An analysis of the factors that influence sugarcane yield in Northern Argentina using classification and regression trees

Field Crops Research

Volumn 112, Issue 2-3, 2009, Pages 149-157

  Ferraro, Diego O ^a   Rivero, Dario E ^a   Ghersa, Claudio M ^a  

^a Instituto de Investigaciones Fisiologicas y Ecologicas   (Argentina)

Author keywords

Cane yield variability; CART analysis; Data mining; Non parametric method

Indexed keywords

BIOMASS; CROP YIELD; DATA MINING; DATA SET; ENVIRONMENTAL CONDITIONS; MULTIVARIATE ANALYSIS; REGRESSION ANALYSIS; SUGAR CANE;

ARGENTINA; SOUTH AMERICA;

SACCHARUM OFFICINARUM;

EID: 66049131606     PISSN: 03784290     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.fcr.2009.02.014     Document Type: Article

References (44)

1. Anderson D.L., Portier K.M., Obreza T.A., Collins M.E., and Pitts D.J. Tree regression analysis to determine effects of soil variability on sugarcane yields. Soil Sci. Soc. Am. J. 63 (1999) 592-600
2. Bakker M.M., Govers G., Ewert F., Rounsevell M., and Jones R. Variability in regional wheat yields as a function of climate, soil and economic variables: assessing the risk of confounding. Agric. Ecosyst. Environ. 110 (2005) 195-209
3. Basanta M.V., Dourado-Neto D., Reichardt K., Bacchi O.O.S., Oliveira J.C.M., Trivelin P.C.O., Timm L.C., Tominaga T.T., Correchel V., Cassaro F.A.M., Pires L.F., and de Macedo J.R. Management effects on nitrogen recovery in a sugarcane crop grown in Brazil. Geoderma 116 (2003) 235-248
4. Belsley D.A., Kuh E., and Welsch R.E. Regression Diagnostics: Identifying Influential Data and Sources of Collinearity (1980), Wiley, New York
5. Braunbeck O., Bauen A., Rosillo-Calle F., and Cortez L. Prospects for green cane harvesting and cane residue use in Brazil. Biomass Bioenergy 17 (1999) 495-506
6. Breiman L., Friedman R., Olshen R., and Stone C. Classification and Regression Trees (1984), Pacific Grove, California
7. de Wit C.T. Resource use efficiency in agriculture. Agric. Syst. 40 (1992) 125-151
8. De'ath G., and Fabricius K.E. Classification and regression trees: a powerful yet simple technique for ecological data analysis. Ecology 81 (2000) 3178-3192
9. Dolan B.J., and Parker G.R. Ecosystem classification in a flat, highly fragmented region of Indiana, U.S.A. Forest Ecol. Manag. 219 (2005) 109-131
10. Dzeroski S., and Drumm D. Using regression trees to identify the habitat preference of the sea cucumber (Holothuria leucospilota) on Rarotonga, Cook Islands. Ecol. Model. 170 (2003) 219-226
11. Ellis R.N., Basford K.E., Cooper M., Leslie J.K., and Byth T.L.D.E. A methodology for analysis of sugarcane productivity trends. I. Analysis across districts. Aust. J. Agric. Res. 52 (2001) 1001-1009
12. Etter A., McAlpine C., Wilson K., Phinn S., and Possingham H. Regional patterns of agricultural land use and deforestation in Colombia. Agric. Ecosyst. Environ. 114 (2006) 369-386
13. Evenson C.I., Muchow R.C., El-Swaify S.A., and Osgood R.V. Yield accumulation in irrigated sugarcane. I. Effect of crop age and cultivar. Agronomy J. 89 (1987) 638-646
14. Garside A.L., Smith M.A., Chapman L.S., Hurney A.P., and Magarey R.C. The yield plateau in the Australian sugar industry: 1970-1990. In: Keating B.A., and Wilson J.R. (Eds). Intensive Sugarcane Production: Meeting the Challenges Beyond 2000 (1997), CAB International, Wallingford, UK 103-124
15. Gilbert R.A., Shine J.J.M., Miller J.D., Rice R.W., and Rainbolt C.R. The effect of genotype, environment and time of harvest on sugarcane yields in Florida, U.S.A. Field Crops Res. 95 (2006) 156-170
16. Glaz B., and Ulloa M.F. Graphic analysis for comparing commercial production practices. J. Prod. Agric. 4 (1990) 135-139
17. Grant R.H., Hollinger S.E., Hubbard K.G., Hoogenboom G., and Vanderlip R.L. Ability to predict daily solar radiation values from interpolated climate records for use in crop simulation models. Agric. Forest Meteorol. 127 (2004) 65-75
18. Higgins A.J., Muchow R.C., Rudd A.V., and Ford A.W. Optimising harvest date in sugar production: a case study for the Mossman mill region in Australia: I. Development of operations research model and solution. Field Crops Res. 57 (1998) 153-162
19. Inman-Bamber N.G., and Smith D.M. Water relations in sugarcane and response to water deficits. Field Crops Res. 92 (2005) 185-202
20. Jain A.K., and Dubes R.C. Algorithms for Clustering Data (1988), Prentice-Hall, Englewood Hills, NJ
