Management Influence on Income Risk in an Apple Production System on Swiss Fruit Farms

Figures & data

TABLE 1. Farm-structure parameters of the 12 fruit farms under study, based on the year 2000

Farm-structure parameters	Mean	Standard deviation	Minimum	Maximum
Structure of labor force
Age of farm manager (years)	43.9	10.1	28.0	66.0
Experience as farm manager (years)	18.4	11.5	4.0	48.0
Permanent labours per farm (N)	2.0	0.7	1.0	3.0
Seasonal workers per farm (N)	7.6	7.7	1.0	28.0
Structure of farmland
Altitude (m above sea level)	467.9	75.6	390.0	610.0
Total area per farm (ha)	16.8	5.3	8.2	31.0
Area per farm with fruit orchards (ha)	9.1	4.7	2.3	18.0
Structure of apple orchards
Area per farm with apple orchards (ha)	7.2	3.9	1.7	14.4
Apple cultivar-mix index ^a , ^b	1.03	0.07	0.93	1.18
Number of apple orchards ^a	9.27	4.09	4.00	18.00
Area of an individual apple orchard (ha)^a	0.4	0.2	0.1	1.4
Density of trees (trees/ha) ^a	2340	602	1502	3984
Age of apple orchards (years since planting^a)	8	3.1	4	15
^aOnly apple orchards in the productive phase (4–15 years old).
^bA cultivar mix index > 1.0 shows that a farm has planted cultivars with higher potential receipts than the average in Switzerland. The cultivar mix index considers the planted acreage of the eight most common cultivars in Switzerland weighted by the average prices and yields (1997–2000) without clearance.

TABLE 2. Income variables and calculation scheme of “Net income per labor hour (V ₀).”

Type of income variable				Calculation scheme
Vd	Vi	Vi,j	Vi,j,k
		V 1,1		+ Total receipts per hectare=
			V 1,1,1	(Yield per hectare*
			V 1,1,2	Total receipts per kilogram)
		V 1,2		− Nonlabor production costs per hectare =
			V 1,2,1	+ Depreciation on orchard per hectare
			V 1,2,2	+ Total machinery costs per hectare
			V 1,2,3	+ Pesticide costs per hectare
			V 1,2,4	+ Fertilizer costs per hectare
			V 1,2,5	+ Deductions per hectare
			V 1,2,6	+ All other production costs per hectare
	V 1			= Net income per hectare
	V 2			/ Total labor hours per hectare
		V 2,1		+ Preharvest labor hours per hectare
		V 2,2		+ Harvest labor hours per hectare
V 0				= Net income per labor hour
Vd = dependent variable; Vi = independent variables; Vi,j = first indicators of independent variables; Vi,j,k = second indicators of independent variables.

TABLE 3. Statistical moments for “Net income per labor hour (V ₀)” of 12 fruit farms with homogeneous boundary conditions based on annual data sets of 445 individual apple orchards, Switzerland, 1997–2000

Farm No.	N	Mean (CHF/h)	Standard deviation(CHF/h)	Skewness	K-S-Test ^a (P)	Minimum (CHF/h)	Maximum (CHF/h)
1	18	26.3	14.4	0.4	0.20*	6.0	51.3
2	33	19.2	15.8	0.2	0.20*	−15.0	56.1
3	71	8.2	21.7	0.1	0.20*	−52.7	90.4
4	39	0.1	28.0	−0.8	0.20*	−75.8	55.9
5	26	−3.8	28.8	−1.0	0.20*	−87.5	40.2
6	23	−5.8	35.1	−0.2	0.20*	−62.5	54.6
7	32	−7.2	21.1	−1.6	0.01	−68.1	20.4
8	56	−8.9	33.3	−1.4	0.01	−125.9	48.4
9	52	−15.7	22.1	−0.1	0.20*	−81.9	42.9
10	17	−18.5	34.7	−0.4	0.20*	−85.0	40.0
11	45	−19.1	24.0	−1.8	0.01	−99.2	17.6
12	33	−38.0	56.1	−1.3	0.02	−204.4	25.2
Average	37	−5.3	27.9	−0.6	0.01	−79.3	45.2
^aKolmogorov-Smirnov test of normal distribution; *normal distribution can be assumed if P > 0.05.
N = Number of annual data sets of productive apple orchards (4–15 years old) analyzed per farm.
CHF = Swiss Francs, exchange rate during the observed period: 1.0 US$ = 1.5 CHF.
Farms are sorted by the mean value.

FIGURE 1. Linear correlation of mean and standard deviation of “Net income per labor hour (V ₀)” of apple production on 12 fruit farms, Switzerland, 1997–2000. N = 12; r is the Pearson correlation coefficient; P the significance level (two-tailed); 95% confidence interval marked by curved lines; farm numbers sorted by the mean value.

FIGURE 2. Linear correlation of mean and skewness of “Net income per labor hour (V ₀)” of apple production on 12 fruit farms, Switzerland, 1997–2000. N = 12; r is the Pearson correlation coefficient; P the significance level (two-tailed); 95% confidence interval marked by curved lines; farm numbers sorted by the mean value.

