Two-year growth cycle sugarcane crop parameter attributes and their application in modeling.

Published in Agron. J. 107:1310–1320 (2015) doi:10.2134/agronj14.0588 Copyright © 2015 by the American Society of Agronomy, 5585 Guilford Road, Madison, WI 53711. All rights reserved. No part of this periodical may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. ABSTRACT The renewed interest in the use of sugarcane (Saccharin officinarum L.) for biofuel could provide a viable market for potential Hawaiian sugarcane feedstock producers. In Hawaii, sugarcane is grown as an irrigated 2-yr cycle crop. There is however little information on crop parameter attributes of 2-yr cycle sugarcane. This field study on Maui, Hawaii, analyzed the relationship between sugarcane biomass accumulation and specific crop parameters. Overall, the high dry biomass yield (80.20 Mg ha–1) was the result of a high leaf area index (LAI, 7.50) and radiation use efficiency (RUE, 2.06 g MJ–1. The crop growth rate was highly correlated to LAI (R2, 0.86), and a light extinction coefficient (k) of 0.53 was estimated. Stalk density was estimated at 18 stalks m–2, with a maximum plant height of 3.6 m, and a rooting depth exceeding 2.0 m. When the crop parameters were incorporated into a biological model of Agricultural Land Management Alternatives with Numerical Assessment Criteria (ALMANAC) the model accurately simulated sugarcane yields across seven different soil types and multiple management scenarios of applied irrigation water, N and P fertilizer inputs and various planting and harvest dates. The mean simulation percent (%) errors ranged from –6.4% to 1.8%, while the calculated Fisher’s paired t test of 1.41 with 39 degrees of freedom, showed no significant differences (P ≥ 0.05) between measured and simulated yields. The ALMANAC model should be useful as a decision support tool for evaluating sugarcane management alternatives that maximize yields while optimizing water, N and P inputs.