Combination of Strobilurin and Triazole Chemicals for the Management of Blast Disease in Mushk Budji -Aromatic Rice

Rice blast is considered one of the most important fungal diseases of rice. Although diseases can be managed by using resistant cultivars, the blast pathogen has successfully overcome the single gene resistance in a short period and rendered several varieties susceptible to blast which were otherwise intended to be resistant. As such, chemical control is still the most efficient method of disease control for reducing the losses caused due to diseases. Field experiments were conducted over two successive years, 2018 and 2019, in temperate rice growing areas in northern India. All the fungicides effectively reduced leaf blast incidence and intensity, and neck blast incidence under field conditions. Tricyclazole proved most effective against rice blast and recorded a leaf blast incidence of only 8.41%. Among the combinations of fungicides, azoxystrobin + difenoconazole and azoxystrobin + tebuconazole were highly effective, recording a leaf blast incidence of 9.19 and 10.40%, respectively. The chemical combination mancozeb + carbendazim proved less effective in controlling the blast and it recorded a disease incidence of 27.61%. A similar trend was followed in neck blast incidence with tricyclazole, azoxystrobin + difenoconazole, and azoxystrobin + tebuconazole showing the highest levels of blast reductions. It is evident from the current study that the tested fungicide combinations can be used as alternatives to tricyclazole which is facing the challenges of fungicide resistance development and other environmental concerns and has been banned from use in India and other countries. The manuscript may provide a guideline of fungicide application to farmers cultivating susceptible varieties of rice.

Evaluation of combination spray schedules of Tricyclazole and Pseudomonas fluorescens against blast disease of rice

Rice is the most important food crop and directly feeding more people than any other crop in the world.The blast disease caused by Pyricularia oryzae is a major and foremost constraint in rice production.Use of tricyclazole fungicide is one of the best and cost effective ways to quickly manage the disease. Considering the extensive use of fungicide has adverse effects for environment, the present study has been conducted to know the effect of Tricyclazole and Pseudomonas fluorescens alone and various combinations during rabi 2015-2016 and 2016-2017. From the two years data, the results indicated that a spray schedule consisting of tricyclazole followed by an alternate spray of Pseudomonas fluorescens (T + P + T + P), as well as either seed treatment with tricyclazole at 0.1 percent or root dipping with P. fluorescens at 1%, effectively reduced both leaf blast and neck blast with increasing grain yield.

Automatic Diagnosis of Rice Diseases Using Deep Learning

Rice disease has serious negative effects on crop yield, and the correct diagnosis of rice diseases is the key to avoid these effects. However, the existing disease diagnosis methods for rice are neither accurate nor efficient, and special equipment is often required. In this study, an automatic diagnosis method was developed and implemented in a smartphone app. The method was developed using deep learning based on a large dataset that contained 33,026 images of six types of rice diseases: leaf blast, false smut, neck blast, sheath blight, bacterial stripe disease, and brown spot. The core of the method was the Ensemble Model in which submodels were integrated. Finally, the Ensemble Model was validated using a separate set of images. Results showed that the three best submodels were DenseNet-121, SE-ResNet-50, and ResNeSt-50, in terms of several attributes, such as, learning rate, precision, recall, and disease recognition accuracy. Therefore, these three submodels were selected and integrated in the Ensemble Model. The Ensemble Model minimized confusion among the different types of disease, reducing misdiagnosis of the disease. Using the Ensemble Model to diagnose six types of rice diseases, an overall accuracy of 91% was achieved, which is considered to be reasonably good, considering the appearance similarities in some types of rice disease. The smartphone app allowed the client to use the Ensemble Model on the web server through a network, which was convenient and efficient for the field diagnosis of rice leaf blast, false smut, neck blast, sheath blight, bacterial stripe disease, and brown spot.

