The study was conducted with 75 tomato entries at the farm of Olericulture Division, Horticulture Research Centre (HRC), Bangladesh Agricultural Research Institute (BARI), Gazipur, Bangladesh during the winter season ...The study was conducted with 75 tomato entries at the farm of Olericulture Division, Horticulture Research Centre (HRC), Bangladesh Agricultural Research Institute (BARI), Gazipur, Bangladesh during the winter season of 2020-21 to evaluate insect and disease reaction. Among the various insect and diseases of tomatoes, the late blight, TYLCV, bacterial wilt infection and leaf miner, fruit borer infestation are most common in Bangladesh. The TYLCV infection was observed 0% to 27% infection, while 47 entries showed zero percent infection. The range of bacterial wilt infection was 0% to 10% and zero percent infection was observed in 62 entries. In case of leaf miner infestation and fruit borer infestation, the range was 0% to 43% and 0% to 10%, respectively. Considering tolerance to late blight, TYLCV, bacterial wilt infection and leaf miner, fruit borer infestation, fruit size, fruit shape, plant growth nature, cluster nature of fruit, type of fruit ten entries AVTO 1010, AVTO 1706, AVTO 1713, AVTO 1829, AVTO 1909, AVTO 1911, AVTO 1915, AVTO 1921, AVTO 1954 and SLA 011 were found zero percent late blight, TYLCV, bacterial wilt infection and leaf miner, fruit borer infestation. So, these ten entries can be selected for disease and insect tolerant tomato varieties development as well as developing disease and insect tolerant hybrid tomato varieties.展开更多
Soil-borne plant diseases cause major economic losses globally.This is partly because their epidemiology is difficult to predict in agricultural fields,where multiple environmental factors could determine disease outc...Soil-borne plant diseases cause major economic losses globally.This is partly because their epidemiology is difficult to predict in agricultural fields,where multiple environmental factors could determine disease outcomes.Here we used a combination of field sampling and direct experimentation to identify key abiotic and biotic soil properties that can predict the occurrence of bacterial wilt caused by pathogenic Ralstonia solanacearum.By analyzing 139 tomato rhizosphere soils samples isolated from six provinces in China,we first show a clear link between soil properties,pathogen density and plant health.Specifically,disease outcomes were positively associated with soil moisture,bacterial abundance and bacterial community composition.Based on soil properties alone,random forest machine learning algorithm could predict disease outcomes correctly in 75%of cases with soil moisture being the most significant predictor.The importance of soil moisture was validated causally in a controlled greenhouse experiment,where the highest disease incidence was observed at 60%of maximum water holding capacity.Together,our results show that local soil properties can predict disease occurrence across a wider agricultural landscape,and that management of soil moisture could potentially offer a straightforward method for reducing crop losses to R.solanacearum.展开更多
文摘The study was conducted with 75 tomato entries at the farm of Olericulture Division, Horticulture Research Centre (HRC), Bangladesh Agricultural Research Institute (BARI), Gazipur, Bangladesh during the winter season of 2020-21 to evaluate insect and disease reaction. Among the various insect and diseases of tomatoes, the late blight, TYLCV, bacterial wilt infection and leaf miner, fruit borer infestation are most common in Bangladesh. The TYLCV infection was observed 0% to 27% infection, while 47 entries showed zero percent infection. The range of bacterial wilt infection was 0% to 10% and zero percent infection was observed in 62 entries. In case of leaf miner infestation and fruit borer infestation, the range was 0% to 43% and 0% to 10%, respectively. Considering tolerance to late blight, TYLCV, bacterial wilt infection and leaf miner, fruit borer infestation, fruit size, fruit shape, plant growth nature, cluster nature of fruit, type of fruit ten entries AVTO 1010, AVTO 1706, AVTO 1713, AVTO 1829, AVTO 1909, AVTO 1911, AVTO 1915, AVTO 1921, AVTO 1954 and SLA 011 were found zero percent late blight, TYLCV, bacterial wilt infection and leaf miner, fruit borer infestation. So, these ten entries can be selected for disease and insect tolerant tomato varieties development as well as developing disease and insect tolerant hybrid tomato varieties.
基金the National Natural Science Foundation of China(41922053,42090062,31972504 and 42007038)the Fundamental Research Funds for the Central Universities(KJQN202116-KJQN202117,KYXK202009-KYXK202012)+3 种基金the Natural Science Foundation of Jiangsu Province(BK20190518,BK20180527 and BK20200533)the China Postdoctoral Science Foundation(2019M651848)the Bioinformatics Center of Nanjing Agricultural University.S.G.is funded by the NWO-Veni grant(016.Veni.181.078 to S.G.).V.F.is funded by the Royal Society(RSG\R1\180213 and CHL\R1\180031)jointly by a grant from UKRI,Defra,and the Scottish Government,under the Strategic Priorities Fund Plant Bacterial Diseases programme(BB/T010606/1)at the University of York.
文摘Soil-borne plant diseases cause major economic losses globally.This is partly because their epidemiology is difficult to predict in agricultural fields,where multiple environmental factors could determine disease outcomes.Here we used a combination of field sampling and direct experimentation to identify key abiotic and biotic soil properties that can predict the occurrence of bacterial wilt caused by pathogenic Ralstonia solanacearum.By analyzing 139 tomato rhizosphere soils samples isolated from six provinces in China,we first show a clear link between soil properties,pathogen density and plant health.Specifically,disease outcomes were positively associated with soil moisture,bacterial abundance and bacterial community composition.Based on soil properties alone,random forest machine learning algorithm could predict disease outcomes correctly in 75%of cases with soil moisture being the most significant predictor.The importance of soil moisture was validated causally in a controlled greenhouse experiment,where the highest disease incidence was observed at 60%of maximum water holding capacity.Together,our results show that local soil properties can predict disease occurrence across a wider agricultural landscape,and that management of soil moisture could potentially offer a straightforward method for reducing crop losses to R.solanacearum.
