The paper presents PyPlants, an open-source object-oriented Python package, which includes plant models validated and published in the scientific literature, useful for predicting phenology and diseases. These tools are essential in agriculture, as they help to predict growth phases and disease risk, reducing the probability of crop loss. As of today, these models are rarely distributed as software; the few available implementations are developed in different programming languages and provide limited interoperability. PyPlants addresses these limitations by offering a common software interface and a simple framework to facilitate model adoption, for both researchers and developers. Moreover, users can take advantage of this tool to benchmark and consequently share new models. The current release includes eleven different models, ten for diseases and one for phenology, but it is ready to include many more in the near future.

PyPlants: an open-source python package implementing disease and phenological models for plants / Colucci, G.P., Salotti, I., Battilani, P., Trinchero, D.. - In: SOFTWAREX. - ISSN 2352-7110. - ELETTRONICO. - 36:(2026), pp. 1-4. [10.1016/j.softx.2026.103062]

PyPlants: an open-source python package implementing disease and phenological models for plants

Giovanni Paolo Colucci;Daniele Trinchero
2026

Abstract

The paper presents PyPlants, an open-source object-oriented Python package, which includes plant models validated and published in the scientific literature, useful for predicting phenology and diseases. These tools are essential in agriculture, as they help to predict growth phases and disease risk, reducing the probability of crop loss. As of today, these models are rarely distributed as software; the few available implementations are developed in different programming languages and provide limited interoperability. PyPlants addresses these limitations by offering a common software interface and a simple framework to facilitate model adoption, for both researchers and developers. Moreover, users can take advantage of this tool to benchmark and consequently share new models. The current release includes eleven different models, ten for diseases and one for phenology, but it is ready to include many more in the near future.
2026
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/3015967