GM, Zullo Junior J (2010) Estimativa de parâmetros biofísicos de plantios de café a partir de imagens orbitais de alta resolução espacial. Eng Agríc 30:468–479. doi:10.1590/S0100-69162010000300011

    Article  Google Scholar 

  • Rey R, Alvarez P (1991) Evaluación de diferentes ecuaciones de regresión en la estimación del área foliar del cafeto en vivero a partir de sus medidas lineares. Agrotec Cuba 23:69–74

    Google Scholar 

  • Roy PS, Ravan SA (1996) Biomass estimation using satellite remote sensing data—an investigation on possible approaches for natural forest. J Biosci 21:535–561. doi:10.1007/BF02703218

    Article  Google Scholar 

  • Running SW, Coughlan JC (1988) A general model of forest ecosystem processes for regional applications: 1. Hydrologic balance, canopy gas exchange and primary production processes. Ecol Model 42:125–154. doi:10.1016/0304-3800(88)90112-3

    Article  CAS  Google Scholar 

  • Running SW, Hunt ER (1993) Generalization of a forest ecosystem process model for other biomes, BIOME-BGC, and an application for global-scale models. In: Ehleringer J (ed) Scaling physiological processes: leaf to globe. Academic, New York, pp 141–158

    Chapter  Google Scholar 

  • Schroeder P, Brown S, Mo J, Birdsey R, Cieszwski C (1997) Biomass estimation for temperate broadleaf forests of the US using inventory data. For Sci 43:424–434

    Google Scholar 

  • Sediyama GC, Melo Junior JCF, Santos AR, Ribeiro A, Costa MH, Hamakawa PJ, Costa MH, Costa JMN, Costa LC (2001) Zoneamento agroclimático do cafeeiro (Coffea arabica L.) para o estado de Minas Gerais. Rev Bras Agrometeorol 9:501–509

    Google Scholar 

  • Segura M, Kanninen M, Suárez D (2006) Allometric models for estimating aboveground biomass of shade trees and coffee bushes grown together. Agrofor Syst 68:143–150. doi:10.1007/s10457-006-9005-x

    Article  Google Scholar 

  • Siles P, Harmand J, Vaast P (2010) Effects of Inga densiflora on the microclimate of coffee (Coffea arabica L.) and overall biomass under optimal growing conditions in Costa Rica. Agrofor Syst 78:269–286. doi:10.1007/s10457-009-9241-y

    Article  Google Scholar 

  • Soto-Pinto L, Anzueto M, Mendoza J, Ferrer GJ, de Jong B (2010) Carbon sequestration through agroforestry in indigenous communities of Chiapas, Mexico. Agrofor Syst 78:39–51. doi:10.1007/s10457-009-9247-5

    Article  Google Scholar 

  • Stroppiana D, Boschetti M, Confalonieri R, Stefano B, Alessandro BP (2006) Evaluation of LAI-2000 for leaf area index monitoring in paddy rice. Field Crops Res 99:167–170

    Article  Google Scholar 

  • Súarez Pascua DA (2002) Cuantifación y valoración economica del servicio ambiental almacenamiento de carbono en sistemas agroflorestales de café en la Comarca Yassica Sur, Matagalpa. Nicaragua, Dissertation, CATIE

  • Thornthwaite CW, Mather JR (1955) The water balance. In: Publication on Climatology, Vol.VIII, n.1. Drexel Institute of Technology, Laboratory of Climatology, Centerton, NJ, 104 p

  • Tiwari KA (1994) Mapping forest biomass through digital processing of IRS-1A data. Int J Remote Sens 15:1849–1866. doi:10.1080/01431169408954212

    Article  Google Scholar 

  • Weiss M, Baret F, Smith GJ, Jonckheere I, Coppin P (2004) Review of methods for in situ leaf area index (LAI) determination Part II. Estimation of LAI, errors and sampling. Agric For Meteorol 121:37–53. doi:10.1016/j.agrformet.2003.08.001

    Article  Google Scholar 

  • Zullo Junior J, Pinto HS, Assad ED, Avila AMH (2011) Potential for growing Arabica coffee in the extreme south of Brazil in a warmer world. Clim Change 109:535–548. doi:10.1007/s10584-011-0058-0

    Article  Google Scholar 

Download references

Acknowledgments

The authors wish to acknowledge EPAMIG for the study area, CNPQ, FAPESP and EMBRAPA CAFÉ for the financial support.

Author information

Authors and Affiliations

  1. Center of Research Meteorological and Climatological Applied to Agricultural (CEPAGRI) Cidade Universitária “Zeferino Vaz”, University of Campinas (UNICAMP), Campinas, SP, Brazil

    Priscila Pereira Coltri, Jurandir Zullo Junior, Hilton Silveira Pinto, Gustavo Coral & Camila Giorgi Lazarim

  2. Rennes 2 University, Rennes 2, France

    Vincent Dubreuil

  3. Federal University of Mato Grosso UFMT, Mato Grosso, Brazil

    Glaucia Miranda Ramirez

Authors
  1. Priscila Pereira Coltri
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jurandir Zullo Junior
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Vincent Dubreuil
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Glaucia Miranda Ramirez
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Hilton Silveira Pinto
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Gustavo Coral
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Camila Giorgi Lazarim
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Priscila Pereira Coltri.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Coltri, P.P., Zullo Junior, J., Dubreuil, V. et al. Empirical models to predict LAI and aboveground biomass of Coffea arabica under full sun and shaded plantation: a case study of South of Minas Gerais, Brazil. Agroforest Syst 89, 621–636 (2015). https://doi.org/10.1007/s10457-015-9799-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10457-015-9799-5

Keywords

Search

Navigation