Agriculture is under considerable pressure to improve productivity in the face of changing environmental circumstances and a continuing rise in the earth’s human population. Plant diseases induced by pathogenic microbes cause huge annual losses that are estimated to range between 13 (Oerke, 2006) and 22% among the world’s most important food species alone, i.e., wheat, corn, soybean, potato, rice (Savary et al., 2019). This toll greatly threatens the sustainable supply of quality food, adding to concerns around food security, especially given the potential for ongoing climate change to generate conditions that may foster the geographic spread and local increase of diseases (Burdon and Zhan, 2020).

Plant diseases in agricultural ecosystems are mainly controlled by using host resistance and agrochemicals (Borrelli et al., 2018; Burdon et al., 2020; Burdon and Zhan, 2020). In the gene-for-gene system involving an effector and receptor interaction governed by major gene inheritance, resistance is often ephemeral due to rapid evolution of pathogen infectivity (Barrett et al., 2009). In contrast, quantitative resistance is polygenic and therefore more durable, but its application in disease management is threatened by the emergence of pathogen populations with higher aggressiveness and tolerance to environmental stresses (Yang et al., 2013; Zhan et al., 2015; Burdon et al., 2016). When host resistance is not available, agrochemicals become another major control option and have been widely used to produce immediate mitigation effects on pathogens either by killing them or constraining their growth and reproduction. However, this management approach is no panacea because chemicals often have detrimental effects on non-target organisms (Belsky and Joshi, 2020; Alengebawy et al., 2021) and are subject to erosion of their efficacy (Ishii and Holloman, 2015).

With increasing concern over the need for natural resource conservation (including resistance genes) and environmental wellbeing, the use of eco-evolutionary approaches to control plant diseases in agricultural ecosystems has received renewed attention in recent years (Zhan et al., 2014, 2015; He et al., 2016). One eco-evolutionary approach is to use biodiversity that, in its simplest form, utilizes mixtures of genotypes of the same species. In term of plant disease management, theoretical and empirical data suggest that increased biodiversity not only reduce plant disease epidemics in the short term but also reduce pathogen evolution in the longer term (Mundt, 2002; Zhan et al., 2002; Keesing et al., 2010; Sommerhalder et al., 2011; Burdon et al., 2016; Rimbaud et al., 2021). In addition to the suppressing effects of diversifying selection on the evolution of pathogen infectivity (Marshall et al., 2009), and of the inoculum reduction consequences caused by physical barriers that hamper pathogen dispersal, increasing biodiversity may generate indirect effects that are favourable for host immunity development but suboptimal for the survival, reproduction and transmission of pathogens (Eisenhauer et al., 2018).

Although the potential benefits of biodiversity have been identified for many decades, crop diversification has gradually reduced due to agricultural (de Lima et al., 2020) intensification and mechanization approaches that require functional uniformity of agronomic traits. However, this trend can be reversed in several ways through spatial and temporal deployment of crops by rotation, intercropping, or the use of carefully structured varietal mixtures (Kovács-Hostyánszki et al., 2017). Among these options, varietal mixtures composed of component lines with very similar agronomic traits but different genetic backgrounds and/or functional traits could be the best immediate option of applying biodiversity to control plant diseases (Zhu et al., 2000). Varietal mixtures can often be relatively easily adopted and implemented by both industrial and smallholder farmers. In contrast, other types of crop diversification such as intercropping, are often faced with agronomic, environmental, financial and other practical problems related to planting, harvesting and marketing as well as additional investments in new machines and knowledge required for the cultivation of the alternative crops (Wuest et al., 2021). The availability of technology to breed crop varieties with similar agronomic characteristics such as plant height, maturity and marketing quality but differing in other functional traits increases the potential to use varietal mixtures in sustainable commercial production (Zhan et al., 2015).

However, knowledge of the ways in which in-crop diversification can contribute to the control of plant diseases is still incomplete. For example, how much of the disease reduction in the mixtures is attributable to genetic diversity per se rather than to the presence of identifiable resistance genes is unclear (Schuldt et al., 2019; Rohr et al., 2020). Similarly, potential background effects of component varieties on disease reduction are yet to be clarified, as is the contribution of interactions among functional traits in the component varieties. To optimize the benefits of using in-crop biodiversity in controlling plant disease further detailed experimentation is required.

In this study, we used the potato-Phytophthora infestans interaction as a model system to address some of the key remaining questions associated with the contribution of in-crop diversification to plant disease management. Phytophthora infestans is the causal agent of potato and tomato late blights and one of the major factors limiting sustainable potato production globally. The pathogen was responsible for the Irish famine in 1840s and is still one of the main diseases in agriculture (Dean et al., 2012). It can cause up to 80% yield loss with the direct globally economic cost estimated to be >8 billion US dollars annually (Haverkort et al., 2009). In addition, billions of US dollars are spent annually on control practices including plant breeding, clean “seed” production and fungicide sprays. Previously, we combined field experiments and laboratory analyses to understand how genetic diversity in potato host populations affects potato yield, epidemics of late blight disease, the evolution of P. infestans, and soil fertility (Yang et al., 2019, 2021). We found that increasing genetic diversity through varietal mixtures increased potato yield and its stability, reduced late blight disease, increased microbial diversity and nutrition availability in the rhizosphere, and reduced fungicide resistance, aggressiveness, and the evolutionary rate of the pathogen. Here, we reanalyse some of these published data together with additional data generated from a new experiment. Our aim is to understand the interaction of genetic diversity with other functional traits such as host resistance and how this interaction affects disease epidemics. Such information is important in optimizing the effectiveness of plant disease management through the rational deployment of available varieties.

