Photosynthetic responses of oat to leaf blight disease caused by Pantoea agglomerans

Wang, Jianjun; Chen, Taixiang; Wei, Xuekai; Malik, Kamran; White, James F.; Li, Chunjie

doi:10.1007/s42161-022-01089-z

Cited by 6 publications

(3 citation statements)

References 53 publications

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“…It demonstrated that the response of A. sativa and A. nuda to BHB (Ps-c) is different, which is probably related to the disease resistance of different oat varieties. Similarly, our previous study on effects of Pantoea agglomerans infection on photosynthetic responses of A. sativa and A. nuda revealed that A. sativa had a stronger photosynthetic capacity than A. nuda under healthy and diseased conditions, and their responses to disease are also different (Wang et al, 2022).…”

Section: Discussionmentioning

confidence: 53%

Pseudomonas syringae pv. coronafaciens, causing a new bacterial halo blight disease on oat (Avena sativa L.) in China

Wang,

Zhang,

Chen

et al. 2024

Preprint

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Pseudomonas syringae pv. coronafaciens (Ps-c) is a pathogenic bacterium species that can be found in agricultural environments that causes diseases in plants. During a survey in 2019–2020 of different areas, bacterial halo blight (BHB) caused by Ps-c in oat (Avena sativa L.) was observed in many oat fields in Huan county, Gansu Province of China. Average leaf disease incidence was approximately 1 to 14%. The symptoms of BHB were mainly observed on leaves of oat and appeared as white to yellow streaks. After 20–30 d, the streaks became yellow necrotic lesions and spread to whole leaves, eventually causing leaves to wilt and decline. Symptomatic leaves of affected oats were collected from locations to investigate the etiology of BHB disease, and a group of 32 bacterial isolates (HK7) phenotypically similar was consistently isolated from the necrotic lesion margins in all samples. Pathogenicity tests of this group isolates by wounding and injection inoculations in greenhouse demonstrated that the symptoms induced by them on oat were similar to those observed in the field. HK7 isolates were identified as Ps-c based on Biolog Gen III MicroStation, morphological, physiological and biochemical characterization, 16S rRNA and gyrB gene sequence analysis, which compared with a reference strain (Ps-c ATCC 19608). Furthermore, Ps-c had a narrow host range and was host specific. After inoculation of Ps-c on A. sativa (B7) and A. nuda (B2) in greenhouse, effective tillers, plant height, flag-leaf length, flag-leaf width, fresh weight, dry weight, panicle length, grains per spike, reproductive branches number and thousand grains weight of infected oat were averagely decreased by 19.44%, 11.49%, 11.34%, 9.23%, 11.61%, 7.57%, 6.11%, 9.73%, 9.31% and 4.15% compared with that of healthy oat, respectively. Therefore, BHB (Ps-c) is a new bacterial disease on oat in China and has negative influences on plant growth, forage and grain yield of oat, and these negative effects are enhanced with the increase of disease severity.

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Section: Discussionmentioning

confidence: 53%

Pseudomonas syringae pv. coronafaciens, causing a new bacterial halo blight disease on oat (Avena sativa L.) in China

Wang,

Zhang,

Chen

et al. 2024

Preprint

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“…Wang et al 6 studied the alterations in leaf area, photosynthetic rate, stomatal conductance, transpiration rate of oat to understand the plant response towards leaf blight disease. Francesconi and Balestra 7 studied the changes in photosynthesis and stomatal conductance to describe wheat response for fusarium head blight disease.…”

Section: Introductionmentioning

confidence: 99%

Combining biophysical parameters with thermal and RGB indices using machine learning models for predicting yield in yellow rust affected wheat crop

