The rational control of harmful organisms for plants (pests) forms the basis of the integrated pest management (IPM), and is fundamental for ensuring agricultural productivity while maintaining economic and environmental sustainability. The high level of complexity of the decision processes linked to IPM requires careful evaluations, both economic and environmental, considering benefits and costs associated with a management action. Plant protection models and other decision tools (DTs) have assumed a key role in supporting decision-making process in pest management. The advantages of using DTs in IPM are linked to their capacity to process and analyze complex information and to provide outputs supporting the decision-making process. Nowadays, several DTs have been developed, tackling different issues, and have been applied in different climatic conditions and agricultural contexts. However, their use in crop management is restricted to only certain areas and/or to a limited group of users. In this paper, we review the current state-of-the-art related to DTs for IPM, investigate the main modelling approaches used, and the different fields of application. We also identify key drivers influencing their adoption and provide a set of critical success factors to guide the development and facilitate the adoption of DTs in crop protection.

This review gives a perspective of selected advances made since the middle of the 20th century in plant disease modeling, and the associated increase in the number of models published during that time frame. This progress can be mainly attributed to advances in (i) sensors and automatic environmental data collection technology, (ii) instrumentation and methods for studying botanical epidemiology, and (iii) data analytics and computer science. We review the evolution of techniques for developing data-based (empirical) models and process-based (mechanistic) models using the wheat rusts as a case study. We also describe the increased importance of knowledge about biological processes for plant disease modeling by using apple scab as a second case study. For both wheat rusts and apple scab, we describe how the models have evolved over the last 50 years by considering certain milestones that have been achieved in disease modeling. Finally, we describe how plant disease models are used as part of a multi-modeling approach to develop decision-making tools in the application of integrated pest management.

Dynamics of ascocarp development, ascospore maturation, and dispersal in Erysiphe necator were studied over a 4-year period, from the time of ascocarp formation to the end of the ascosporic season at the end of June in the following spring. Naturally dispersed chasmothecia were collected from mid-August to late November (when leaf fall was complete); the different collections were used to form three to five cohorts of chasmothecia per year, with each cohort containing ascocarps formed in different periods. Chasmothecia were exposed to natural conditions in a vineyard and periodically sampled. Ascocarps were categorized as containing mature or immature ascospores, or as empty; mature ascospores inside chasmothecia were enumerated starting from late February. Ascospore discharge was determined using silicone-coated slides that were placed 3 to 4 cm from sections of the vine trunk holding the chasmothecia. Before complete leaf fall, 34% of the chasmothecia had mature ascospores, 48% had immature ascospores, and 18% were empty; in the same period, the trapped ascospores represented 56% of the total ascospores trapped in an ascosporic season (i.e., from late summer until the next spring or early summer). The number of viable chasmothecia diminished over time; 11 and 5% of chasmothecia had mature ascospores between complete leaf fall and bud break and after bud break, respectively. These ascocarps discharged ≈2 and 42% of the total ascospores, respectively. All the ascocarp cohorts released ascospores in autumn, survived the winter, and discharged viable ascospores in spring; neither ascospore numbers nor their pattern of temporal release was influenced by the time when chasmothecia were collected and exposed in the vineyard. Abundance of mature ascospores in chasmothecia was expressed as a function of degree-days (DD) (base 10°C) accumulated before and after bud break through a Gompertz equation (R² = 0.92). Based on this equation, 90% of the ascospores were mature when 153 DD (confidence interval, 100 to 210 DD) had accumulated after bud break. Most ascospores were trapped in periods with >2 mm of rain; however, a few ascospores were airborne with <2 mm of rain and, occasionally, in wet periods of ≥3.5 h not initiated by rain.