Intercropping—Evaluating the Advantages to Broadacre Systems
Abstract
:1. Introduction
2. Intercropping Systems
3. Review of Intercropping Metrics
3.1. Land Equivalent Ratio
3.2. Other Yield-Based Measures
3.3. Value Measures
3.4. Profit Measures
3.5. Risk Measures
3.6. Measures of Indirect Benefits
4. Selecting the Most Appropriate Intercropping Metric
5. An Example of Intercropping Evaluation
6. Summary and Conclusions
- Though LER is a good measure to indicate how efficiently the given land area is utilized by an intercropping system compared to a monocropping system, LER alone is not adequate to assess the relative advantage of intercropping in terms of productivity and value.
- Unequal area sown to mixtures and their monocultures (enterprise mix ratio) will affect the value, profit and risk needed to be applied to assess intercropping advantage. This needs to be applied to all value, profit and risk metrics.
- Valuing the benefits of intercropping beyond crop yield is also necessary, which can affect the choice of cropping strategies. Thus, the researchers’ focus should not only be on increasing the biomass and yield in the short term, but also on how the adoption of intercropping can enhance environmental services and longer-term productivity improvements.
- There are management complexities associated with intercropping which could demand more skills and knowledge, change in machinery and infrastructure etc, thereby increasing the cost of producing intercrops as compared to monocrops. Evaluation of intercropping advantages should consider not only benefits but also costs associated.
- There is a need to use appropriate profit and risk metrics in assessing intercropping. We recommend the use of the net gross margin, profit ratio and the ’certainty equivalent’ that can take into account all possible private differences in costs and benefits between intercropping and monocropping systems, including the implications for business risk and the decision-makers risk tolerance.
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
- Baulcombe, D.; Crute, I.; Davies, B.; Dunwell, J.; Gale, M.; Jones, J.; Pretty, J.; Sutherland, W.; Toulmin, C. Reaping the Benefits: Science and the Sustainable Intensification of Global Agriculture; The Royal Society: London, UK, 2009. [Google Scholar]
- Antle, J.M.; Ray, S. Sustainable Agricultural Development An. Economic Perspective. In Palgrave Studies in Agricultural Economics and Food Policy; Christopher, B., Ed.; Cornell University: Ithaca, NY, USA, 2020; Available online: https://link.springer.com/book/10.1007%2F978-3-030-34599-0 (accessed on 17 February 2021).
- Boult, C.; Chancellor, W. Productivity of Australian Broadacre and Dairy Industries, 2018–2019; Research Report; Australian Bureau of Agricultural and Resource Economics and Sciences (ABARES): Canberra, Australia, 2020. [Google Scholar]
- O’Donnell, C. Productivity and Efficiency Analysis: An Economic Approach to Measuring and Explaining Managerial Performance; Springer Nature: Singapore, 2018. [Google Scholar]
- Bernard, B.; Lux, A. How to feed the world sustainably: An overview of the discourse on agroecology and sustainable intensification. Reg. Environ. Chang. 2017, 17, 1279–1290. [Google Scholar] [CrossRef]
- Barr, N. The Social Landscapes of Rural Victoria. In Landscape Analysis and Visualisation: Spatial Models for Natural Resource Management and Planning; Springer Science & Business Media: Berlin/Heidelberg, Germany, 2008; pp. 305–325. [Google Scholar] [CrossRef]
- Eadie, L.; Stone, C.; Burton, R. Farming Smarter, not Harder: Securing Our Agricultural Economy; Centre for Policy Development: Sydney, Australia, 2012. [Google Scholar]
- Dowling, A.; Sadras, V.O.; Roberts, P.; Doolette, A.; Zhou, Y.; Denton, M.D. Legume-oilseed intercropping in mechanised broadacre agriculture–A review. Field Crops Res. 2021, 260. [Google Scholar] [CrossRef]
- Altieri, M.A.; Funes-Monzote, F.R.; Petersen, P. Agroecologically efficient agricultural systems for smallholder farmers: Contributions to food sovereignty. Agron. Sustain. Dev. 2012, 32, 1–13. [Google Scholar] [CrossRef] [Green Version]
- Sullivan, P. Intercropping Principles and Production Practices. Appropriate Technology Transfer for Rural Areas Publication. 2003. Available online: http://www.attra.ncat.org (accessed on 12 January 2021).