21. Kingston G. Recognising the impact of climate on CCS of sugarcane across tropical and sub-tropical regions of the Australian sugar industry. Proc. Aust. Soc. Sugar Cane Technol. (2002) 24 (CD-ROM)
22. Lark R.M. An empirical method for describing the joint effects of environmental and other variables on crop yield. Ann. Appl. Biol. 131 (1997) 141-159
23. Lawes R.A., and Fuelling T.J. The possible pitfalls of using productivity data to evaluate variety performance. In: Hogarth D. (Ed). Proceedings Australian Society of Sugar Cane Technologists. Australian Society of Sugar Cane Technologists. Bundaberg (2000) 277-282
24. Lawes R.A., and Lawn R.J. Applications of industry information in sugarcane production systems. Field Crops Res. 92 (2005) 353-363
25. Lawes R.A., Lawn R.J., Wegener M.K., and Basford K.E. Understanding and managing the late time of ratooning effect on cane yield. Proc. Aust. Soc. Sugar Cane Technol. 24 (2002) 160-165
26. Lawes R.A., Lawn R.J., Wegener M.K., and Basford K.E. The evaluation of the spatial and temporal stability of sugarcane farm performance based on yield and commercial cane sugar. Aust. J. Agric. Res. 55 (2004) 335-344
27. Lawes R.A., McDonald L.M., Wegener M.K., Basford K.E., and Lawn R.J. Factors affecting cane yield and commercial cane sugar in the Tully district. Aust. J. Exp. Agriculture 42 (2002) 473-480
28. Legendre P. Spatial autocorrelation: trouble or new paradigm?. Ecology 74 (1993) 1659
29. Lisson S.N., Inman-Bamber N.G., Robertson M.J., and Keating B.A. The historical and future contribution of crop physiology and modelling research to sugarcane production systems. Field Crops Res. 92 (2005) 321-335
30. Marshall R.J. The use of classification and regression trees in clinical epidemiology. J. Clin. Epidemiol. 54 (2001) 603-609
31. Nelson P.N., and Ham G.J. Exploring the response of sugar cane to sodic and saline conditions through natural variation in the field. Field Crops Res. 66 (2000) 245-255
32. Patterson H.D., and Thompson R. Recovery of interblock information when blocks sizes are unequal. Biometrika 58 (1971) 545-554
33. Perez-Quezada J.F., Pettygrove G.S., and Plant R.E. Spatial-temporal analysis of yield and soil factors in two four-crop-rotation fields in the Sacramento Valley. California Agron J. 95 (2003) 676-687
34. Roel A., Firpo H., and Plant R.E. Why do some farmers get higher yields? Multivariate analysis of a group of Uruguayan rice farmers. Comput. Electronics Agriculture 58 (2007) 78-92
35. Russell J.S., Wegener M.K., and Valentine T.R. Effect of weather variables on C.C.S. at Tully simulated by the AUSCANE model. Proc. Aust. Soc. Sugar Cane Technol. 13 (1991) 157-163
36. Silva A.J.N., Ribeiro M.R., Carvalho F.G., Silva V.N., and Silva L.E.S.F. Impact of sugarcane cultivation on soil carbon fractions, consistence limits and aggregate stability of a Yellow Latosol in Northeast Brazil. Soil Tillage Res. 94 (2007) 420-424
37. Steinberg D., and Colla P. CART: Tree-Structured Non-Parametric Data Analysis (1995), Salford Systems, San Diego, CA, U.S.A.
38. Thorburn P.J., Meier E.A., and Probert M.E. Modelling nitrogen dynamics in sugarcane systems: recent advances and applications. Field Crops Res. 92 (2005) 337-351
39. Tittonell P., Shepherd K.D., Vanlauwe B., and Giller K.E. Unravelling the effects of soil and crop management on maize productivity in smallholder agricultural systems of western Kenya-An application of classification and regression tree analysis. Agriculture Ecosystems Environ. 123 (2008) 137-150
40. Vallis I., Parton W.J., Keating B.A., and Wood A.W. Simulation of the effects of trash and N fertilizer management on soil organic matter levels and yields of sugarcane. Soil Tillage Res. 38 (1996) 115-132
41. van Ittersum M.K., Leffelaar P.A., van Keulen H., Kropff M.J., Bastiaans L., and Goudriaan J. On approaches and applications of the Wageningen crop models. Eur. J. Agronomy 18 (2003) 201-234
42. Wood W. Management of crop residues following green harvesting of sugarcane in North Queensland. Soil Tillage Res. 20 (1991) 69-85
43. Yadav R.L., and Verma R.P. Crop residue management to conserve soil organic matter content in sugarcane-based crop rotations. Bioresour. Technol. 51 (1995) 241-245
44. Zar J.H. Biostatistical Analysis (1999), Prentice-Hall, Inc., New Jersey 663 p.