Singh,

Krishnan,

Singh

et al. 2023

Sci Rep

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Evaluating crop health and forecasting yields in the early stages are crucial for effective crop and market management during periods of biotic stress for both farmers and policymakers. Field experiments were conducted during 2017–18 and 2018–19 with objective to evaluate the effect of yellow rust on various biophysical parameters of 24 wheat cultivars, with varying levels of resistance to yellow rust and to develop machine learning (ML) models with improved accuracy for predicting yield by integrating thermal and RGB indices with crucial plant biophysical parameters. Results revealed that as the level of rust increased, so did the canopy temperature and there was a significant decrease in crop photosynthesis, transpiration, stomatal conductance, leaf area index, membrane stability index, relative leaf water content, and normalized difference vegetation index due to rust, and the reductions were directly correlated with levels of rust severity. The yield reduction in moderate resistant, low resistant and susceptible cultivars as compared to resistant cultivars, varied from 15.9–16.9%, 28.6–34.4% and 59–61.1%, respectively. The ML models were able to provide relatively accurate early yield estimates, with the accuracy increasing as the harvest approached. The yield prediction performance of the different ML models varied with the stage of the crop growth. Based on the validation output of different ML models, Cubist, PLS, and SpikeSlab models were found to be effective in predicting the wheat yield at an early stage (55-60 days after sowing) of crop growth. The KNN, Cubist, SLR, RF, SpikeSlab, XGB, GPR and PLS models were proved to be more useful in predicting the crop yield at the middle stage (70 days after sowing) of the crop, while RF, SpikeSlab, KNN, Cubist, ELNET, GPR, SLR, XGB and MARS models were found good to predict the crop yield at late stage (80 days after sowing). The study quantified the impact of different levels of rust severity on crop biophysical parameters and demonstrated the usefulness of remote sensing and biophysical parameters data integration using machine-learning models for early yield prediction under biotically stressed conditions.

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“…Similarly, the nutritional qualities of oat, such as crude ash, crude protein, ether extract, soluble carbohydrate, calcium, phosphorus, digestible dry matter, dry matter intake and relative feed value, were decreased by LBD (P. agglomerans), but the content of crude ber, acid and neutral detergent ber was increased. It might be due to P. agglomerans reduced the photosynthetic e ciency of oat leaves, which affected the formation and accumulation of nutrients on oat plants based on the previous research results of LBD (P. agglomerans)(Wang et al, 2022c). There are differences in growth character, forage yield and feeding value between A. nuda and A. sativa, and their resistances to biotic and abiotic stress are also different because of differences in genetic and biological characteristics(Pisulewska et al, 2009;Ma et al, 2010;Sliková et al, 2010;Ta et al, 2010;Hu et al, 2012).Tao et al (…”

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confidence: 96%

Impact of bacterial leaf blight disease ( Pantoea agglomerans ) on forage yield and feeding value of oat

Wang,

Zhang,

Chen

et al. 2023

Preprint

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From 2018 to 2019, bacterial leaf blight disease (LBD) caused by Pantoea agglomerans was observed on the leaves of oat (Avena sativa L.) in Northwest China, and diseased oat often showed yellow-colored necrotic symptoms on the leaves. This is a new bacterial disease of oat in China. In this study, greenhouse experiments were conducted to explore the effect of LBD (P. agglomerans) on forage yield and feeding value of Avena sativa [Baiyan 2 (B2)] and A. nuda [Baiyan 7 (B7)]. The results revealed that effective tillers, plant height, flag-leaf length, flag-leaf width, fresh weight, dry weight, fresh-dry ratio, crude ash, crude protein, ether extract, soluble carbohydrate, calcium, phosphorus, digestible dry matter, dry matter intake and relative feed value of B2 and B7 were all significantly (P < 0.05) decreased by LBD. Hay yield of oat was reduced 1.38 to 23.48%, and relative feed value was decreased 1.01 to 26.24% by LBD. In contrast, crude fiber, acid detergent fiber, neutral detergent fiber and nitrogen free extract of B2 and B7 were significantly (P < 0.05) increased after inoculation of P. agglomerans. Moreover, B7 had a higher forage yield and relative feed value than B2 under inoculation and non-inoculation of P. agglomerans. LBD (P. agglomerans) has negative influences on growth, forage yield and feeding value of oat, and these negative effects are enhanced with increase of LBD severity.

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Photosynthetic responses of oat to leaf blight disease caused by Pantoea agglomerans

Cited by 6 publications

References 53 publications

Pseudomonas syringae pv. coronafaciens, causing a new bacterial halo blight disease on oat (Avena sativa L.) in China

Pseudomonas syringae pv. coronafaciens, causing a new bacterial halo blight disease on oat (Avena sativa L.) in China

Combining biophysical parameters with thermal and RGB indices using machine learning models for predicting yield in yellow rust affected wheat crop

Impact of bacterial leaf blight disease ( Pantoea agglomerans ) on forage yield and feeding value of oat

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