The specific objectives of the current study were to:

Analysis of variance revealed that the number of varieties, level of host resistance, DHR, and varietal proportion in the mixtures all had a significant impact on the total late blight and/or PDR (P < 0.01). Further assessment using partial correlation analysis indicated that PDR increased as the number of varieties in the mixtures increased (Figure 1) with the logarithmic model outperforming the linear model (Figure 1) as indicated by the AIC test. In line with predictions of the better fitting logarithmic model, PDR increased more rapidly as the first few varieties were added relative to levels predicted under the linear model. As the number of varieties continued to increase, PDR started to slowly flatten out (Figure 1). Although the partial correlation analysis also pointed to a linear association between PDR and the level of host resistance, this effect was caused by the interaction between host resistance and genetic diversity as shown by the multiple regression analysis (Table 2).

When data from the two-component mixtures in Experiment 1 was analysed separately, PDR increased linearly as DHR increased, but this association was only marginally significant (Figure 2A). The association became highly significant when data points were increased by considering late blight and host resistance according to each replicate, location, and/or year (Figure 2B; Supplementary Figure 1). Multiple regression analysis from this part of the data also indicated that host resistance did not affect PDR (Table 2).

In Experiment 2, all two-variety mixtures reduced late blight disease relative to the mean of pure stands regardless of host resistant level and DHR (Figures 3, 4). An average of 10.2% disease reduction with a mode of 14.3% (expected maximum reduction) was observed in Group S in which the average AUDPC in the two varieties when they were grown in pure stands was 4,337 (lower host resistance). In contrast, only an average of 5.7% disease reduction, with a mode of 7.0%, was found in Group MR in which the average AUDPC of the two varieties when they were planted in pure stands was 1,547 (higher host resistance, Table 3). Both the observed PDR and its expected maximum (mode) in the Group S were significantly higher than those in the Group MR. Both ODS and PDR fitted quadratic distributions well (Figures 3, 4). In Group MR where the level of resistance in the two varieties was the same, the mode of the quadratic distribution was found to be located at the point where two varieties were planted in the proportions of 51:49 (Figure 3A; Table 3), indicating that the least amount of late blight disease would occur if the two varieties were planted in equal proportions. In contrast, in Group S where the AUDPC ratio of varieties was 56:44, the mode of the quadratic distribution was located at the point where two varieties were planted in a 69:31 ratio (Figure 3A; Table 3), indicating the least disease occurrence would be achieved only when the more susceptible variety was planted in a lower proportion. However, in term of PDR, the best results were achieved by planting more susceptible varieties (∼60%) in both situations (Figure 4).

Increasing host diversity by growing different genotypes of the same species together has been proposed as an environmentally friendly and economically justifiable approach to plant disease management, and many studies have been conducted to understand the mechanisms behind this strategy. However, results from empirical studies are not always consistent. While some have shown that diversity enrichment in host populations makes a positive contribution to crop yield and disease management, other studies have failed to achieve the expectation (Ganz and Ebert, 2010; Gibson and Nguyen, 2021). This inconsistency suggests that the efficacy of using in-crop diversity to reduce disease may be a variety-dependent phenomenon, possibly attributable to eco-evolutionary differences associated with functional characteristics of varieties. Indeed, it is hypothesised that varietal mixtures are only effective in delivering disease reductions when there is DHR among varietal components (Xu, 2012). Our results partially falsify this hypothesis. We found that mixing two varieties with the same level of host resistance also significantly reduced the amount of disease in fields although PDR was more apparent as DHR between the varietal components increased (Figures 2–4). However, the level of host resistance per se does not have a direct impact on late blight epidemics. Rather, its contribution to PDR in the mixture is indirect through its interaction with other functional traits such as host diversity and DHR among varietal components. These phenomena are likely caused by fitness penalties that occur when allo-deposition events involving cross-transmission of pathogens from different host varieties result in reductions of infection or lesion development (Marshall et al., 2009). As DHR between the two host varieties in the mixture increases, this cross-transmission fitness penalty also increases, leading to greater PDR. These results suggest that in practices involving only two-variety mixtures, we should aim to maximize DHR to increase disease reduction efficiency. For example, if there are two groups of varieties with one group being disease resistance while another group is disease susceptible, we should mix varieties from different rather the same group to achieve best disease control. However, a two-component mixture approach is still effective in reducing disease epidemics even if there is no possibility of mixing varieties with sufficient DHR due to inappropriate combinations of other agronomical traits such as plant height, harvest time, yield, or consumer preference. These agronomical traits should be as identical as possible for both practical and marketing reasons, and should be of primary consideration in selecting varieties for mixtures.

