Relationship between Verticillium dahliae inoculum and sunflower wilt in Argentina

Figures & data

Fig. 1 Effect of soil microsclerotia (MS) density of Verticillium dahliae on leaf mottle (LM) progress in two experiments in buried pots (Exp. 1 in the field: A and B; Exp. 2 in greenhouse: C, D, E and F) and two soil pasteurization treatments (pasteurized: (a– d); non-pasteurized: (e and f)). Microsclerotia densities: (●) 0, (○) 0.1, (▼) 1, (▽) 3, (▲) 4, (■) 5, (∆) 15, (□) 25 and (♦) 100 MS/g of soil. Leaf mottle variables: Incidence (number of plants with LM/number of total plants in percentage), severity (number of leaves with LM/number of total leaf assessed in diseased plants, in percentage) and the area under disease progress curve (AUDPC) in figure insets for incidence and severity. Bars indicate one area under diseases progress curve standard error.

Table 1. Regression models evaluation. The second-order Akaike Index Criterion (AICc) and linear regression analysis of observed vs predicted values between microsclerotia density of Verticillium dahliae in soil and sunflower leaf mottle (severity on grain filling stage and area under severity progress curve, AUDPC).

		Severity of leaf mottle on grain filling stage (R7)						AUDPC of disease severity
						Observed vs Predicted						Observed vs Predicted
Exp.^†	Regression model	n	k	AICc^#	∆AICc^##	ρ	ρc	n	k	AICc^#	∆AICc^##	ρ	ρc
1	Linear	7	2	2.9	0.5	0.83*	0.82	7	2	−2.4	0.5	0,83*	0,82
	Quadratic	7	3	10.1	7.7	0.87*	0.86	7	3	4.7	7.6	0,86*	0,85
	Sigmoid	7	3	10.1	7.6	0.86*	0.85	7	3	4.7	7.6	0,86*	0,84
	Power	7	2	3.8	1.4	0.95**	0.95	7	2	−1.6	1.2	0,94*	0,94
	Logarithm	7	2	3.1	0.6	0.86*	0.85	7	2	−2.4	0.5	0,61^NS	0,6
	Exponential	7	2	2.5	0.0	0.74*	0.74	7	2	−2.9	0.0	0,74^NS	0,73
2a	Linear	5	2	6.2	0	0.75^NS	0.72	5	2	0.5	0.0	0,71^NS	0,67
	Quadratic	5	3	26.5	20.3	0.83^NS	0.82	5	3	20.9	20.3	0,81^NS	0,79
	Sigmoid	5	3	27.0	20.8	0.91*	0.91	5	3	22.2	21.6	0,93*	0,93
	Power	5	2	8.5	2.3	0.99**	0.98	5	2	3.1	2.6	0,99***	0,99
	Logarithm	5	2	7.7	1.5	0.96*	0.96	5	2	2.5	2.0	0,98**	0,97
	Exponential	5	2	7.0	0.8	0.91*	0.91	5	2	1.6	1.0	0,93*	0,93
2b	Linear	5	2	7.1	0.1	0.75^NS	0.73	5	2	1.1	0.0	0,71^NS	0,67
	Quadratic	5	3	27.9	20.9	0.91*	0.9	5	3	21.9	20.8	0,9*	0,89
	Sigmoid	5	3	27.9	20.9	0.91*	0.9	5	3	21.9	20.8	0,89*	0,89
	Power	5	2	8.2	1.2	0.94*	0.94	5	2	2.2	1.1	0,93*	0,93
	Logarithm	5	2	7.7	0.6	0.88*	0.87	5	2	1.8	0.7	0,88*	0,88
	Exponential	5	2	7.1	0	0.85^NS	0.82	5	2	1.2	0.1	0,78^NS	0,78
3	Linear	18	2	0.3	0	0.67*	0.62
	Quadratic	18	3	3.5	3.2	0.78***	0.75
	Sigmoid	18	3	3.7	3.3	0.82***	0.8
	Power	18	2	0.5	0.2	0.76***	0.73
	Logarithm	18	2	0.5	0.2	0.73***	0.7
	Exponential	18	2	0.5	0.1	0.78***	0.77

^†Experiments in buried pots in the field (Experiment 1) or in greenhouse (Experiment 2) and two soil pasteurization treatments (pasteurized soil, Exp. 1 and 2a, or non-pasteurized soil, Exp. 2b). Experiment 3 with natural soilborne inoculum in the field.

NS: non-significant; *P-value = 0.05; ** P-value = 0.01; *** P-value = 0.001

^# AICc = −2log(RSS/n) + 2k +2k(k + 1)/(n-k-1); RSS = Residuals Sum Square; n = sample size; k = parameters number. Lower AICc value indicates better model fitting.

^##∆AICc = AICi-minAIC; AICi = AICc value for model; minAIC = minimum AICc value

∆AICc<2 = substantial support for the model; 3<∆AICc<7 = model has considerably less support; ∆AICc<10 = model very unlikely

ρ_c: Concordance correlation coefficient calculated as the product of the Pearson correlation coefficient (ρ) and the bias correction factor (Cb). Cb indicates changes in line height and slope of the observed vs predicted linear regression of each evaluated model. ρ_c~1indicates model low deviation from the concordance line (1:1) meaning high model fitting to the data.

-1≤-│ρ│≤ρ_c≤│ρ│≤1

Regression models equations, Exponential: LM = a*(1-exp(-b*ID)); Linear: LM = LM_o+a*ID; Logarithm: LM = if(ID>0, LM₀ + a*ln(abs(ID)), 0); Power: LM = a*ID^b; Quadratic: LM = LM₀ + a*ID+b*ID^2 and Sigmoid: LM = a/(1+ exp(-(ID-ID₀)/b)).

ID = inoculum density (microsclerotia/g of soil)

LM = leaf mottle

Fig. 2 Power regression model for relationship between soil microsclerotia (MS) densities of Verticillium dahliae and leaf mottle severity on R7 stage (early grain filling) or area under disease progress curve (severity) in two experiments in buried pots (Exp. 1 in the field: (a) and (b); Exp. 2 in greenhouse: (c) and (d)). Leaf mottle disease (LM) variables: Severity and the area under the disease progress curve (AUDPC) for severity. Bars indicate one standard error (n = 3 in Exp 1 and n = 2 in Exp 2). Dashed lines show LM in non-pasteurized soil.

Fig. 3 Power regression model for relationship between microsclerotia (MS) density of Verticillium dahliae in soil and leaf mottle severity in R7 stage (early grain filling). Symbol´s shape identifies field experiment location: triangle up, Balcarce Conventional Tillage; triangle upside down, Balcarce No Tillage; diamond, S. F. Bellocq; hexagonal, Coronel Suárez; circle, El Carretero and square, Pieres. Symbol´s color identifies hybrids: black, Paihuén; grey, DK3920 and white, PAN7009. The location of each symbol is the mean of three replications.