The Impact of Crop Mix on Decreasing Soil Price and Soil Degradation: A Case Study of Selected Regions in Czechia (2002–2019)
Abstract
:1. Introduction
Objectives
- Determine the structure of 10 of the most widespread crops according to VTS for regions where the OLP has decreased.
- Identify differences between the VTS crop share and real shares of crops in the regions where the OLP has decreased and to determine if these differences are statistically significant (at level α = 0.05).
2. Materials and Methods
2.1. Data
2.2. Methods
- r = average proportion of crop (i) in all VTS, r∈ (0, 100).
- k = crops in individual VTS, k∈ (1, 11).
- n = valuation type structure (VTS), n (1, 40).
- x = area of VTS depending on areas included in ESEU.
- X2 = Chi-square value.
- Xi = Observed crop share in each category.
- Epi = Expected crop share in each category.
- = sample proportion.
- = tested hypothesis proportion.
- n = sample size.
- = Average annual chain index.
- = Share of individual crop (i) at total area in given year.
- m = number of observed years.
- MSl = the percentage share of total area l and there are m crops in the regions.
- The resulting numerical value can be as high as 10,000 (indicating a high concentration and little diversity) or as low as share would have an HHI of 100.
3. Results
4. Discussion
5. Conclusions and Recommendations
- Crop rotation should not be limited to the main three crops: winter barley—winter rapeseed—winter wheat.
- As part of crop rotation, consider the negative impact of the overlapping share of wheat and maize, and the declining development of sugar beet and perennial fodder crops.
- Encourage growing of perennial fodder crops as part of greening support. Greening could also help the perennial fodder crops cultivation for seeds as a subject of Czech foreign trade.
- The greening part of SAPS requires that the farmers with areas higher than 30 hectares grow at least 3 different crops. However, it would be suitable to monitor the variety representation as the mix of corn, wheat, and rapeseed (as 3 common crops) is not appropriate.
- There is a lack of farm manure in the soil. The remittance of the SAPS payment should be partially linked to the livestock unit per hectare.
Author Contributions
Funding
Conflicts of Interest
References
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ESEU (BPEJ) Code | Digit Order | Scale | |
---|---|---|---|
X.xx.xx | 1. | Climatic Region Code | 0–9 |
x.XX.xx | 2. and 3. | Code of main pedelogic unit | 01–78 |
x.xx.Xx | 4. | Code of slope and exposure | 0–9 |
x.xx.xX | 5. | Associated code of stoniness and soil depth | 0–9 |
Region | HRRE Change (CZK/ha) |
---|---|
Zlín | −763 |
Vysočina | 111 |
Olomouc | −327 |
Central Bohemia | −194 |
South Moravian | −907 |