- Amanullah, F.K.; Muhammad, H.; Jan, A.U.; Ali, G. Land equivalent ratio, growth, yield and yield components response of mono-cropped vs. inter-cropped common bean and maize with and without compost application. Agric. Biol. J. N. Am. 2016, 7, 40–49. [Google Scholar]
- Bedoussac, L.; Journet, E.P.; Hauggaard-Nielsen, H.; Naudin, C.; Corre-Hellou, G.; Jensen, E.S.; Prieur, L.; Justes, E. Ecological principles underlying the increase of productivity achieved by cereal-grain legume intercrops in organic farming. A review. Agron. Sustain. Dev. 2015, 35, 11–935. [Google Scholar] [CrossRef]
- Bybee-Finley, K.; Ryan, M.R. Advancing intercropping research and practices in industrialized agricultural landscapes. Agriculture 2018, 8, 80. [Google Scholar] [CrossRef] [Green Version]
- Tilman, D. Benefits of intensive agricultural intercropping. Nat. Plants 2020, 6, 604–605. [Google Scholar] [CrossRef]
- De Roest, K.; Ferrari, P.; Knickel, K. Specialisation and economies of scale or diversification and economies of scope? Assessing different agricultural development pathways. J. Rural Stud. 2018, 59, 222–231. [Google Scholar] [CrossRef]
- Cowger, C.; Weisz, R. Winter wheat blends (mixtures) produce a yield advantage in North Carolina. Agron. J. 2008, 100, 169–177. [Google Scholar] [CrossRef]
- Kiær, L.P.; Skovgaard, I.M.; Østergård, H. Grain yield increase in cereal variety mixtures: A meta-analysis of field trials. Field Crops Res. 2009, 114, 361–373. [Google Scholar] [CrossRef]
- Lin, B.B. Resilience in agriculture through crop diversification: Adaptive management for environmental change. BioScience 2011, 61, 183–193. [Google Scholar] [CrossRef] [Green Version]
- Makate, C.; Wang, R.; Makate, M.; Mango, N. Crop diversification and livelihoods of smallholder farmers in Zimbabwe: Adaptive management for environmental change. SpringerPlus 2016, 5, 1135. [Google Scholar] [CrossRef] [Green Version]
- Sharma, N.K.; Singh, R.J.; Mandal, D.; Kumar, A.; Alam, N.M.; Keesstra, S. Increasing farmer’s income and reducing soil erosion using intercropping in rainfed maize-wheat rotation of Himalaya, India. Agric. Ecosyst. Environ. 2017, 247, 43–53. [Google Scholar] [CrossRef]
- Manevski, K.; Børgesen, C.D.; Andersen, M.N.; Kristensen, I.S. Reduced nitrogen leaching by intercropping maize with red fescue on sandy soils in North Europe: A combined field and modeling study. Plant Soil 2015, 388, 67–85. [Google Scholar] [CrossRef]
- Gou, F.; van Ittersum, M.K.; Wang, G.; van der Putten, P.E.; van der Werf, W. Yield and yield components of wheat and maize in wheat–maize intercropping in the Netherlands. Eur. J. Agron. 2016, 76, 17–27. [Google Scholar] [CrossRef]
- Hombegowda, H.C.; Adhikary, P.P.; Jakhar, P.; Madhu, M.; Barman, D. Hedge row intercropping impact on run-off, soil erosion, carbon sequestration and millet yield. Nutr. Cycl. Agroecosyst. 2020, 116, 103–116. [Google Scholar] [CrossRef]
- Johnston, G.; Vaupel, S.; Kegel, F.; Cadet, M. Crop and farm diversification provide social benefits. Calif. Agric. 1995, 49, 10–16. [Google Scholar] [CrossRef] [Green Version]
- Zhang, C.; Dong, Y.; Tang, L.; Zheng, Y.; Makowski, D.; Yu, Y.; Zhang, F.; van der Werf, W. Intercropping cereals with faba bean reduces plant disease incidence regardless of fertilizer input; a meta-analysis. Eur. J. Plant Pathol. 2019, 154, 931–942. [Google Scholar] [CrossRef]
- Ma, Y.H.; Fu, S.L.; Zhang, X.P.; Zhao, K.; Chen, H.Y. Intercropping improves soil nutrient availability, soil enzyme activity and tea quantity and quality. Appl. Soil Ecol. 2017, 119, 171–178. [Google Scholar] [CrossRef]
- Nyawade, S.O.; Karanja, N.N.; Gachene, C.K.; Gitari, H.I.; Schulte-Geldermann, E.; Parker, M.L. Short-term dynamics of soil organic matter fractions and microbial activity in smallholder potato-legume intercropping systems. Appl. Soil Ecol. 2019, 142, 123–135. [Google Scholar] [CrossRef]
- Schmidt, O.; Curry, J.P.; Hackett, R.A.; Purvis, G.; Clements, R.O. Earthworm communities in conventional wheat monocropping and low-input wheat-clover intercropping systems. Ann. Appl. Biol. 2001, 138, 377–388. [Google Scholar] [CrossRef]
- Schmidt, O.; Clements, R.; Donaldson, G. Why do cereal–legume intercrops support large earthworm populations? Appl. Soil Ecol. 2003, 22, 181–190. [Google Scholar] [CrossRef]
