In vitro Methodology to Assess Quantitative Resistance in Plant-fungus Pathosystems

Abstract

Background: Quantitative resistance (QR) to fungal pathogens remains a primary focus of all major host breeding programs. Field screenings for resistant plants, although accurate and effective, demand significant time and a sizable workforce to accomplish. Moreover, weather conditions in the field may not always be favorable for uniform disease spread, which eventually may lead to failure of the overall experiment. The development of a more efficient and reliable bioassay to screen for resistance to fungal pathogens would be advantageous for any breeding program working on disease resistance, however, only if it correlates with field screening trials. Objective: The objective of this review is to combine novel findings related to rapid screening methods to evaluate QR, which are needed to accelerate the progress in developing fungal disease resistance in cultivars. Insights into the in vitro quantitative components of the host–pathogen interaction, factors affecting in vitro evaluation in young plant materials as well as molecular pathways for the association between the in vitro and adult plant responses to fungal infection are also reviewed. Conclusion: An in vitro method was found to be efficient and successful in terms of inoculum volume, plant samples, and working space. The main advantage of this method is its predictive ability of adult plant disease. In addition, it gives reproducible results and was found to be simple and reliable method. The in vitro assay allows rapid and early determination of resistance/susceptibility to fungal pathogens, which can be incorporated into a breeding program for identifying resistant plants.

Hyperspectral imaging for quantifying Magnaporthe oryzae sporulation on rice genotypes

“…Understanding and accounting for variations in the relation between mycelial mass and conidia production are essential for refining the quantification methods of fungal sporulation. The number of conidiophores per unit of area reflects the density of conidia produced by the pathogen, while the area of sporulation indicates the spatial extent of spore production on the leaf surface [20]. Incorporating information from both parameters, the AUDS approach allows for a more precise evaluation of the total number of conidia per blast lesion.…”

“…While visual assessment of disease severity is a common method for selecting blastresistant rice varieties in the field, it may not provide detailed information about the underlying mechanisms of partial blast resistance [14]. It is essential to estimate the contribution of each component of partial resistance to disease development followed by selection for a single component [15,20]. In the case of partial resistance to leaf blast in rice, the sporulating of M. oryzae is an important parameter.…”

Adaptation of Fusarium Species causing Head Blight to Quantitative Resistance in Wheat: Field Evidence for Increased Aggressiveness in a New Pathogen Population

“…The use of plant genetic resistance in agro-systems offers an interesting alternative to disease control methods based on the use of chemicals (Mundt, 2014;Sakr, 2023), but it also has a considerable effect on the evolutionary pathogen dynamics (McDonald and Linde, 2002) rendering resistance lacks durability due to the rapid pathogen evolution (Simmonds, 1991;Dangl and Jones, 2001). In the phytopathology literature, two extreme resistance categories for the resistance have historically been recognized (Parlevliet, 2002).…”

“…The mechanisms of the rapid adaptation of the pathogen frequently resulting in the breakdown of major resistance genes have already been studied in details (Mundt, 2014). Quantitative resistance associated with the presence of quantitative trait loci, QTLs, does not confer absolute protection (Simmonds, 1991), but is considered to be either be specific to some pathogen isolates or be effective against all known isolates of the pathogen (Cowger and Brown, 2019;Sakr, 2023). Over several generations, quantitative resistance can select for isolates with an increased rate of quantitative component of pathogenicity, i.e., aggressiveness which is dependent on the host, the pathogen and the interactions between them (McDonald and Linde, 2002), leading to erosion of the resistance (Mundt, 2014).…”

“…However, QTLs overcome by a slow pathogen adaptation is poorly understood by contrast to qualitative resistance broken by a swift process in pathogens (Parlevliet, 2002), which make them difficult to predict their durability (Mundt, 2014). Alternations in the pathogen population may include either augmented aggressiveness in general or a variation in specificity with higher aggressiveness on cultivars with a particular quantitative resistance gene (Cowger and Brown, 2019;Sakr, 2023). Fusarium head blight (FHB) is one of the most destructive diseases of bread wheat (Triticum aestivum) and durum wheat (T. durum) and other small-grain cereals (i.e., barley, oat, rye and triticale) on a global scale (Parry et al, 1995).…”