Liberec | 321 |
South Bohemian | 46 |
Pilsen | 58 |
Hradec Králové | 221 |
Pardubice | 218 |
Moravian-Silesian | −227 |
Usti nad Labem | 78 |
Karlovy Vary | 352 |
Crop Region | Wheat | Rye | Barley | Oats | Rapeseed | Potatoes | Sugar Beet | Maize | Fodder Crops | Permanent Grasslands |
---|---|---|---|---|---|---|---|---|---|---|
Zlín (r) | 23.01 | 0.74 | 15.74 | 0.52 | 5.64 | 0.37 | 3.27 | 10.54 | 14.33 | 25.84 |
CSO (R) | 23.50 | 0.29 | 7.08 | 0.74 | 11.11 | 0.18 | 1.37 | 9.42 | 7.13 | 39.18 |
dif. in p.p. | 0.49 | −0.45 | −8.66 | 0.22 | 5.47 | −0.19 | −1.90 | −1.12 | −7.20 | 13.35 |
South Moravian (r) | 26.83 | 1.85 | 19.26 | 0.35 | 3.73 | 0.51 | 5.09 | 13.44 | 16.89 | 12.05 |
CSO (R) | 37.16 | 0.86 | 11.63 | 0.57 | 14.06 | 0.46 | 1.67 | 19.34 | 6.72 | 7.52 |
dif. in p.p. | 10.33 | −0.98 | −7.63 | 0.22 | 10.33 | −0.05 | −3.43 | 5.90 | −10.17 | −4.53 |
Olomouc (r) | 24.68 | 2.18 | 16.18 | 0.81 | 5.83 | 1.29 | 4.29 | 10.44 | 15.21 | 19.09 |
CSO (R) | 22.32 | 0.48 | 15.78 | 0.64 | 11.95 | 0.14 | 5.36 | 9.23 | 5.11 | 29.00 |
dif. in p.p. | −2.36 | −1.70 | −0.40 | −0.17 | 6.12 | −1.16 | 1.08 | −1.21 | −10.10 | 9.91 |
Moravian-Silesian (r) | 20.07 | 3.72 | 15.76 | 1.26 | 6.02 | 2.30 | 2.23 | 8.92 | 14.13 | 25.58 |
CSO (R) | 20.32 | 0.43 | 8.24 | 1.15 | 10.67 | 0.41 | 3.49 | 6.06 | 4.08 | 45.15 |
dif. in p.p. | 0.25 | −3.29 | −7.52 | −0.11 | 4.65 | −1.89 | 1.26 | −2.87 | −10.04 | 19.57 |
Central Bohemia (r) | 25.64 | 4.01 | 18.80 | 1.28 | 7.48 | 2.01 | 3.38 | 11.50 | 17.24 | 8.67 |
CSO (R) | 34.49 | 0.83 | 12.45 | 1.09 | 17.90 | 1.06 | 3.62 | 8.50 | 5.87 | 14.18 |
dif. in p.p. | 8.85 | −3.18 | −6.34 | −0.18 | 10.42 | −0.95 | 0.24 | −3.00 | −11.38 | 5.52 |
Czechia (r) | 21.87 | 3.41 | 17.07 | 1.71 | 6.99 | 2.28 | 2.44 | 10.08 | 15.53 | 18.62 |
CSO (R) | 26.15 | 0.81 | 10.36 | 1.37 | 13.14 | 0.64 | 2.07 | 9.76 | 4.13 | 31.58 |
dif. in p.p. | 4.28 | −2.61 | −6.71 | −0.34 | 6.14 | −1.64 | −0.37 | −0.32 | −11.40 | 12.97 |
Chi-Square Test for Specified Proportions in Given Regions | ||||||
---|---|---|---|---|---|---|
Region | Zlin | South Moravian | Olomouc Region | Moravian-Silesian | Central Bohemia | Czech Republic |
Chi-Square | 27,729.8 | 253,230 | 38,954.42 | 61,421.75 | 11,3267.2 | 820,748,5 |
DF | 9 | 9 | 9 | 9 | 9 | 9 |
Pr > ChiSq | <0.0001 | <0.0001 | <0.0001 | <0.0001 | <0.0001 | <0.0001 |
Chi (DF9) alfa 0.05 | 16.919 | 16.919 | 16.919 | 16.919 | 16.919 | 16.919 |
alfa | 0.05 | 0.05 | 0.05 | 0.05 | 0.05 | 0.05 |
Sample Size | 142,783.08 | 304,467.44 | 229,843.01 | 196,631.17 | 494,303.88 | 3,134,794.07 |
Region | Fodder Crops | Maize | Pernanment Grasslands | Barley | Oats | Potatoes | Rapeseed | Rye | Sugar Beet | Wheat | |
---|---|---|---|---|---|---|---|---|---|---|---|
