Scientia Agricultura Sinica ›› 2023, Vol. 56 ›› Issue (6): 1061-1073.doi: 10.3864/j.issn.0578-1752.2023.06.004

• TILLAGE & CULTIVATION·PHYSIOLOGY & BIOCHEMISTRY·AGRICULTURE INFORMATION TECHNOLOGY • Previous Articles     Next Articles

Effects of Powdery Mildew on Photosynthetic Characteristics and Quantitative Simulation of Disease Severity in Winter Wheat

CHANG ChunYi(), CAO Yuan, GHULAM Mustafa, LIU HongYan, ZHANG Yu, TANG Liang, LIU Bing, ZHU Yan, YAO Xia, CAO WeiXing, LIU LeiLei()   

  1. College of Agriculture, Nanjing Agricultural University/National Engineering and Technology Center for Information Agriculture/ Engineering Research Center of Smart Agriculture, Ministry of Education/Key Laboratory for Crop System Analysis and Decision Making, Ministry of Agriculture and Rural Affairs/Jiangsu Key Laboratory for Information Agriculture/Jiangsu Collaborative Innovation Center for Modern Crop Production, Nanjing 210095
  • Received:2022-06-28 Accepted:2022-08-02 Online:2023-03-16 Published:2023-03-23

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Abstract:

【Objective】 The objective of this paper was to clearly demonstrate the effects of powdery mildew on photosynthetic characteristics of winter wheat and to establish a model for simulating effects of powdery mildew stress on wheat photosynthetic productivity. 【Method】 To clarify the effects of powdery mildew on wheat photosynthetic characteristics, the powdery mildew experiments of wheat were conducted under two initial inoculation degrees of wheat powdery mildew at jointing and booting stages. On this basis, a prediction model of wheat powdery mildew severity was established to quantify the physiological effects of powdery mildew on wheat. And then, based on the single leaf net photosynthetic rate (Pn) and leaf area index (LAI), the wheat powdery mildew severity prediction model was coupled with the crop growth model (WheatGrow). 【Result】 Under the stress of powdery mildew, Pn and LAI showed a decreasing trend. Compared with the control (CK), the averaged Pn and LAI decreased by 18.81% and 23.41%, respectively. Moreover, the effects of stages of powdery mildew on Pn and LAI were more serious than the initial inoculation degrees. In general, the development of wheat powdery mildew in the field had obvious gentle period, exponential outbreak period and stable period, and the temporal dynamic characteristics of wheat powdery mildew epidemic under each treatment accorded with Logistic function. Therefore, based on the Logistic fitting results, the wheat powdery mildew disease stress factor was established to reflect the stress effects of powdery mildew on wheat physiological indexes. In addition, based on the photosynthesis productivity sub-model of WheatGrow and the effect factor of wheat powdery mildew severity, the algorithms to simulate the effects of powdery mildew on Pn and LAI were established, and then the improved WheatGrow model was estimated by using the powdery mildew experimental datasets in independent years. 【Conclusion】 The integrated model with powdery mildew stress algorithms was better than the original WheatGrow model in predicting Pn, LAI, aboveground biomass and yield under powdery mildew stress condition, with the simulation accuracy improved by 53.29%, 43.61%, 60.09% and 67.57%, respectively. The improved model could provide the digital tool and technical support for prediction of wheat powdery mildew severity and the quantitative evaluation of wheat yield loss.

Key words: winter wheat, powdery mildew, photosynthetic characteristics, prediction model of disease severity, WheatGrow model, coupling

Fig. 1

Leaf phenotype and hyphal development in wheat leaves after inoculation with powdery mildew"

Fig. 2

Effects of powdery mildew on the net photosynthesis rate (Pn) of different leaf positions in wheat A-C: Inoculation of powdery mildew at jointing stage; D-F: Inoculation of powdery mildew at booting stage; A and D: The first leaf from the top; B and E: The second leaf from the top; C and F: The third leaf from the top. Error bars represent the standard deviation of mean"

Fig. 3

Effects of powdery mildew on the leaf area index (LAI) of wheat A: Inoculation of powdery mildew at jointing stage; B: Inoculation of powdery mildew at booting stage. Error bars represent the standard deviation of mean"

Fig. 4

Dynamic changes of powdery mildew severity with growth length day in different leaf positions of wheat A and B: Light and high inoculation at jointing stage; C and D: Light and high inoculation at booting stage; Error bars represent the standard deviation of mean"

Fig. 5

Dynamic prediction of different varieties wheat powdery mildew incidence by disease prediction model A, B, C and D represent experiment 2, 3, 4 and 5, respectively"

Table 1

Statistical indices in the validation of wheat powdery mildew severity prediction model"

试验 Experiment 试验品种 Experiment variety RMSE NRMSE (%) R2
试验2 Experiment 2 扬辐麦4号 Yangfumai4 0.057 16.60 0.99
生选6号 Shengxuan6 0.044 17.40 0.98
试验3 Experiment 3 南农0686 Nannong0686 0.056 21.25 0.97
试验4 Experiment 4 川育20 Chuanyu20 0.075 19.70 0.94
川农26 Chuannong26 0.089 18.60 0.86
川育20 Chuanyu20 0.062 15.60 0.98
试验5 Experiment 5 石新733 Shixin733 0.041 19.63 0.96
石新828 Shixin828 0.036 27.74 0.94
平均 Average 0.058 19.57 0.95

Fig. 6

Relationship between the disease severity of powdery mildew and relative Pn (A) and relative LAI (B) of wheat S1 and S2 indicate the treatment at jointing stage and booting stage"

Fig. 7

Comparison of simulated and observed Pn (A and B), LAI (C and D), aboveground biomass (E and F) and yield (G and H) with original and improved WheatGrow model"

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