Advanced epidemiology of wheat stem rust: disease occurrence and progression

Figures & data

Table 1. Standard regression models generated by GenStat to characterize stem rust progress in eight wheat cultivars with different resistance levels and sowing times at plot scale.

	2013–2014		2014–2015		2015–2016		2016–2017
Models	R^2	F prob.	R^2	F prob.	R^2	F prob.	R^2	F prob.
Exponential	0.71	<0.001	0.82	0.001	0.70	0.045	0.80	<0.001
Line + Exponential	0.84	<0.001	0.89	0.040	0.82	0.403	0.88	<0.001
Double exponential	0.93	0.002	0.88	nd^a	0.97	nd	1.00	nd
Critical exponential	0.93	<0.001	0.89	0.032	0.89	0.026	1.00	nd
Logistic	0.76	0.034	0.81	0.451	0.79	0.555	0.77	0.074
Generalized logistic	0.71	0.992	0.72	Nd	0.67	nd	0.77	0.852
Gompertz	0.74	0.077	0.82	0.360	0.81	0.429	0.80	0.030
Linear-by-linear	0.70	<0.001	0.82	0.001	0.68	0.110	0.80	<0.001
Linear-by-quadratic	0.86	<0.001	0.89	0.025	0.86	0.147	0.80	<0.001
Quadratic-by-quadratic	0.97	<0.001	1.00	Nd	0.99	nd	1.00	nd
Fourier	0.85	<0.001	0.90	0.019	0.91	0.007	0.74	0.175
Double fourier	0.99	nd	nd	Nd	0.41	nd	0.99	nd
Gaussian	0.91	<0.001	0.90	0.022	0.99	<0.001	0.32	1.00
Double Gaussian	0.91	nd	nd	Nd	nd	nd	nd	nd

^a nd = Not detected by statistical procedure.

Table 2. Average, standard deviation, and range values detected for predictors of stem rust progress in wheat cultivars with different resistance levels and sowing times at plot scale.

Descriptors	Average	Standard deviation	Range
Area under disease progress curve	92.00	151.00	0.00–631.70
Exponential parameter b	−561766.00	5426763.00	−52616133.00–42.00
Exponential parameter r	32.10	174.20	0.10–1578.00
Maximum disease severity	16.94	25.84	0.00–95.00

Figure 1. Wheat stem rust severity curves during 2013–2014 (up) and 2015–2016 (down) growing seasons in resistant (Baharan and Pishtaz), semi-resistant (Pishgam and Sirwan) and susceptible (Bahar, Chamran II, Parsi and Sivand) cultivars sown at different dates (x axis represents assessment times).

Table 3. Effects of cultivar resistance and sowing time on wheat stem rust progress curve elements examined by Kruskal-Wallis one-way ANOVA based on H-test.

					Exponential parameters
Resistance classes^a	Sowing time classes	Area under disease progress curve	Disease onset	Maximum disease severity	b	r
Resistant	Early-Optimum	34.30 (6)^b	51.20	34.15 (6)	46.10 (4)	59.30
	Late-Very late	37.27 (4)	44.36	45.18 (4)	52.45 (2)	48.18
Semi-resistant	Early-Optimum	35.71 (5)	54.33	35.96 (5)	46.21 (3)	55.54
	Late-Very late	49.08 (3)	46.50	48.04 (3)	44.00 (5)	51.75
Susceptible	Early-Optimum	55.22 (1)	49.32	48.74 (2)	35.24 (6)	55.54
	Late-Very late	54.75 (2)	42.58	58.33 (1)	60.98 (1)	51.75
Mean adjusted H		10.57	2.66	9.68	14.41	5.40
Ranking Chi P		0.046	0.753	0.054	0.013	0.369

^a Resistant cultivars: Baharan and Pishtaz; semi-resistant cultivars: Pishgam and Sirwan; susceptible cultivars: Bahar, Chamran II, Parsi and Sivand.

^b Values inside parentheses refer to the significant ranking (P ≤ 0.05).

Table 4. Spearman’s rank correlations between wheat stem rust progress curve elements determined for eight cultivars with different resistance levels and sowing times at plot scale.

Variables	AUDPC	b	r	MDS
Area under disease progress curve (AUDPC)	1.00
Exponential parameter b	−0.04	1.00
Exponential parameter r	−0.60^a	0.33	1.00
Maximum disease severity (MDS)	0.79	0.12	−0.41	1.00

^a Bold numbers refer to significance at 0.05 probability level.

Table 5. Principal component analysis of stem rust progress curve elements characterized for wheat cultivars with different resistance levels and sowing times at plot scale.

	Principal components
Variables	1	2
Area under disease progress curve	−0.56^a	−0.06
Disease onset time	0.54	−0.11
Exponential parameter b	0.20	0.50
Exponential parameter r	0.14	−0.86
Maximum disease severity	−0.58	−0.09
Eignvalues	2.34	1.00
Percentage variation explained	46.86	19.91
Cumulative variation	46.86	66.77

^a A bold number refers to significant loading when Chi-squared P ≤ 0.05.

Data availability statement

The data that support the findings of this study are openly available in figshare at https://doi.org/10.6084/m9.figshare.20487651.