- Nyawade, S.O.; Karanja, N.N.; Gachene, C.K.; Gitari, H.I.; Schulte-Geldermann, E.; Parker, M. Optimizing soil nitrogen balance in a potato cropping system through legume intercropping. Nutr. Cycl. Agroecosyst. 2020, 12, 1–7. [Google Scholar] [CrossRef] [Green Version]
- Latati, M.; Aouiche, A.; Tellah, S.; Laribi, A.; Benlahrech, S.; Kaci, G.; Ouarem, F.; Ounane, S.M. Intercropping maize and common bean enhance microbial carbon and nitrogen availability in low phosphorus soil under Mediterranean conditions. Eur. J. Soil Biol. 2017, 80, 9–18. [Google Scholar] [CrossRef]
- Ren, Y.Y.; Wang, X.L.; Zhang, S.Q.; Palta, J.A.; Chen, Y.L. Influence of spatial arrangement in maize-soybean intercropping on root growth and water use efficiency. Plant Soil 2017, 415, 131–144. [Google Scholar] [CrossRef]
- Ren, J.; Zhang, L.; Duan, Y.; Zhang, J.; Evers, J.B.; Zhang, Y.; Su, Z.; van der Werf, W. Intercropping potato (Solanum tuberosum L.) with hairy vetch (Vicia villosa) increases water use efficiency in dry conditions. Field Crops Res. 2019, 240, 168–176. [Google Scholar] [CrossRef]
- Njeru, E.M. Crop diversification: A potential strategy to mitigate food insecurity by smallholders in sub-Saharan Africa. J. Agric. Food Syst. Community Dev. 2013, 3, 63–69. [Google Scholar] [CrossRef] [Green Version]
- Iqbal, N.; Hussain, S.; Ahmed, Z.; Yang, F.; Wang, X.; Liu, W.; Yong, T.; Du, J.; Shu, K.; Yang, W.; et al. Comparative analysis of maize–soybean strip intercropping systems: A review. Plant Prod. Sci. 2019, 22, 131–142. [Google Scholar] [CrossRef] [Green Version]
- Mamine, F. Barriers and levers to developing wheat–pea intercropping in Europe: A review. Sustainability 2020, 12, 6962. [Google Scholar] [CrossRef]
- Lithourgidis, A.S.; Vasilakoglou, I.B.; Dhima, K.V.; Dordas, C.A.; Yiakoulaki, M.D. Forage yield and quality of common vetch mixtures with oat and triticale in two seeding ratios. Field Crops Res. 2006, 99, 106–113. [Google Scholar] [CrossRef]
- Swinton, S.M.; Jolejole-Foreman, C.B.; Lupi, F.; Ma, S.; Zhang, W.; Chen, H. Economic value of ecosystem services from agriculture. In The Ecology of Agricultural Landscapes: Long-Term Research on the Path to Sustainability; Hamilton, S.K., Doll, J.E., Robertson, G.P., Eds.; Oxford University Press: New York, NY, USA, 2015; pp. 54–76. [Google Scholar]
- Willey, R.W.; Osiru, D.S.O. Studies on mixtures of maize and beans (Phaseolus vulgaris) with particular reference to plant population. J. Agric. Sci. 1972, 79, 517–529. [Google Scholar] [CrossRef]
- Mead, R.; Willey, R.W. The concept of a ‘land equivalent ratio’and advantages in yields from intercropping. Exp. Agric. 1980, 16, 217–228. [Google Scholar] [CrossRef] [Green Version]
- Adetiloye, P.O.; Ezedinma, F.O.C.; Okigbo, B.N. A land equivalent coefficient (LEC) concept for the evaluation of competitive and productive interactions in simple to complex crop mixtures. Ecol. Model. 1983, 19, 27–39. [Google Scholar] [CrossRef]
- Harris, D.; Natarajan, M.; Willey, R.W. Physiological basis for yield advantage in a sorghum/groundnut intercrop exposed to drought. 1. Dry-matter production, yield, and light interception. Field Crops Res. 1987, 17, 259–272. [Google Scholar] [CrossRef] [Green Version]
- Wilson, J.B. Shoot competition and root competition. J. Appl. Ecol. 1988, 25, 279–296. [Google Scholar] [CrossRef]
- Odo, P.E. Evaluation of short and tall sorghum varieties in mixtures with cowpea in the Sudan savanna of Nigeria: Land equivalent ratio, grain yield and system productivity index. Exp. Agric. 1991, 27, 435–441. [Google Scholar] [CrossRef]
- Francis, C.A. Future perspectives of multiple cropping. In Multiple Cropping Systems; Francis, C.A., Ed.; Macmillan Publishers: New York, NY, USA, 1986; pp. 351–370. [Google Scholar]
- Vandermeer, J.H. The Ecology of Intercropping; Cambridge University Press: Cambridge, UK, 1992. [Google Scholar]
- Soetedjo, I.N.P.; Martin, L.D. Intercropping with canola improves the productivity and sustainability of field pea. In Proceedings of the 11th Australian Agronomy Conference, Geelong, Australia, 2–6 February 2003; Available online: http://www.regional.org.au/au/asa/2003/c/4/martin.htm (accessed on 12 January 2021).
