The Applicability of Mechanism Phenology Models to Simulating Apple Flowering Date in Shaanxi Province

Wu Dingrong; Huo Zhiguo; Wang Peijuan; Wang Jinghong; Jiang Huifei; Bai Qinfeng; Yang Jianying

doi:10.11898/1001-7313.20190504

Vol.30, NO.5, 2019

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Article Navigation > Journal of Applied Meteorological Science > 2019 > 30(5): 555-564

Wu Dingrong, Huo Zhiguo, Wang Peijuan, et al. The applicability of mechanism phenology models to simulating apple flowering date in Shaanxi Province. J Appl Meteor Sci, 2019, 30(5): 555-564. DOI: 10.11898/1001-7313.20190504.

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Wu Dingrong, Huo Zhiguo, Wang Peijuan, et al. The applicability of mechanism phenology models to simulating apple flowering date in Shaanxi Province. J Appl Meteor Sci, 2019, 30(5): 555-564. DOI: 10.11898/1001-7313.20190504.

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The Applicability of Mechanism Phenology Models to Simulating Apple Flowering Date in Shaanxi Province

DOI: 10.11898/1001-7313.20190504

1.
Chinese Academy of Meteorological Sciences, Beijing 100081
2.
Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science & Technology, Nanjing 210044
3.
Shaanxi Meteorological Service Observatory for Economical Crop, Xi'an 710015
4.
College of Resource and Environment Sciences, China Agriculture University, Beijing 100193

Received Date: 2019-05-10
Rev Recd Date: 2019-07-24
Publish Date: 2019-09-30

Abstract

Abstract

China's apple growing area and production rank first in the world, and thus apple is one of important economical crops in China. Meteorological disaster occurring in apple critical phenology stage is one of the main disasters impacting yield and quality, especially in the dominant planting provinces such as Shaanxi. Accurate forecasting on flowering date in Shaanxi can provide scientific support for taking applicable defensive management and improving the ability to resist meteorological disasters, and therefore benefit to apple yield and quality. Taking apple flowering stage as an example, the applicability of 4 typical phenology models is evaluated, including Sequential Model (SM), Parallel Model (PM), Deepening Rest Model (DRM), and Thermal Time Model (TTM). There are 4 apple planting divisions in Shaanxi Province. In each division, there are two phenology observation sites. Internal validation and cross validation (Leave One Out Cross Validation) of 4 models are done using sites with longer observations, while shorter record sites are used to evaluate the effect of model extrapolation application. In 4 divisions, 4 sites performing internal validation and cross validation are Xunyi, Luochuan, Liquan and Baishui, respectively, while four sites to conduct extrapolation application are Changwu, Baota, Fengxiang and Tongchuan, respectively. Model performance is assessed according to the root mean square error (RMSE) of modelled flowering date. Internal validation results show that optimal models are different in different sites and generally TTM and SM give similar accuracy (3.30 d). Cross validation also verifies and there is no particularly prominent model. The average RMSE for all four models is 4.52 d. TTM is then extrapolatively applied to other sites with two methods (extrapolation based on values in a single site, and extrapolation based on average values of 4 sites). The accuracy of both methods is higher than that of similar studies abroad (10.0 d), while the accuracy of extrapolation based on values in a single site (5.90 d) is higher than that of extrapolation based on average values of 4 sites (7.21 d). Considering the complexity and simulation accuracy, TTM is recommended to be used to simulate the flowering period in each apple planting division in Shaanxi Province.
- apple flowering date;
- mechanical model;
- applicability evaluation;
- thermal time model

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References(42)

Figures and Tables

Fig. 1 The target area and location of sites(regional division of apple planting from Reference [32])

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Fig. 2 Observed flowering date at 4 parameter-calibration sites and values given by 4 models in internal validation

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Fig. 3 Observed flowering date at 4 parameter-calibration sites and values given by 4 models in cross validation

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图 4 TTM参数在4个外推站应用的模拟结果

(a)单站外推，(b)参数求平均值后外推至4个站

Fig. 4 Simulated flowering date applied by TTM at 4 parameter-validation sites

(a)based on values of a single site, (b)based on average values of 4 sites

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Table 1 Years and number of observations at each site

所属果区	站名	观测年份	观测年数
关中果区	礼泉	1973—1974，1976，1980，1982—1983，1989，1992，1998，2000—2001，2003—2004，2007—2014	21
关中果区	凤翔	2001—2009	9
渭北西部果区	旬邑	1994—2014	21
渭北西部果区	长武	1995—2002	8
渭北东部果区	白水	2001—2009，2011—2014	13
渭北东部果区	铜川	2001—2005，2007—2009	8
延安果区	洛川	1998—2014	17
延安果区	宝塔	2001—2003，2005，2007，2009	6

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Table 2 Parametric optimization spaces of SM, PM and DRM

参数	最小值	最大值
T_b/℃	-20	-5
T_opt/℃	2.0	6.9
T_max/℃	7	11
R_c	3	20
a	0.1	3.0
b	5	15
c	-5	10
R_f	10	40

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Table 3 Internal validation results of 4 models at 4 parameter-calibration sites

站点	统计量	SM	PM	DRM	TTM
旬邑	均方根误差/d	4.02	4.43	4.75	3.63
旬邑	R²	0.438^***	0.446^***	0.402^*	0.412^**
洛川	均方根误差/d	2.8	3.48	2.78	3.07
洛川	R²	0.618^***	0.474^**	0.611^***	0.536^***
礼泉	均方根误差/d	2.86	4.27	3.17	2.88
礼泉	R²	0.834^***	0.698^***	0.802^***	0.836^***
白水	均方根误差/d	3.5	4.63	3.78	3.67
白水	R²	0.638^***	0.369^*	0.556^***	0.531^***
注：，和**分别表示达到0.05, 0.01和0.001显著性水平。

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Table 4 Cross validation results of 4 models at 4 parameter-calibration sites

站名	统计量	SM	PM	DRM	TTM
旬邑	均方根误差/d	5.36	4.75	6.65	6.41
旬邑	R²	0.273^***	0.335^**	0.247^*	0.193^*
洛川	均方根误差/d	4.2	4.09	3.48	3.79
洛川	R²	0.241^*	0.259^*	0.406^**	0.365^**
礼泉	均方根误差/d	3.82	3.73	3.74	3.53
礼泉	R²	0.718^***	0.728^***	0.735^***	0.761^***
白水	均方根误差/d	6.34	5.24	4.21	5.19
白水	R²	0.32^*	0.43^*	0.48^**	0.32^*
注：，和**分别表示达到0.05, 0.01和0.001显著性水平。

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Table 5 Parameter values, thermal threshold(F^*) and simulation accuracy in internal validation of TTM at 4 parameter-calibration sites

站点	下限气温/℃	静止期始期	热驱动阈值F^*	内部验证准确率/%
旬邑	2.5	03-11	206.0	61.9
洛川	2.0	02-24	317.5	94.1
礼泉	2.9	02-13	287.7	81.0
白水	2.7	03-09	218.3	69.2

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Table 6 Root mean square errors of simulated flowering date applied by TTM at 4 parameter-validation sites(unit:d)

站点	单站外推	求平均后外推
长武	6.24	9.80
宝塔	5.08	5.69
凤翔	5.34	4.51
铜川	5.34	7.62

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