Adaptation of SUBSTOR for controlled-environment potato production with elevated carbon dioxide.

IF 1.5 4区 农林科学 Q2 Agricultural and Biological Sciences
D H Fleisher, J Cavazzoni, G A Giacomelli, K C Ting
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引用次数: 8

Abstract

The SUBSTOR crop growth model was adapted for controlled-environment hydroponic production of potato (Solanum tuberosum L. cv. Norland) under elevated atmospheric carbon dioxide concentration. Adaptations included adjustment of input files to account for cultural differences between the field and controlled environments, calibration of genetic coefficients, and adjustment of crop parameters including radiation use efficiency. Source code modifications were also performed to account for the absorption of light reflected from the surface below the crop canopy, an increased leaf senescence rate, a carbon (mass) balance to the model, and to modify the response of crop growth rate to elevated atmospheric carbon dioxide concentration. Adaptations were primarily based on growth and phenological data obtained from growth chamber experiments at Rutgers University (New Brunswick, N.J.) and from the modeling literature. Modified-SUBSTOR predictions were compared with data from Kennedy Space Center's Biomass Production Chamber for verification. Results show that, with further development, modified-SUBSTOR will be a useful tool for analysis and optimization of potato growth in controlled environments.

SUBSTOR对高二氧化碳控制环境马铃薯生产的适应性。
SUBSTOR作物生长模型适用于马铃薯(Solanum tuberosum L. cv.)的控制环境水培生产。在大气二氧化碳浓度升高的情况下。适应性包括调整输入文件以考虑田间和受控环境之间的文化差异,校准遗传系数,以及调整作物参数(包括辐射利用效率)。还对源代码进行了修改,以考虑作物冠层以下表面反射光的吸收、叶片衰老率的增加、模型的碳(质量)平衡,并修改作物生长速率对大气二氧化碳浓度升高的响应。适应性主要基于罗格斯大学(New Brunswick, N.J.)生长室实验和建模文献中获得的生长和物候数据。修改后的substor预测与肯尼迪航天中心生物质生产室的数据进行了比较,以进行验证。结果表明,经过进一步开发,改良的substor将成为分析和优化受控环境下马铃薯生长的有用工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Transactions of the Asae
Transactions of the Asae 农林科学-农业工程
CiteScore
2.30
自引率
0.00%
发文量
0
审稿时长
12.0 months
期刊介绍: This peer-reviewed journal publishes research that advances the engineering of agricultural, food, and biological systems. Submissions must include original data, analysis or design, or synthesis of existing information; research information for the improvement of education, design, construction, or manufacturing practice; or significant and convincing evidence that confirms and strengthens the findings of others or that revises ideas or challenges accepted theory.
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