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ARS Home » Plains Area » Temple, Texas » Grassland Soil and Water Research Laboratory » Research » Publications at this Location » Publication #312151
Title: Two-year growth cycle sugarcane crop parameter attributes and their application in modeling

Author
item MEKI, MANYOWA - Texas Agrilife Research
item Kiniry, James
item YOUKHANA, ADEL - University Of Hawaii
item CROW, SUSAN - University Of Hawaii
item OGOSHI, RICHARD - University Of Hawaii
item NAKAHATA, MAE - Hawaiian Commercial And Sugar Company
item Tirado-Corbala, Rebecca
item Anderson, Raymond - Ray
item OSORIO, JAVIER - Texas Agrilife Research
item JEONG, JAEHAK - Texas Agrilife Research

Submitted to: Agronomy Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/1/2014
Publication Date: 5/12/2015
Publication URL: http://handle.nal.usda.gov/10113/60953
Citation: Meki, M.N., Kiniry, J.R., Youkhana, A.H., Crow, S.E., Ogoshi, R.M., Nakahata, M.H., Tirado-Corbala, R., Anderson, R.G., Osorio, J., Jeong, J. 2015. Two-year growth cycle sugarcane crop parameter attributes and their application in modeling. Agronomy Journal. 107(4):1310-1320.

Interpretive Summary: Sugarcane (Saccharum officinarum L.) production in Hawaii has declined since the 1970s due to a number of factors that include low prices, high labor costs, competition from artificial sweeteners, and low-cost production from such countries as Mexico, Brazil, India, and China. Recently, competition for water resources coupled with declining precipitation has become the major constraint to sugarcane productivity and profitability at the only remaining sugarcane plantation in Hawaii - the Hawaii Commercial & Sugar Company (HC&S)-based on Maui Island. Crop simulation models like ALMANAC (Agricultural Land Management Alternatives with Numerical Assessment Criteria) have the potential to evaluate management practices that optimize sugarcane growth and productivity with limited water resources. However, prior to applying the model, there is a need to determine key sugarcane-specific crop parameters that are needed to simulate crop growth in these models. These crop parameters were developed from field experiments conducted at HC&S plantation. The crop parameters, along with weather, soils and management practices for 7 HC&S fields were used to calibrate and test the ALMANAC model’s capability to accurately simulate historical sugarcane yields. Overall, the ALMANAC model was able to accurately simulate sugarcane yields across 7 different soil types and under multiple management scenarios, in particular applied irrigation water, N & P fertilizer inputs and various planting and harvest dates demonstrating that the model can be used as a decision-making tool for obtaining accurate and cost-effective estimates of sugarcane yields and optimum irrigation application rates and timing.

Technical Abstract: Sugarcane (Saccharum officinarum L.) production in Hawaii has declined since the 1970s due to a number of factors that include low prices, high labor costs, competition from artificial sweeteners and low-cost production from such countries as Mexico, Brazil, India, and China. Recently, competition for water resources coupled with declining precipitation has become the major constraints to sugarcane productivity and profitability at the only remaining sugarcane plantation in Hawaii - the Hawaii Commercial & Sugar Company (HC&S) based on Maui Island. Crop simulation models like ALMANAC (Agricultural Land Management Alternatives with Numerical Assessment Criteria) have the potential to evaluate management practices that optimize sugarcane growth and productivity with limited water resources. However, prior to applying the model, there is a need to determine key sugarcane-specific crop parameters that are needed to simulate crop growth in these models, such as leaf area index (LAI), light extinction coefficient (Kc), radiation use efficiency (RUE), maximum plant height and rooting depth, plant density, potential heat units (PHUs), biomass yield and percent moisture content at harvest, N and P nutrient contents at early seedling emergence, midseason and at maturity. These crop parameters were determined from field experiments conducted at HC&S plantation. We applied these crop parameters, along with weather, soils and management practices for 7 HC&S fields to calibrate and test the ALMANAC model’s capability to accurately simulate historical sugarcane yields. Overall, the ALMANAC model was able to accurately simulate sugarcane yields across 7 different soil types and under multiple management scenarios, in particular applied irrigation water, N & P fertilizer inputs and various planting and harvest dates demonstrating that the model can be used as a decision-making tool for obtaining accurate and cost-effective estimates of sugarcane yields and optimum irrigation application rates and timing. The mean simulation percent (%) errors ranged from -6.4% to 1.8%. The slope and intercept of the regression line of simulated versus measured yields were not significantly different from one and zero, respectively. In addition, the calculated Paired t test statistic of 0.40 with 35 degrees of freedom, and the Pearson correlation coefficient of 0.96 also showed that there were no significant differences (P = 0.05) between measured and simulated yields. The coefficients of variation (CV) of the measured and simulated yields were 5.0% and 5.2%, respectively.