中国农业气象 ›› 2021, Vol. 42 ›› Issue (01): 34-43.doi: 10.3969/j.issn.1000-6362.2021.01.004

• 农业生物气象栏目 • 上一篇    下一篇

基于光温效应的大白菜生理特性及营养品质动态模拟效果

蔡淑芳,吴宝意,雷锦桂   

  1. 福建省农业科学院数字农业研究所,福州 350003
  • 收稿日期:2020-09-09 出版日期:2021-01-20 发布日期:2021-01-17
  • 通讯作者: 雷锦桂,研究员,研究方向为数字农业,E-mail: 71906244@qq.com E-mail:71906244@qq.com
  • 作者简介:蔡淑芳,E-mail: csf2019@qq.com
  • 基金资助:
    福建省自然科学基金项目(2017J01045);福建省农业科学院项目(A2018-4;YDXM2019006;STIT2017-2-12)

Dynamic Simulation Effect of Physiological Characteristics and Nutritional Quality of Chinese Cabbage Based on Light and Temperature Function

CAI Shu-fang, WU Bao-yi, LEI Jin-gui   

  1. Institute of Digital Agriculture, FAAS, Fuzhou 350003, China
  • Received:2020-09-09 Online:2021-01-20 Published:2021-01-17

摘要: 在温室环境下,研究大白菜生理特性及营养品质与气温、光合有效辐射的动态模拟关系,以期为温室大白菜生长管理与环境优化调控提供参考。2020年6−9月,以“新早熟5号”大白菜为试材开展前后三期实验,自动采集温室气温和光合有效辐射数据,每3d进行1次大白菜生理特性及营养品质测定。计算实验期间各处理大白菜光温效应LTF以及辐热积TEP、积温GDD值,利用一期实验数据建立生理特性及营养品质动态模拟模型;利用独立两期实验数据开展模型检验,比较动态模拟模型的预测效果。检验结果表明,对大白菜各项生理特性及营养品质的模拟,以LTF模型效果较佳,R2>0.956,RMSE<46.752,RE<11.99%,LTF模型拟合度和模拟精度优于GDD和TEP模型。其中,大白菜叶片可溶性糖、可溶性蛋白和维生素C含量呈单峰曲线变化规律,其LTF模型可用Extreme函数表达;硝酸盐含量呈“N”字形变化规律,其LTF模型可用Poly5函数表达;纤维素、根系活力、叶绿素(a、b、a+b)和类胡萝卜素呈“S”型变化规律,纤维素LTF模型可用Gompertz函数表达,其余指标LTF模型可用Logistic函数表达。LTF法能根据气温和光合有效辐射数据较精准地预测温室大白菜生理特性及营养品质,为建立更具普适性的温室大白菜生长模型提供参考。

关键词: 温室, 大白菜, 生理特性, 营养品质, 光温效应

Abstract: Studying the relationship among ambient temperature, photosynthetically active radiation and physiological characteristics, nutritional quality of Chinese cabbage in greenhouse can provide reference for growth management and environmental optimization of facility cultivating Chinese cabbage. From June to September 2020, the "New Zaoshu No.5" Chinese cabbage was used as the test material for carrying out 3 experiments. Ambient temperature and photosynthetically active radiation data in greenhouse were collected automatically by automatic acquisition system, and physiological characteristics, nutritional quality of Chinese cabbage were measured once every 3 days. Light and temperature function, thermal effectiveness and photosynthetically active radiation, growing degree days of experiment days were calculated. One period experiment data was used to establish dynamic simulation models of physiological characteristics and nutritional quality. The prediction effect of the dynamic simulation models was verified and compared with the data of another 2 period experiments. The results showed that the average daily ambient temperature during the experiments was 33.06−38.31℃, and the daily photosynthetically active radiation was 3.84−19.37mol·m−2·d−1. The simulation effect of LTF models on physiological characteristics and nutritional quality of Chinese cabbage was good, which R2 was > 0.956, RMSE was < 46.752 and RE was < 11.99%. The degree of fit and simulation accuracy of LTF models were better than that of GDD and TEP models. Among them, soluble sugar, soluble protein and vitamin C showed the change of single peak curve, which LTF model could be expressed as extreme function. Nitrate showed the change of N-shaped curve, which LTF model could be expressed as Poly5 function. Cellulose, root activity, chlorophyll (a, b, a+b) and carotenoids showed the change of S-type curve, among them, Cellulose LTF model could be expressed as Gompertz function, and the other indexes LTF model could be expressed as Logistic function. LTF method can accurately predict physiological characteristics and nutritional quality of Chinese cabbage in greenhouse based on ambient temperature and photosynthetically active radiation. LTF method can provide a reference for the establishment of a more general growth model of Chinese cabbage in greenhouse.

Key words: Greenhouse, Chinese cabbage, Physiological characteristics, Nutritional quality, Light and temperature function