Delineating productivity zones in a citrus grove using citrus production, tree growth and temporally stable soil data
The productivity of a citrus grove with variation in tree growth was mapped to delineate zones of productivity based on several indicator properties. These properties were fruit yield, ultrasonically measured tree canopy volume, normalized difference vegetation index (NDVI), elevation and apparent electrical conductivity (ECa). The spatial patterns of soil series, soil color and ECa, and their correspondence with the variation in yield emphasized the importance of variation in the soil in differentiating the productivity of the grove. Citrus fruit yield was positively correlated with canopy volume, NDVI and ECa, and yield was negatively correlated with elevation. Although all the properties were strongly correlated with yield and were able to explain the productivity of the grove, citrus tree canopy volume was most strongly correlated (r = 0.85) with yield, explaining 73% of its variation. Tree canopy volume was used to classify the citrus grove into five productivity zones termed as ‘very poor’, ‘poor’, ‘medium’, ‘good’ and ‘very good’ zones. The study showed that productivity of citrus groves can be mapped using various attributes that directly or indirectly affect citrus production. The productivity zones identified could be used successfully to plan soil sampling and characterize soil variation in new fields.
KeywordsCitrus Soil Variation Productivity zone Yield Canopy volume NDVI Elevation Apparent electrical conductivity (ECa)
This research was supported by the Florida Agricultural Experiment Station and the Hunt Brothers graduate fellowship. The authors would like to thank Mosaic Co. for the use of their grove, Kevin Hostler, Reza Ehsani, Sherrie Buchanan, and other staff members of the CREC and SWS departments who assisted in this study. Mention of trade names and commercial products is solely for the purpose of providing specific information and does not imply recommendation by the University of Florida or its cooperators.
- Doerge, T. (1999). Management zone concepts. SSMG-2. In Site specific management guidelines. Norcross, GA: Potash and Phosphate Institute. http://ppifarorg/ssmg. Accessed 9 Aug 2010.
- Ehsani, R., Schumann, A., & Salyani, M. (2009). Variable rate technology for Florida citrus1. Gainesville: Florida Cooperative Extension Service. AE444. University of Florida, Institute of Food and Agricultural Science. edis.ifas.ufl.edu/document_ae444. Accessed 29 July 2010.
- Khosla, R., & Alley, M. M. (1999). Soil-specific nitrogen management on mid-Atlantic coastal plain soils (USA). Better Crops, 83, 6–7.Google Scholar
- Khosla, R., Fleming, K., Delgado, J. A., Shaver, T. M., & Westfall, D. G. (2002). Use of site-specific management zones to improve nitrogen management for precision agriculture. Journal Soil and Water Conservation (Ankeny), 57, 513–518.Google Scholar
- Land Boundary Information System–Florida Department of Environmental Protection. (2004). Aerial photograph for Florida citrus. data.labins.org/2004/MappingData/DOQQ/. Accessed 19 July 2010.
- Muchovej, R. M. (2001). Application of precision agricultural techniques to Florida’s mineral soils. Fla. Coop. Ext. Serv. SS-AGR-172. Gainesville: University of Florida, Institute of Food and Agricultural Sciences. edis.ifas.ufl.edu/AG118. Accessed 9 Aug 2010.
- Muchovej, R. M., Hanlon, E. A., Ozores-Hampton, M., Shukla, S., Roka, F. M., Yamataki, H., et al. (2005). Sugarcane production in Southwest Florida: Mineral soils and amendments. Gainesville: Fla. Coop. Ext. Serv. SL 230. University of Florida, Institute of Food and Agricultural Sciences. edis.ifas.ufl.edu/SC073. Accessed 9 Aug 2010.
- Muchovej, R. M., Luo, Y., Shine, J., & Jones, J. (2000). Nutritional problems associated with low yield of sugarcane on mineral soils. Soil and Crop Science Society of Florida Proceedings, 59, 146–149.Google Scholar
- Mulla, D. J., & Bhatti, A. U. (1997). An evaluation of indicator properties affecting spatial patterns in N and P requirements for winter wheat yield. In J. V. Stafford (Ed.), Precision agriculture ′97 (pp. 145–153). Oxford, UK: BIOS Scientific Publishers.Google Scholar
- Obreza, T. A., Zekri, M., & Hanlon, E. W. (2008a). Soil and leaf tissue testing. In T. A. Obreza & K. L. Morgan (Eds.), Nutrition of Florida citrus trees (2nd ed., pp. 24–32). Gainesville: Florida Cooperative Extension Service. SL253. University of Florida, Institute of Food and Agricultural Sciences. edis.ifas.ufl.edu/SS478. Accessed 9 Aug 2010.
- Obreza, T. A., Zekri, M., & Stephen., H. F. (2008b). General soil fertility and citrus tree nutrition. In T. A. Obreza & K. L. Morgan (Eds.), Nutrition of Florida citrus trees (2nd ed., pp. 16–22). Gainesville: Florida Cooperative Extension Service SL253. University of Florida, Institute of Food and Agricultural Sciences. edis.ifas.ufl.edu/SS478. Accessed 19 July 2010.
- Official Soil Series Descriptions (OSD). (1999). With series extent mapping capabilities. USDA. NRCS. http://soils.usda.gov/technical/classification/osd. Accessed 29 July 2010.
- Schumann, A. W., Fares, A., Alva, A. K., & Paramasivam, S. (2003). Response of ‘Hamlin’ orange to fertilizer source, rate and irrigated area. Proceedings of Florida State Horticultural Society, 116, 256–260.Google Scholar
- Schumann, A. W., Hostler, K. H., Miller, W. M., & Zaman, Q. (2004). Sensor-based automatic yield monitoring for manually harvested citrus. Pap. 041098. St. Joseph, MI: ASAE.Google Scholar
- Schumann, A. W., & Zaman, Q. (2003). Mapping water table depth by electromagnetic induction. Applied Engineering in Agriculture, 19, 675–688.Google Scholar
- Statistical Analysis System Institute. (2003). SAS/STAT Guide for personal computers. Version 9.1. Cary, NC: SAS Institute Incorporation.Google Scholar
- Wheaton, T. A., Whitney, J. D., Castle, W. S., Muraro, R. P., Browning, H. W., & Tucker, D. P. H. (1995). Citrus scion and rootstock, topping height, and tree spacing affect tree size, yield, fruit quality, and economic return. Journal of the American Society for Horticultural Science, 120, 861–870.Google Scholar
- Whitney, J. D., Miller, W. M., Wheaton, T. A., Salyani, M., & Schueller, J. K. (1999). Precision farming applications in Florida citrus. Applied Engineering in Agriculture, 15, 399–403.Google Scholar
- Wibawa, W., Dludlu, D., Swenson, L. J., Hopkins, D., & Dahnke, W. (1993). Variable fertilizer application based on yield goal, soil fertility, and soil map unit. Journal of Production Agriculture, 6, 255–261.Google Scholar
- Zaman, Q., Schumann, A. W., & Hostler, H. K. (2006). Rapid estimation of citrus tree damage from hurricanes in Florida using an ultrasonic tree measurement system. HortTechnology, 16, 339–344.Google Scholar
- Zaman, Q., Schumann, A. W., & Miller, W. M. (2005). Variable rate nitrogen application in Florida citrus based on ultrasonically-sensed tree size. Applied Engineering in Agriculture, 21, 331–335.Google Scholar