- Jahansooz, M.R.; Yunusa, I.A.M.; Coventry, D.R.; Palmer, A.R.; Eamus, D. Radiation-and water-use associated with growth and yields of wheat and chickpea in sole and mixed crops. Eur. J. Agron. 2007, 26, 275–282. [Google Scholar] [CrossRef] [Green Version]
- Eyre, J.X.; Routley, R.A.; Rodriguez, D.; Dimes, J.P. Intercropping maize and mungbean to intensify summer cropping systems in Queensland, Australia. In World Congress on Conservation Agriculture 2011 Papers, Proceedings of the 5th World Congress on Conservation Agriculture and Farming Systems Design, Brisbane, Australia, 26–29 September 2011; Asia-Pacific Association of Agricultural Research Institution: Bangkok, Thailand, 2011. [Google Scholar]
- Craig, P.R. Development of a Novel Crop-Pasture System for Mixed Farms in the Higher Rainfall Zone of Southern Australia. Ph.D. Thesis, School of Agriculture, Food and Wine, The University of Adelaide, Adelaide, Australia, 2011. [Google Scholar]
- Malhi, S.S. Improving crop yield, N uptake and economic returns by intercropping barley or canola with pea. Agric. Sci. 2012, 3. [Google Scholar] [CrossRef] [Green Version]
- Schultz, B.; Phillips, C.; Rosset, P.; Vandermeer, J. An experiment in intercropping cucumbers and tomatoes in southern Michigan, USA. Sci. Hortic. 1982, 18, 1–8. [Google Scholar] [CrossRef]
- Dutra, A.F.; de Melo, A.S.; Dutra, W.F.; da Silva, F.G.; de Oliveira, I.M.; Suassuna, J.F.; Neto, J.G.V. Agronomic performance and profitability of castor bean (‘Ricinus communis’ L.) and peanut (‘Arachis hypogaea’ L.) intercropping in the Brazilian semiarid region. Aust. J. Crop Sci. 2015, 9, 120. [Google Scholar]
- Ngwira, A.R.; Aune, J.B.; Mkwinda, S. On-farm evaluation of yield and economic benefit of short-term maize legume intercropping systems under conservation agriculture in Malawi. Field Crops Res. 2012, 132, 149–157. [Google Scholar] [CrossRef]
- Azam-Ali, S.N.; Matthews, R.B.; Williams, J.H.; Peacock, J.M. Light use, water uptake and performance of individual components of a sorghum/groundnut intercrop. Exp. Agric. 1990, 26, 413–427. [Google Scholar] [CrossRef]
- Choudhary, V.K.; Dixit, A.; Chauhan, B.S. Resource-use maximisation through legume intercropping with maize in the eastern Himalayan region of India. Crop. Pasture Sci 2016, 67, 508–519. [Google Scholar] [CrossRef]
- Wang, Z.G.; Jin, X.; Bao, X.G.; Li, X.F.; Zhao, J.H.; Sun, J.H.; Christie, P.; Li, L. Intercropping enhances productivity and maintains the most soil fertility properties relative to sole cropping. PLoS ONE 2014, 9, e113984. [Google Scholar] [CrossRef] [Green Version]
- Lithourgidis, A.S.; Vlachostergios, D.N.; Dordas, C.A.; Damalas, C.A. Dry matter yield, nitrogen content, and competition in pea–cereal intercropping systems. Eur. J. Agron. 2011, 34, 287–294. [Google Scholar] [CrossRef]
- Pelzer, E.; Bazot, M.; Makowski, D.; Corre-Hellou, G.; Naudin, C.; Al Rifaï, M.; Carrouée, B. Pea–wheat intercrops in low-input conditions combine high economic performances and low environmental impacts. Eur. J. Agron. 2012, 40, 39–53. [Google Scholar] [CrossRef]
- Kermah, M.; Franke, A.C.; Adjei-Nsiah, S.; Ahiabor, B.D.; Abaidoo, R.C.; Giller, K.E. Maize-grain legume intercropping for enhanced resource use efficiency and crop productivity in the Guinea savanna of northern Ghana. Field Crops Res. 2017, 213, 38–50. [Google Scholar] [CrossRef]
- Huang, C.; Liu, Q.; Heerink, N.; Stomph, T.; Li, B.; Liu, R.; van der Werf, W. Economic performance and sustainability of a novel intercropping system on the North China Plain. PLoS ONE 2015, 10, e0135518. [Google Scholar] [CrossRef] [Green Version]
- Li, Q.Z.; Sun, J.H.; Wei, X.J.; Christie, P.; Zhang, F.S.; Li, L. Overyielding and interspecific interactions mediated by nitrogen fertilization in strip intercropping of maize with faba bean, wheat and barley. Plant Soil 2011, 339, 147–161. [Google Scholar] [CrossRef] [Green Version]
- Chai, Q.; Qin, A.; Gan, Y.; Yu, A. Higher yield and lower carbon emission by intercropping maize with rape, pea, and wheat in arid irrigation areas. Agron. Sustain. Dev. 2014, 34, 535–543. [Google Scholar] [CrossRef]
