中国农业气象 ›› 2016, Vol. 37 ›› Issue (01): 59-67.doi: 10.3969/j.issn.1000-6362.2016.01.008

• 论文 • 上一篇    下一篇

基于温光效应的小白菜营养品质模拟模型研究

谭 文,杨再强,李 军   

  1. 1. 南京信息工程大学气象灾害预报预警与评估协同创新中心,南京210044;2. 上海市气候中心,上海200030
  • 收稿日期:2015-06-08 出版日期:2016-02-20 发布日期:2016-02-24
  • 作者简介:谭文(1990-),女,硕士生,主要从事设施作物模拟研究。E-mail:tanwen603@163.com
  • 基金资助:

    “十二五”国家科技支撑计划项目(2014BAD10B07);国家公益性行业(气象)科研专项(GYHY201506001);江苏省科技计划(社会发展)(BE2015693)

Simulation of Nutrient Quality of Pakchoi Based on Temperature-light Function

TAN Wen,YANG Zai-qiang,LI Jun   

  1. 1.Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science & Technology, Nanjing 210044, China; 2.Shanghai Climate Center, Shanghai 200030
  • Received:2015-06-08 Online:2016-02-20 Published:2016-02-24

摘要:

为了建立小白菜营养品质模型,本研究以小白菜品种“四月慢”为试材设计分期播种试验,测定不同温光条件下小白菜不同时期维生素C、纤维素、可溶性糖以及可溶性蛋白含量等营养品质指标,建立基于温光效应 (Light and temperature function,LTF)的小白菜营养品质数学模型,并利用独立试验资料对模型进行检验。结果表明:本模型对小白菜的维生素C、纤维素、可溶性糖以及可溶性蛋白含量的预测结果回归估计标准误差(RMSE)比辐热积法(Thermal effectiveness and photosynthetically active radiation,TEP)、积温法(Growing degree days,GDD)显著降低,与辐热积法相比,各指标的RMSE分别降低81.14%、77.46%、77.23%、75.53%,与积温法相比则分别降低77.15%、78.77%、79.90%、21.17%,表明模型的预测精度更高。本模型实测值与模拟值间的相关系数(r)均大于0.98,优于辐热积法和积温法的模拟结果,表明模拟值与实测值之间符合度较高。与传统的辐热积法和积温法相比,温光效应法显著提高了小白菜营养品质预测精度,可为耐弱光的温室作物营养品质模拟提供参考。

关键词: 小白菜, 温室, 温光效应, 营养品质, 模拟模型

Abstract:

To establish the simulation model of the nutrient quality of pakchoi (Brassica chinensis), the ‘Siyueman’ was used as test strains from March 2014 to January 2015, including five sowing times. By measuring internal quality index: vitamin C, cellulose, soluble sugar and soluble protein content under different temperature and light conditions, the mathematical model of pakchoi internal quality based on light and temperature function (LTF) was established and validated by independent experimental data. The results showed that comparing with product of thermal effectiveness and photosynthetically active radiation (TEP) and growing degree days (GDD), the root mean squared error (RMSE) of prediction values on pakchoi vitamin C, cellulose, soluble sugar and soluble protein content decreased significantly. The RMSE values decreased by 81.14%, 77.46%, 77.23%, 75.53% than that of the TEP method, and 77.15%, 78.77%, 79.90%, 21.17% than that of the GDD method respectively, which indicated the prediction accuracy of the model was higher. The correlation coefficient (r) between measured data and model prediction value was more than 0.98, higher than that of RMSE method and GDD method, which indicated the simulated values were closer to measured values. This prediction model significantly improved the prediction accuracy of pakchoi, which provided a reference for crop quality simulation with resistance to weak light in greenhouse.

Key words: Pakchoi, Greenhouse, Temperature-light function, Nutrient quality, Simulation model