Environmental Engineering Reference
In-Depth Information
Table 5.6
Simulated supply response (tonnes per farm) to price changes for farm type 3303 in
Flevoland
Supply response (tonnes)
Maize
(silage)
Sugar
beet
Wheat
spring
Wheat
winter
Price (€/t)
Onions
Potatoes
Maize
(silage)
21
23
671
1,219
628
132
28
29
671
1,217
626
131
35
35
670
1,216
624
131
41
41
669
1,215
622
130
48
47
669
1,214
620
129
Onions
66
39
526
1,237
660
143
89
37
598
1,227
642
137
111
35
670
1,216
624
131
133
33
742
1,206
606
124
155
31
814
1,195
588
118
Potatoes
45
41
684
1,055
672
147
60
38
677
1,135
648
139
75
35
670
1,216
624
131
89
33
663
1,297
600
122
104
30
655
1,376
585
113
Sugar beet
27
36
673
1,222
585
134
36
36
673
1,222
585
134
46
35
670
1,216
624
131
55
33
662
1,201
724
122
64
30
655
1,187
824
113
Wheat spring
86
35
670
1,216
624
131
115
35
670
1,216
624
131
144
35
670
1,216
624
131
173
35
670
1,216
624
119
202
33
662
1,201
599
126
Wheat winter
94
38
677
1,231
649
111
125
38
677
1,231
649
111
156
35
670
1,216
624
131
187
32
661
1,199
594
140
218
28
651
1,178
585
148
Conclusions
This chapter presented a detailed description of the bio-economic farm model
(FSSIM), especially its specifications, structure, model linking and component
integration. The original contributions of FSSIM to bio-economic farm modelling are
the integrative approach, the modular setup and the generic features. The integrative
approach of FSSIM makes the complex relationship between biological processes
and economic decisions more transparent and allows a correct integration of technical
economic and environmental issues, enabling the simulation of the different type of
policies. The multidisciplinary framework facilitates synthesis of scientific knowledge
in the domain of agriculture and its environment. The generic features allow the