In this study, we move beyond the traditional focus on two-component to multiple-component mixtures including up to six different varieties. This design allowed us to directly quantify the efficacy of using genetic diversity to control plant disease by conducting a correlation analysis between disease seen in the field and the number of varieties involved in the mixtures. We used two approaches to remove variety-dependent phenomena directly by creating potato populations in such a way that the contribution of the genetic background from individual varieties was equally weighted and indirectly by partitioning disease variance to different factors (Table 2). Similar to the previous result estimated from observed disease severity (Yang et al., 2019), our analysis indicates that PDR also increases in response to an increase in varietal number included in the mixtures even though this additional gain in disease control efficacy declines and eventually may asymptote to a constant maximum as further varieties are added (Figure 1). In addition to a fitness penalty associated with allo-deposition events (Schoeny et al., 2008), increasing travel distance of pathogens (Madden, 1997) and a diluting effect on inoculum density (Haas et al., 2011), other eco-evolutionary elements may also contribute to the observed result. For example, balanced uptake of fertilisers applied and diversified secretion of compounds required for mineral element release from soils by different host varieties increases nutrition availability and efficiency for healthy crops (Zak et al., 2003). Increasing genetic diversity of microbial communities in rhizosphere by host varietal diversification can serve both as a promoter of fossil element release and competitor to reduce the reproduction and transmission of pathogens (Lambers et al., 2009). These positive effects of biodiversity on host health and negative effects on pathogen survival and transmission create a suboptimal environment for disease epidemics in the short term and pathogen evolution in the long term. These ecological phenomena have been documented widely in both agricultural and natural ecosystems (Finckh et al., 2000; Loreau et al., 2001).

To maximise the effect of variety mixture on disease reduction, the proportion of different varieties in the mixture populations should be carefully adjusted (Garrett and Mundt, 1999). Our results indicate that the best disease reduction is not always associated with equal mixture of varietal components that provides the expected highest diversity in host populations (Nei, 1973). To achieve the lowest total disease severity (Figure 3), the relative abundance of the two varieties is roughly reflected by their DHR with a skewness toward the variety with the higher host resistance (Table 3). For example, if total disease reduction is the primary consideration and the ratio of host susceptibility in the higher and lower susceptible variety is 70:30, then the lowest total disease in the field occurs when the two varieties are planted at the ratio of 30:70. On the other hand, if there is a preference for the more susceptible variety due to its yield potential or quality, etc., it can be planted at greater than 50% in the mixture as indicated by the continuing increase in PDR as the proportion of more susceptible variety in the mixture increased (Figure 4). However, our results were only derived from two pairs of treatments generated from mixture of varieties with the same resistant level. It is not clear whether our observation is a specific case to our experiments or is the general phenomenon in the agricultural systems. Further research should be conducted with more pairs of mixtures including mixture of varieties among resistant groups to confirm this result.

In agriculture, crop varieties favoured by farmers are often associated with higher productivity or good quality but lower disease resistance (Vyska et al., 2016). Due to their susceptibility, these varieties have to be withdrawn from commercial use or rely on heavy application of agrichemicals to ensure necessary levels of productivity – a production strategy that is often associated with enhancing evolutionary changes in the pathogen, deleterious effects on the environment and increasing economic costs for growers and society as a whole (Lechenet et al., 2017; He et al., 2021; Wright et al., 2021). In developing countries where smallholder farmers lack the resources for extensive purchase of agrichemicals, these financial burdens are a particular concern. The breeding of replacement varieties with similar production potential, quality and consumer acceptance is time consuming and requires additional genetic and financial resources. Our research provides empirical guidance on how to effectively extend the useful life of crop varieties whose resistance has been overcome to ensure sustainable agricultural production without additional financial or environmental burdens. If many varieties are available for use, a complex mixture involved several varieties (≥5) should be considered to increase the efficacy of disease reduction. However, if the number of varieties available are limited, the simplest mixture of two varieties could also achieve the goal of disease reduction. In this case, choice should go to varieties with levels of host resistance that are as different as possible.

Our results indicate that mixing crop varieties can significantly reduce disease epidemics in the field, but planting varieties in equal proportion, as it is commonly practised, does not necessarily generate the best disease control. To achieve the best disease mitigation, growers should include as many varieties as possible in mixtures or, if only two component mixtures are possible, increase DHR (difference in host resistance) among those component varieties. In the latter case, the percentage representation of the component varieties should be carefully adjusted to reflect their DHR. The more susceptible variety should be less represented in the two-component mixtures if disease control is the primary consideration but can be planted at a higher proportion if the variety is preferred by farmers due to its quality or yield potential.

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Y-PW and Z-CP collected and analyzed data and wrote the manuscript. L-NY collected and analyzed data. JB and HF wrote the manuscript. Q-JS conceived the project and managed the field experiment. JZ conceived, designed and supervised the experiments analyzed the data, and wrote the manuscript. All authors reviewed the manuscript.

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.