English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONS
  This item is discarded!Release HistoryDetailsSummary

Discarded

Journal Article

Optimizing crop rotations via Parrondo’s paradox for sustainable agriculture

MPS-Authors
/persons/resource/persons56693

Gokhale,  Chaitanya S.
Research Group Theoretical Models of Eco-Evolutionary Dynamics, Department Evolutionary Theory, Max Planck Institute for Evolutionary Biology, Max Planck Society;

/persons/resource/persons269279

Sharma,  Nikhil
Department Evolutionary Theory, Max Planck Institute for Evolutionary Biology, Max Planck Society;
IMPRS for Evolutionary Biology, Max Planck Institute for Evolutionary Biology, Max Planck Society;

External Resource

(No access)

Fulltext (restricted access)
There are currently no full texts shared for your IP range.
Fulltext (public)
There are no public fulltexts stored in PuRe
Supplementary Material (public)
There is no public supplementary material available
Citation

Gokhale, C. S., & Sharma, N. (2023). Optimizing crop rotations via Parrondo’s paradox for sustainable agriculture. Royal Society Open Science, 10(5): 221401. doi:10.21203/rs.3.rs-1141107/v1.


Abstract
Crop rotation, a sustainable agricultural technique, has been at humanity’s disposal since time immemorial and is practised globally. Switching between cover crops and cash crops helps avoid the adverse effects of intensive farming. Determining the optimum cash-cover rotation schedule for maximizing yield has been tackled on multiple fronts by agricultural scientists, economists, biologists and computer scientists, to name a few. However, considering the uncertainty due to diseases, pests, droughts, floods and impending effects of climate change is essential when designing rotation strategies. Analysing this time-tested technique of crop rotations with a new lens of Parrondo’s paradox allows us to optimally use the rotation technique in synchrony with uncertainty. While previous approaches are reactive to the diversity of crop types and environmental uncertainties, we make use of the said uncertainties to enhance crop rotation schedules. We calculate optimum switching probabilities in a randomized cropping sequence and suggest optimum deterministic sequences and judicious use of fertilizers. Our methods demonstrate strategies to enhance crop yield and the eventual profit margins for farmers. Conforming to translational biology, we extend Parrondo’s paradox, where two losing situations can be combined eventually into a winning scenario, to agriculture.