- Moghbeli, T.; Bolandnazar, S.; Panahande, J.; Raei, Y. Evaluation of yield and its components on onion and fenugreek intercropping ratios in different planting densities. J. Clean. Prod. 2019, 213, 634–641. [Google Scholar] [CrossRef]
- Oyejola, B.A.; Mead, R. Statistical assessment of different ways of calculating land equivalent ratios (LER). Exp. Agric. 1982, 18, 125–138. [Google Scholar] [CrossRef] [Green Version]
- Davidson, B.R.; Martin, B.R. The relationship between yields on farms and in experiments. Aust. J. Agric. Econ. 1965, 9, 129–140. [Google Scholar] [CrossRef] [Green Version]
- Jolliffe, P.A.; Wanjau, F.M. Competition and productivity in crop mixtures: Some properties of productive intercrops. J. Agric. Sci. 1999, 132, 425–435. [Google Scholar] [CrossRef]
- Trapnell, L.; Malcolm, L.R. Expected benefits on and off farm from including lucerne (Medicago sativa) in crop rotations on the Broken Plains of north-eastern Victoria. AFBM J. 2014, 11, 19–31. [Google Scholar]
- Dillon, J.L. The definition of farm management. J. Agric. Econ. 1980, 31, 257–258. [Google Scholar] [CrossRef]
- Anderson, J.R.; Dillon, J.L.; Hardaker, J.B. Agricultural Decision Analysis; Iowa State University Press: Ames, Iowa, 1977. [Google Scholar]
- Boehlje, M.D.; Eidman, V.R. Farm Management; John Wiley and Sons: Hoboken, NJ, USA, 1984. [Google Scholar]
- Malcolm, L.R.; Makeham, J.P.; Wright, V. The Farming Game: Agricultural Management and Marketing; Cambridge University Press: Melbourne, Australia, 2005. [Google Scholar]
- Pannell, D. Economic perspectives on nitrogen in farming systems: Managing trade-offs between production, risk and the environment. Soil Res. 2017, 55, 473–478. [Google Scholar] [CrossRef]
- Hadar, J.; Russell, W.R. Rules for ordering uncertain prospects. Am. Econ. Rev. 1969, 4, 25–34. [Google Scholar]
- Hanoch, G.; Levy, H. Efficiency analysis of choices involving risk. Rev. Econ. Stud. 1969, 36, 335–345. [Google Scholar] [CrossRef]
- Hochman, Z.; Horan, H.; Garcia, J.N.; Hopwood, G.; Whish, J.; Bell, L.; Zhang, X.; Jing, H. Cropping system yield gaps can be narrowed with more optimal rotations in dryland subtropical Australia. Agric. Syst. 2020, 184, 1–9. [Google Scholar] [CrossRef]
- Hardaker, J.B.; Richardson, J.W.; Lien, G.; Schumann, K.D. Stochastic efficiency analysis with risk aversion bounds: A simplified approach. Aust. J. Agric. Resour. Econ. 2004, 48, 253–270. [Google Scholar] [CrossRef] [Green Version]
- Hardaker, J.B.; Lien, G.; Anderson, J.R.; Huirne, R.B.M. Coping with Risk in Agriculture: Applied Decision Analysis, 3rd ed.; CABI Publishing: Boston, MA, USA, 2015. [Google Scholar]
- Gandorfer, M.; Pannell, D.; Meyer-Aurich, A. Analysing the effects of risk and uncertainty on optimal tillage and nitrogen fertilizer intensity for field crops in Germany. Agric. Syst. 2011, 104, 615–622. [Google Scholar] [CrossRef]
- Monjardino, M.; Hochman, Z.; Horan, H. Yield potential determines Australian wheat growers’ capacity to close yield gaps while mitigating economic risk. Agron. Sustain. Dev. 2019, 39, 39–49. [Google Scholar]
- Fathelrahman, E.M.; Ascough, J.C.; Hoag, D.L.; Malone, R.W.; Heilman, P.; Wiles, L.J.; Kanwar, R.S. Economic and stochastic efficiency comparison of experimental tillage systems in corn and soybean under risk. Exp. Agric. 2011, 47, 111–136. [Google Scholar] [CrossRef] [Green Version]
- Alcon, F.; Marín-Miñano, C.; Zabala, J.A.; de-Miguel, M.D.; Martínez-Paz, J.M. Valuing diversification benefits through intercropping in Mediterranean agroecosystems: A choice experiment approach. Ecol. Econ. 2020, 171, 106593. [Google Scholar] [CrossRef]
- Martin-Guay, M.O.; Paquette, A.; Dupras, J.; Rivest, D. The new green revolution: Sustainable intensification of agriculture by intercropping. Sci. Total Environ. 2018, 615, 767–772. [Google Scholar] [CrossRef]
- Cooper, J.C.; Signorello, G. Farmer premiums for the voluntary adoption of conservation plans. J. Environ. Plan. Manag. 2008, 51, 1–14. [Google Scholar] [CrossRef] [Green Version]
- DAWE. Agriculture Stewardship Package. Department of Agriculture, Water and Environment, Australian Government, 2021. Available online: https://www.agriculture.gov.au/sites/default/files/documents/ag-steward-program-factsheet-1.pdf (accessed on 9 April 2021).