Zlin | % | 0.1 | 0.1 | 0.4 | 0.1 | 0.0 | 0.0 | 0.1 | 0.0 | 0.0 | 0.2 |
Test % | 0.1 | 0.1 | 0.3 | 0.2 | 0.0 | 0.0 | 0.1 | 0.0 | 0.0 | 0.2 | |
Statistics u | −221.6 | 22.8 | 263.0 | −246.7 | 160.7 | −194.8 | 268.4 | −231.5 | −227.0 | 10.5 | |
South Moravian | % | 0.1 | 0.1 | 0.1 | 0.1 | 0.0 | 0.0 | 0.2 | 0.0 | 0.0 | 0.4 |
Test % | 0.2 | 0.1 | 0.1 | 0.2 | 0.0 | 0.0 | 0.0 | 0.0 | 0.1 | 0.3 | |
Statistics u | −103.6 | 11.0 | −64.7 | −92.3 | 26.4 | −3.7 | 1054.9 | −27.9 | −50.4 | 177.0 | |
Olomouc | % | 0.1 | 0.1 | 0.3 | 0.2 | 0.0 | 0.0 | 0.1 | 0.0 | 0.1 | 0.2 |
Test % | 0.2 | 0.1 | 0.2 | 0.2 | 0.0 | 0.0 | 0.1 | 0.0 | 0.0 | 0.2 | |
Statistics u | −84.9 | 26.8 | 165.7 | −5.6 | −8.1 | −16.2 | 90.2 | −26.5 | 28.9 | −28.8 | |
Moravian-Silesian | % | 0.0 | 0.1 | 0.5 | 0.1 | 0.0 | 0.0 | 0.061 | 0.0 | 0.0 | 0.2 |
Test % | 0.1 | 0.1 | 0.3 | 0.2 | 0.0 | 0.0 | 0.060 | 0.0 | 0.0 | 0.2 | |
Statistics u | −74.2 | 31.2 | 306.3 | −72.1 | −4.2 | −24.0 | 0.8 | −26.6 | 47.9 | 3.1 | |
Central Bohemia | % | 0.1 | 0.2 | 0.1 | 0.1 | 0.0 | 0.0 | 0.1 | 0.0 | 0.0 | 0.3 |
Test % | 0.2 | 0.1 | 0.1 | 0.2 | 0.0 | 0.0 | 0.1 | 0.0 | 0.0 | 0.3 | |
Statistics u | −135.7 | 187.1 | 184.3 | −103.2 | −11.1 | −35.0 | 30.2 | −53.0 | 9.8 | 191.7 | |
Czech Republic | % | 0.0 | 0.1 | 0.3 | 0.1 | 0.0 | 0.0 | 0.1 | 0.0 | 0.0 | 0.3 |
Test % | 0.2 | 0.1 | 0.2 | 0.2 | 0.0 | 0.0 | 0.1 | 0.0 | 0.0 | 0.2 | |
Statistics u | −312.7 | 216.6 | 851.0 | −270.1 | −41.9 | −104.3 | 235.7 | −125.7 | −39.6 | 226.8 |
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Gebeltová, Z.; Malec, K.; Maitah, M.; Smutka, L.; Appiah-Kubi, S.N.K.; Maitah, K.; Sahatqija, J.; Sirohi, J. The Impact of Crop Mix on Decreasing Soil Price and Soil Degradation: A Case Study of Selected Regions in Czechia (2002–2019). Sustainability 2020, 12, 444. https://doi.org/10.3390/su12020444
Gebeltová Z, Malec K, Maitah M, Smutka L, Appiah-Kubi SNK, Maitah K, Sahatqija J, Sirohi J. The Impact of Crop Mix on Decreasing Soil Price and Soil Degradation: A Case Study of Selected Regions in Czechia (2002–2019). Sustainability. 2020; 12(2):444. https://doi.org/10.3390/su12020444
Chicago/Turabian StyleGebeltová, Zdeňka, Karel Malec, Mansoor Maitah, Luboš Smutka, Seth Nana Kwame Appiah-Kubi, Kamil Maitah, Jeta Sahatqija, and Jitka Sirohi. 2020. "The Impact of Crop Mix on Decreasing Soil Price and Soil Degradation: A Case Study of Selected Regions in Czechia (2002–2019)" Sustainability 12, no. 2: 444. https://doi.org/10.3390/su12020444
APA StyleGebeltová, Z., Malec, K., Maitah, M., Smutka, L., Appiah-Kubi, S. N. K., Maitah, K., Sahatqija, J., & Sirohi, J. (2020). The Impact of Crop Mix on Decreasing Soil Price and Soil Degradation: A Case Study of Selected Regions in Czechia (2002–2019). Sustainability, 12(2), 444. https://doi.org/10.3390/su12020444