Resistance genes and gene pyramids controlling rice blast pathogen populations in eight African countries

BackgroundThe behavior of rice varieties under natural environments in fields often differs from the expected one. For developing varieties, breeders give then a particular importance to multi-local field screening to confirm the resistance of their germplasm. We assembled 81 accessions e.g. blast differential, traditional and improved varieties and tested them for resistance to blast (Pyricularia grisea) in eight African hot spots under different ecologies. We thus expected to identify accessions and genes or gene pyramids that provide durable resistance locally or across sites.Methods81 accessions (e.g. blast differential, traditional and improved varieties were tested in hot spots in Benin, Burkina Faso, Côte d'Ivoire, Madagascar, Mali, Rwanda, Togo and Uganda for resistance to leaf and neck blast. An Alpha design (randomized incomplete block) with four replications was used. Correlation between leaf blast and neck blast severity and between incidence and severity were analyzed.Results:From 2013 to 2016, multi-local screening tests were conducted at yje selected sites. Among the 81 rice accessions tested, seven accessions were consistently susceptible while 12 were resistant across locations and seasons. Interestingly, effective individual resistance genes (R genes) or gene pyramids efficient across the sites were identified. In addition, we noticed on some sites, changes in the responses of some rice accessions to the disease from one season to the other. Responses of some accessions also showed great variations from one site to another. In addition, several accessions sharing the same resistance genes exhibited different responses to blast. Regarding the neck blast, only fewer accessions could be assessed as very susceptible ones died at early stages. Although differential responses were observed in the four sites considered for the analysis, several accessions consistently resisted. In addition, results showed that leaf and neck blast resistances were correlated.ConclusionsResults obtained provide useful information on the tested germplasm resistance. In addition, it was possible to identify resistant accessions and sometimes the R genes associated which were effective locally or across sites. Results also showed shifts in pathogenicity of the pathogen populations over seasons and sites. Finally, breeders can now use this valuable information for sustainable blast resistance breeding.

Field Evaluation of RD6 Introgression Lines for Yield Performance, Blast, Bacterial Blight Resistance, and Cooking and Eating Qualities

Glutinous rice cultivar “RD6” is well known for its fragrance and high cooking and eating qualities, and is the most popular glutinous cultivar in the north and northeastern regions of Thailand. However, it’s susceptible to blast and bacterial blight (BB) diseases. Previously, four blast resistance QTLs on chromosomes 1, 2, 11, and 12, and a single BB resistance gene xa5 pyramided to the background of the RD6 cultivar were tested for a broad spectrum of disease resistance under greenhouse conditions. In the present study, a field experiment was conducted during the rainy seasons of 2015, 2016, 2017, and 2018, across three locations, for performance evaluations of promising lines in terms of disease reaction, agronomical characteristics, grain yield, and quality attributes. The results revealed that the ILs (BC2F5 2-7-5-36, BC2F5 2-7-5-43, BC2F5 2-8-2-25, and BC2F5 6-1/15-2-11) exhibited higher level resistance to leaf blast and neck blast disease. The BC2F5 2-8-2-52 showed resistance to both blast and BB diseases and, like all ILs, exhibited superior yield compared to the original RD6. Furthermore, the agronomic traits and grain qualities were similarly displaced, and were therefore recommended as near-isogenic lines to the RD6. This clearly demonstrated that farm phenotypic selection plays an important role in achieving not only NIL resistance to diseases, but also high yield potential, as well as representing an effective way in which to enhance BB, leaf blast, and neck blast resistance in rice planting in the north and northeastern regions of Thailand.

DECREASE IN PRODUCTION AND QUALITY OF GRAIN DUE TO NECK BLAST DISEASE IN SOME LOWLAND RICE VARIETIES

Decrease in production and quality of grain due to neck blast disease in some lowland rice varieties. Neck blast disease of rice causes a decrease in yields both in quantity and quality. The study was conducted to see the effect of neck blast disease on the characteristics of grain and yields of several high yielding varieties of lowland rice. The varieties used were Ciherang, Inpari 4, Inpari 7, Inpari 8, and Inpari 9. The parameters observed were the incidence and severity of neck blast disease, the ratio of the size of the seeds of healthy and sick panicles and the estimated production. The analysis showed that all varieties planted were infected by neck blast disease, but based on Disease Incident rate in the Necks, Ciherang and Inpari 8 varieties reacted susceptible to neck blast disease, Inpari 7 and 9 were moderate and Inpari 4 was resistant to neck blast disease. The quality of panicle grain infected by neck blast disease has decreased the size of grain width and was significantly different from grain of healthy panicles in all varieties. The highest estimated productivity was Inpari 4 variety of 10,378 kg/ha which experienced a decrease in production by 35.86% and the lowest was Ciherang variety of 8,367 kg/ha which experienced a decrease in production by 48.37% when they were infected by neck blast disease.