TABLE 4. Linear correlation and statistical moments of income variables of apple production on 12 fruit farms with homogeneous boundary conditions, Switzerland, 1997–2000

Income variables	r	Mean	Standard deviation	Skewness	Farms with normal distribution ^a (%)
Dependent variable
V 0 Net income per labor hour (CHF/h)		−5.27	27.92	−0.6	67
Independent variables
V 1 Net income per hectare (CHF/ha)	0.93***	1341.40	7979.01	0.7	92
V 2 Total labor hours per hectare (h/ha)	0.73**	405.54	167.24	0.7	67
First indicators of independent variables
V 1,1 Total receipts per hectare (CHF/ha)	0.91***	20,195.09	9299.50	0.5	92
V 1,2 Nonlabor production costs per hectare (CHF/ha)	−0.06	18,853.68	2883.34	0.4	75
V 2,1 Preharvest labor hours per hectare (h/ha)	0.72**	157.20	71.89	0.9	42
V 2,2 Harvest labor hours per hectare (h/ha)	0.65*	248.34	124.90	0.5	83
Second indicators of independent variables
V 1,1,1 Yield per hectare (kg/ha)	0.96***	31,449.79	14,900.89	0.4	83
V 1,1,2 Total receipts per kilogram (CHF/kg)	−0.34	0.74	0.34	1.0	67
V 1,2,1 Depreciation on orchards per hectare (CHF/ha)	0.52	5015.76	411.73	0.3	8
V 1,2,2 Total machinery costs per hectare (CHF/ha)	−0.30	4922.10	1603.61	0.5	75
V 1,2,3 Pesticide costs per hectare (CHF/ha)	−0.23	1713.44	355.69	0.2	58
V 1,2,4 Fertilizer costs per hectare (CHF/ha)	0.02	439.96	161.61	0.3	58
V 1,2,5 Deductions per hectare (CHF/ha)	0.78**	2192.06	1469.78	0.8	50
V 1,2,6 All other production costs per hectare (CHF/ha)	−0.26	4570.36	842.82	0.3	25
V 2,2,1 Kilogram of apples harvested per labor hour (kg/h)	0.56	137.51	57.51	1.3	58
r is the Pearson correlation coefficient for the correlation of income variables with the dependent variable “Net income per labor hour (V 0).”
^aNormal distribution was tested by Kolmogorov-Smirnov test P > 0.05. N = 12, the sample includes 445 annual data sets.

TABLE 5. Statistical moments for “Total receipts per hectare (V _1.1)” of 12 fruit farms based on annual data sets of 445 individual apple orchards, Switzerland, 1997–2000

Farm No.	N	Mean (CHF/ha)	Standard deviation (CHF/ha)	CV (%)	Skewness	K-S-Test ^a (P)
1	18	34,672	8482	24	0.2	0.20*
2	33	24,893	8280	33	0.3	0.20*
3	71	25,966	11,260	43	0.7	0.09*
4	39	23,195	11,831	51	0.9	0.20*
5	26	20,681	10,225	49	1.3	0.20*
6	23	15,476	10,886	70	0.8	0.02
7	32	17,930	8033	45	0.4	0.20*
8	56	17,902	8462	47	0.3	0.20*
9	52	17,553	9527	54	0.4	0.05*
10	17	15,464	8903	58	0.7	0.20*
11	45	15,603	6090	39	−0.3	0.20*
12	33	13,007	9614	74	0.8	0.20*
Average (N=12)	37	20,195	9299	46	0.5
^aKolmogorov-Smirnov test of normal distribution; *normal distribution can be assumed if P > 0.05.
N = Number of annual data sets of productive apple orchards (4–15 years old) analyzed per farm.
CHF = Swiss Francs, exchange rate during the observed period: 1.0 US$ = 1.5 CHF.

TABLE 6. Statistical moments for “Preharvest labor hours per hectare (V _2.1)” of 12 fruit farms based on annual data sets of 445 individual apple orchards, Switzerland, 1997–2000

Farm No.	N	Mean (h/ha)	Standard deviation (h/ha)	CV (%)	Skewness	K-S-Test ^a (P)
1	18	249	80	32	1.1	0.16*
2	33	181	93	51	0.6	0.19*
3	71	192	81	42	1.0	0.07*
4	39	162	85	52	0.3	0.20*
5	26	152	61	40	0.3	0.20*
6	23	100	59	60	0.6	0.00
7	32	204	115	57	1.2	0.20*
8	56	128	63	49	0.7	0.01
9	52	202	98	49	1.4	0.01
10	17	92	37	41	2.2	0.20*
11	45	140	39	28	0.7	0.01
12	33	85	51	60	0.2	0.20*
Average (N = 12)	37	157	72	46	0.9
^aKolmogorov-Smirnov test of normal distribution; *normal distribution can be assumed if P > 0.05.
N = Number of annual data sets of productive apple orchards (4–15 years old) analyzed per farm.
CHF = Swiss Francs, exchange rate during the observed period: 1.0 US$ = 1.5 CHF.