- Willey, R. Evaluation and presentation of intercropping advantages. Exp. Agric. 1985, 21, 119–133. [Google Scholar] [CrossRef] [Green Version]
Metrics | Description | How to Measure? | Decision Criteria | Reference |
---|---|---|---|---|
Land Equivalent Ratio (LER) | Measures the relative land area required to grow the same quantity of both crop species in the mixture if they were grown as monocultures rather than as companions. | , , | LER > 1 indicates intercropping advantage. | Willey and Osiru [39]; Mead and Willey [40] |
Land Equivalent Coefficient (LEC) | Measures the interaction between component crops in the mixture. | For a two-crop mixture, a yield advantage is obtained if the LEC value is > 0.25. | Adetiloye et al. [41] | |
Crop Performance Ratio (CPR) | Measures the performance of intercrops relative to the component sole crops. | , , CPR | CPR > 1 indicates intercropping advantage. | Harris et al. [42] |
Relative Yield of Mixture (RYM) | Measures the relative yield from the intercropping system compared to that of the monocropping system. | RYM | RYM > 1 indicates intercropping advantage. | Wilson [43] |
System Productivity Index (SPI) | Converts the yield of a component crop in terms of another crop in the mixture utilizing monocrops yields ratio. | Intercropping is advantageous if SPI of intercrops > SPI of monocrops. | Odo [44] | |
Crop Equivalent Yield (CEY) | Standardizes the yield of a component crop in the mixture in terms of another component crop based on the prices. | Intercropping is advantageous if CEY of intercrops > CEY of monocrops. | Francis [45] | |
Relative Value Total (RVT) | Measures the relative value from the intercropping system compared to that of the most valuable of the two monocultures. | RVT = If P1Y1m > P2Y2m | RVT > 1 indicates intercropping advantage. | Vandermeer [46] |
Literature | Intercropping System | Assessment Method | Major Findings | Countries |
---|---|---|---|---|
Soetedjo et al. [47] | Field pea-Canola | LER | Intercropping significantly out yielded monocroppings with LER equals 1.79. Intercropping significantly lowered the incidence of black spot of field pea and, also lowered the harvest losses. | Australia |
Jahansooz et al. [48] | Wheat-Chickpea | LER | LER based on grain yields were 1.01 in 1994 and 1.02 in 1995. Neither radiation use efficiency nor water use efficiency was improved by intercropping. | Australia |
Eyre et al. [49] | Maize-Mungbean | LER | Intercropping yields were comparable to that of monoculture with no significant difference. | Australia |
Craig [50] | Grain-Perennial pasture | LER, GM | Crop-pasture intercropping can improve grain yield and pasture production on mixed farms in the higher rainfall zone of southern Australia. | Australia |
Malhi [51] | Pea-Barley Pea-Canola | LER, Net returns | Intercrop of barley or canola with pea improved crop yield, N uptake and net returns, and reduced land requirements compared to barley, canola or pea as sole crops. | Canada |
Schultz [52] | Cucumber-Tomato | LER, RVT | Intercropping improved yield per unit area. | USA |
Dutra et al. [53] | Castor bean-Peanut | LER, LEC, GM | Intercropping was advantageous if the peanut is sowed 20 days after castor in the spaces 2.0 × 0.5 (castor) and 2.0 × 0.2 (peanut). | Brazil |
Ngwira et al. [54] | Maize-Legume | GM | Intercropping had a positive effect on yield. Total variable costs were higher in intercropping systems compared to conventional practice. However, intercropping resulted in a higher gross margin compared to monocropping. | Malawi |
Azam-Ali [55] | Sorghum-Groundnut | LER, CPR | There was little increase in the overall productivity of the intercrop compared with the combined sole crops with LER = 1.06 and CPR = 1.08. | India |
Choudhary et al. [56] | Maize-Soybean Maize-Peanut | LER, LEC, CEY | Intercropping increased land-use efficiency by 17–53% and land-equivalent coefficient by 0.21–0.56. | India |
Wang et al. [57] | Maize-Faba bean, Maize-Soyabean, Maize-Chickpea, Maize-Turnip | WM of crops yields | Grain yields were significantly greater in all four intercropping systems than the corresponding monocropping over two years. | China |
