Global warming leads to the concurrence of a number of abiotic and biotic stresses, thus affecting agricultural productivity. Occurrence of abiotic stresses can alter plant–pest interactions by enhancing host plant susceptibility to pathogenic organisms, insects, and by reducing competitive ability with weeds. On the contrary, some pests may alter plant response to abiotic stress factors. Therefore, systematic studies are pivotal to understand the effect of concurrent abiotic and biotic stress conditions on crop productivity. However, to date, a collective database on the occurrence of various stress combinations in agriculturally prominent areas is not available. This review attempts to assemble published information on this topic, with a particular focus on the impact of combined drought and pathogen stresses on crop productivity. In doing so, this review highlights some agriculturally important morpho-physiological traits that can be utilized to identify genotypes with combined stress tolerance. In addition, this review outlines potential role of recent genomic tools in deciphering combined stress tolerance in plants. This review will, therefore, be helpful for agronomists and field pathologists in assessing the impact of the interactions between drought and plant-pathogens on crop performance. Further, the review will be helpful for physiologists and molecular biologists to design agronomically relevant strategies for the development of broad spectrum stress tolerant crops.

Drought stress and pathogen infection simultaneously occur in the field. In this study, the interaction of these two stresses with chickpea, their individual and combined effect and the net impact on plant growth and yield traits were systematically assessed under field and confined pot experiments. The field experiments were conducted for four consecutive years from 2014–15 to 2017–18 at different locations of India. Different irrigation regimes were maintained to impose mild to severe drought stress, and natural incidence of the pathogen was considered as pathogen stress. We observed an increased incidence of fungal diseases namely, dry root rot (DRR) caused by Rhizoctonia bataticola , black root rot (BRR) caused by Fusarium solani under severe drought stress compared to well-irrigated field condition. Similar to field experiments, pot experiments also showed severe disease symptoms of DRR and BRR in the presence of drought compared to pathogen only stress. Overall, the results from this study not only showed the impact of combined drought and DRR stress but also provided systematic data, first of its kind, for the use of researchers.

Drought plays a central role in increasing the incidence and severity of dry root rot (DRR) disease in chickpea. This is an economically devastating disease, compromising chickpea yields particularly severely in recent years due to erratic rainfall patterns. Macrophomina phaseolina (formerly Rhizoctonia bataticola) is the causal agent of DRR disease in the chickpea plant. The infection pattern in chickpea roots under well-watered conditions and drought stress are poorly understood at present. This study provides detailed disease symptomatology and the characteristics of DRR fungus at morphological and molecular levels. Using microscopy techniques, the infection pattern of DRR fungus in susceptible chickpea roots was investigated under well-watered and drought stress conditions. Our observations suggested that drought stress intensifies the progression of already ongoing infection by weakening the endodermal barrier and overall defense. Transcriptomic analysis suggested that the plant’s innate immune defense program is downregulated in infected roots when subjected to drought stress. Further, genes involved in hormonal regulation are differentially expressed under drought stress. These findings provide hints in terms of potential chickpea genes to target in crop improvement programs to develop climate change-resilient cultivars.

Rhizoctonia bataticola causes dry root rot (DRR), a devastating disease in chickpea (Cicer arietinum). DRR incidence increases under water deficit stress and high temperature. However, the roles of other edaphic and environmental factors remain unclear. Here, we performed an artificial neural network (ANN)-based prediction of DRR incidence considering DRR incidence data from previous reports and weather factors. ANN-based prediction using the backpropagation algorithm showed that the combination of total rainfall from November to January of the chickpea-growing season and average maximum temperature of the months October and November is crucial in determining DRR occurrence in chickpea fields. The prediction accuracy of DRR incidence was 84.6% with the validation dataset. Field trials at seven different locations in India with combination of low soil moisture and pathogen stress treatments confirmed the impact of low soil moisture on DRR incidence under different agroclimatic zones and helped in determining the correlation of soil factors with DRR incidence. Soil phosphorus, potassium, organic carbon, and clay content were positively correlated with DRR incidence, while soil silt content was negatively correlated. Our results establish the role of edaphic and other weather factors in chickpea DRR disease incidence. Our ANN-based model will allow the location-specific prediction of DRR incidence, enabling efficient decision-making in chickpea cultivation to minimize yield loss.

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