日光温室芹菜外观形态及干物质积累分配模拟模型

为实现日光温室芹菜外观形态与干物质积累分配预测。该研究依据芹菜(Apium graveolens L.)生长发育的光温反应特性,以‘尤文图斯’为试验品种,利用2年2茬分期播种试验观测数据,依据温室芹菜外观形态生长与关键气象因子(温度和辐射)的关系,以单株辐热积(Photo-ThermalIndex,PTI)为自变量构建了外观形态模拟模型;并建立了基于PTI的干物质分配模拟模型;结合叶面积指数模拟模块、光合作用和呼吸作用模拟模块,构建了干物质积累模拟模型;结合各器官各个发育阶段内的相对含水量,可计算鲜物质积累模拟模型。基于各子模块共同组成了日光温室芹菜外观形态及干物质积累分配模拟模型,确定了模型品种参数,利用独立试验数据对模型进行验证。结果表明,1)在外观形态模拟模型中,对根长、主茎茎粗、主茎茎长、株高、整枝和自然管理方式下叶面积指数(Leaf Area Index,LAI)形态指标均方根误差(Root Mean Square Error,RMSE)分别为2.46 cm、1.49 mm、6.72 cm、11.08 cm、0.74 m~2/m~2和0.77 m~2/m~2,归一化均方根误差(Normalized Root Mean Square Error,NRMSE)分别在16.63%～20.63%之间。2)在干物质分配模拟模型中,各器官的干物质分配指数NRMSE在8.24%～27.19%之间,RMSE在0.60%～7.01%之间。3)在干物质积累模拟模型中,不同器官(根、茎、叶、总茎、总叶、主茎、叶柄、整枝和自然管理方式下地上部)的干物质质量RMSE在3.85～85.80 g/m~2之间,NRMSE分别为14.21%～23.13%之间,说明干物质积累模拟模型对不同器官的干物质模拟均有较高的模拟效果。表明模型能够较准确模拟芹菜外观形态与干物质积累分配,系统化定量地表现出日光温室芹菜的生长动态过程。

Simulation model of external morphology and dry matter accumulation and distribution of celery in solar greenhouse

Abstract: A dynamic simulation was performed here to characterize the external morphology, accumulation, and distribution of dry matter in the celery (Apium graveolens L.) under a solar greenhouse. A two-year experiment was carried out in a greenhouse from 2018 to 2020 in the Agricultural Science and Technology Innovation Base, Wuqing District, Tianjin, China (east longitude 116.97 °, latitude 39.43 °, altitude 8 m). There were 2 or 3 transplanting dates for each stubble, including the early transplanting date (EP, about 15 days earlier than the local conventional planting date), medium transplanting date (MP, local conventional transplanting date that was transplanted in mid September), and the late planting (LP, about 15 days later than the local conventional transplanting date). A random block group design was adopted, where three replicates were set for each transplanting date. The variety of celery was selected as Juventus. Five development stages were also divided, namely, the transplanting date (T), outer leaf growth period (OLG), cardiac hypertrophy period (CH), wither period (W), and uprooting period (U). An external morphology model was constructed with the photo-thermal index (PTI) as an independent variable, according to the relationship between the growth dynamic of external morphology and key meteorological factors (temperature and radiation) of celery in a greenhouse. The PTI was also used to establish the dry and fresh matter distribution model. A module of dry matter accumulation in the celery was established under the amount of training using the double integral of leaf area index (LAI) and daily length in photosynthesis per unit leaf area, while considering the simulation modules of photosynthesis and respiration. A new model of fresh matter accumulation was established to combine the relative water content of each organ in each developmental stage. The whole growth model of celery was built in a greenhouse from each sub-module. The model parameters were then calibrated and determined. The rationality and accuracy of modules were validated using the statistical indicators. The results showed that: 1) In the external morphology model, the RMSE of simulated and measured morphological indicators of root length, main stem width, main stem length, plant height and LAI by pruning and natural were 2.46 cm, 1.49 mm, 6.72 cm, 11.08 cm, 0.74 m2/m2 and 0.77 m2/m2, respectively, and the NRMSE was between 16.63% and 20.63%. 2) In the model of dry and fresh matter distribution, the RMSE of the simulated and observed dry matter distribution index of each organ were between 8.24% and 27.19%, and the NRMSE was between 0.60% and 7.01%, respectively. 3) In the dry matter accumulation model, different dry matter of organs (including root, green stems, and leaves, total stem and leaf, stem, petioles, overground by pruning and natural) of dry matter simulated and measured values of RMSE were from 3.82 to 85.80 g/m2, while the NRMSE were from 14.21% to 23.13%. Furthermore, the dry matter accumulation model presented a high accuracy, when simulating the dry matter of different organs. Consequently, the model can be expected to accurately simulate the external morphology, accumulation, and distribution of dry matter, thereby systematically and quantitatively representing the growth dynamics of celery in a solar greenhouse. A growth process of celery was also elucidated to realize and quantify the dynamic monitoring of celery growth. Therefore, the finding can provide sound technical support to the intelligent production and management of leaf vegetables in a solar greenhouse.