Lithourgidis et al. [58] | Pea-Wheat, Pea-Rye, Pea-Triticale | LER, SPI | Pea-triticale and pea-wheat mixtures were more productive than other mixtures. | Greece |
Pelzer et al. [59] | Pea-Wheat | LER, GM | Pea–wheat intercropping is a promising way to produce cereal grains in an efficient, economically sustainable and environmentally friendly way. | France |
Kermah et al. [60] | Maize-Legume (Cowpea, Soybean, Groundnut) | LER, Net benefit (Total revenue − Total cost) | LERs of all intercrops were greater than unity. Intercropping was found more beneficial in less fertile fields and more marginal environments compared with fertile fields. Costs of production were higher in intercropping systems, however, the greater grain yield in intercropping resulted in larger net benefits than in monoculture systems. | Ghana |
Huang et al. [61] | Maize-Watermelon | LER, GM, returns to labour | Compared to the conventional cropping system, the integration of watermelon into the system increased revenues by 60%, variable costs by 79% and the gross margin by 53%. Labour use in the intercropping system was more than three times than in the conventional cropping system. | China |
Li et al. [62] | Maize-Faba bean, Maize-Wheat, Maize-Barley | LER, RYM | Maize was overyielding when intercropped with Faba bean, but under yielding when intercropped with Wheat or Barley. | China |
Chai et al. [63] | Maize-Wheat, Maize-Rape, Maize-Pea, Soybean-Wheat | Relative yield | Yield increase of 27 % for maize–wheat, 41 % for maize–rape, and 42 % for maize–pea versus sole crops were obtained. | China |
Moghbeli [64] | Onion-Fenugreek | LER, RVT | Intercropping improved yield per unit area. | Iran |
Harris et al. [42] | Sorghum-Groundnut | CPR | Intercrop gave more yield than the two crops separately. | India |
Expected Benefits | Valuation Method | Comment/Assumption |
---|---|---|
Increase in crop yield | Calculate revenue (price X yield) | Use rule-based simulation modelling to determine the change in yield. |
Yield stability, reduced risk of crop failure | Mean-Variance analysis | As above, but price and yields are stochastic variables. Crop yields not highly correlated. |
Increase in nutrient accumulation in soil resulting in fertilizer savings for subsequent seasons | Production input method | Estimates are available in the literature for N build-up and release. Amount of nitrogen released to subsequent crops multiplied by the value of N in fertiliser. |
Reduction in pest and diseases infestation thus cost savings for pesticide use | Production input method | Amount of reduction in pesticides multiplied by respective prices. |
Improvement in soil quality | Hedonic analysis of land price OR Production input method for calculating the Annual Value of Nutrients Supplied by soil organic matter (SOM). | Here the assumption is that improved soil quality is expressed in land prices. OR Estimates are available in the literature for nutrient build-up and release as SOM gradually breaks down. As above (for N), but for all nutrients: nitrogen, phosphorus, potassium, sulphur, and carbon. |
Climate regulation Increased biodiversity (crop species richness, habitat for above and below ground microorganisms) | Contingent valuation, choice experiments | The assumption is that the public understands the relationship between improved agricultural practices such as intercropping and environmental benefits. |
Water quality improvement (due to reduced soil erosion, reduced leaching etc.) | Contingent valuation, choice experiments | As above. |
Income stability | A method of stochastic dominance called stochastic efficiency with respect to a function (SERF). | The SERF method allows a non-biased comparison of risk and return trade-offs with reasonable assumptions about how a farmer might value them. |
Objective | What to Measure? | How to Measure? | Decision Criteria |
---|---|---|---|
Reduce or spare land compared to the current yield from monocultures | Partial land equivalent ratios with the assumption of equal value and equal areas and densities. | LER > 1 indicates intercropping advantage. | |
Maximize production per hectare (yield) accounting for enterprise mix ratio | Total yield from alternative cropping systems. | YR > 1 indicates intercropping advantage. | |
Maximize expected gross income per hectare | Total value of production from alternative cropping systems. | VR > 1 indicates intercropping advantage. | |
Maximize expected net income (profits) per hectare | Net income from alternative cropping systems. Net income is income from the sales of crops, less variable costs (i.e., the activity gross margin or GM). | Net Gross Margin (NetGM) = GMc – GMm GMc = GMm = | NetGM > 0 indicates intercropping advantage. PR > 1 indicates intercropping advantage. |
Maximise risk-adjusted net income (profit) per hectare. | Certainty Equivalents derived from cumulative distribution functions (CDFs) of the NetGM for a set of risky intercropping systems. Variability in the NetGM may be due to production risk and/or price risk. Useful when statistical dominance techniques are insufficiently discriminating or when a single figure is required for spatial mapping. | The Certainty Equivalent (CE) is evaluated separately for each risky intercropping system under consideration from the inverse of the decision-maker’s utility function with respect to wealth (. (exponential form) The exact shape of the utility function is unknown. In other words, the decision maker’s exact level of risk aversion is unspecified, so is evaluated for a range of risk attitudes. Decision-maker’s absolute risk aversion coefficient (unknown constant) Decision-maker’s relative risk aversion coefficient (thought to range between zero for risk-neutral and four for extremely risk-averse). A sample of equally likely values of net income (wis) is obtained from the CDF of the NetGM. | Ranks a set of risky intercropping systems, highest to lowest, for a range of risk attitudes. |
Mix ratio (Z1c:Z2c) | Y1m (t/ha) | Y2m (t/ha) | Y1c (t/ha) | Y2c (t/ha) | P1 ($/t) | P2 ($/t) | C1 ($/ha) | C2 ($/ha) | C3 ($/ha) | LER (ha/ha) | YR (kg/ha)/(kg/ha) | VR ($/ha)/($/ha) | NetGM ($/ha) | Absolute GM ($/ha) | PR ($/ha)/($/ha) |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
100:0 | 3.0 | 1.0 | 3.0 | 0 | 300 | 0 | 530 | 0 | 0 | 1.00 | 1.00 | 1.00 | 0 | 370 | 1.00 |
0:100 | 3.0 | 1.0 | 0 | 1.0 | 0 | 570 | 0 | 560 | 0 | 1.00 | 1.00 | 1.00 | 0 | 10 | 1.00 |
25:75 | 3.0 | 1.0 | 1.2 | 0.8 | 300 | 570 | 0 | 0 | 620 | 1.20 | 1.33 | 1.25 | 96 | 196 | 1.96 |
25:75 | 3.0 | 1.0 | 1.8 | 0.4 | 300 | 570 | 0 | 0 | 620 | 1.00 | 1.47 | 1.18 | 48 | 148 | 1.48 |
25:75 | 3.0 | 1.0 | 1.8 | 0.2 | 300 | 570 | 0 | 0 | 620 | 0.80 | 1.33 | 1.00 | -66 | 34 | 0.34 |
50:50 | 3.0 | 1.0 | 1.2 | 0.8 | 300 | 570 | 0 | 0 | 550 | 1.20 | 1.00 | 1.11 | 76 | 266 | 1.40 |
50:50 | 3.0 | 1.0 | 1.8 | 0.4 | 300 | 570 | 0 | 0 | 550 | 1.00 | 1.10 | 1.04 | 28 | 218 | 1.15 |
50:50 | 3.0 | 1.0 | 1.8 | 0.2 | 300 | 570 | 0 | 0 | 550 | 0.80 | 1.00 | 0.89 | -86 | 104 | 0.55 |
75:25 | 3.0 | 1.0 | 1.2 | 0.8 | 300 | 570 | 0 | 0 | 630 | 1.20 | 0.80 | 1.00 | -94 | 186 | 0.66 |
75:25 | 3.0 | 1.0 | 1.8 | 0.4 | 300 | 570 | 0 | 0 | 630 | 1.00 | 0.88 | 0.94 | -142 | 138 | 0.49 |
75:25 | 3.0 | 1.0 | 1.8 | 0.2 | 300 | 570 | 0 | 0 | 630 | 0.80 | 0.80 | 0.80 | -256 | 24 | 0.09 |
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Khanal, U.; Stott, K.J.; Armstrong, R.; Nuttall, J.G.; Henry, F.; Christy, B.P.; Mitchell, M.; Riffkin, P.A.; Wallace, A.J.; McCaskill, M.; et al. Intercropping—Evaluating the Advantages to Broadacre Systems. Agriculture 2021, 11, 453. https://doi.org/10.3390/agriculture11050453
Khanal U, Stott KJ, Armstrong R, Nuttall JG, Henry F, Christy BP, Mitchell M, Riffkin PA, Wallace AJ, McCaskill M, et al. Intercropping—Evaluating the Advantages to Broadacre Systems. Agriculture. 2021; 11(5):453. https://doi.org/10.3390/agriculture11050453
Chicago/Turabian StyleKhanal, Uttam, Kerry J. Stott, Roger Armstrong, James G. Nuttall, Frank Henry, Brendan P. Christy, Meredith Mitchell, Penny A. Riffkin, Ashley J. Wallace, Malcolm McCaskill, and et al. 2021. "Intercropping—Evaluating the Advantages to Broadacre Systems" Agriculture 11, no. 5: 453. https://doi.org/10.3390/agriculture11050453