alexa Screening of Different Rice Genotypes against (Pyricularia grisea) Sacc. in Natural Epidemic Condition at Seedling Stage in Chitwan, Nepal | OMICS International
ISSN: 2329-8863
Advances in Crop Science and Technology
Make the best use of Scientific Research and information from our 700+ peer reviewed, Open Access Journals that operates with the help of 50,000+ Editorial Board Members and esteemed reviewers and 1000+ Scientific associations in Medical, Clinical, Pharmaceutical, Engineering, Technology and Management Fields.
Meet Inspiring Speakers and Experts at our 3000+ Global Conferenceseries Events with over 600+ Conferences, 1200+ Symposiums and 1200+ Workshops on
Medical, Pharma, Engineering, Science, Technology and Business

Screening of Different Rice Genotypes against (Pyricularia grisea) Sacc. in Natural Epidemic Condition at Seedling Stage in Chitwan, Nepal

Khanal Sabin1*, Subedi Bijay1, Bhandari Amrit1, Giri Dilli Raman1, Shrestha Bhuwan1, Neupane Priyanka2, Shrestha Sundar Man2 and Gaire Shankar Prasad2

1Institute of Agriculture and Animal Science, Tribhuwan Univeristy, Chitwan, Nepal

2Department of Plant Pathology, Faculty of Agriculture, Agriculture and Forestry University, Nepal

Corresponding Author:
Sabin Khanal
Institute of Agriculture and Animal Science
Tribhuwan University, Nepal
Tel: +9779849745130
E-mail: [email protected]

Received date: July 02, 2016; Accepted date:July 15, 2016; Published date: July 20, 2016

Citation:Sabin K, Bijay S, Amrit B, Raman GD, Bhuwan S, et al. (2016) Screening of Different Rice Genotypes against (Pyricularia grisea) Sacc. in Natural Epidemic Condition at Seedling Stage in Chitwan, Nepal. Adv Crop Sci Tech 4:231. doi:10.4172/2329-8863.1000231

Copyright: © 2016 Sabin K, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Visit for more related articles at Advances in Crop Science and Technology

Abstract

Numerous research has already establish blast as the continuous and devastating threat to rice production in Nepal and on the contrary Nepalese farmers do not have efficient knowledge and understanding about the complexity of disease for the management of the blast epidemic development. The most effective physical tool seems to be provision of resistant genotypes obtained against screening of different rice genotypes: effective management practices against the complexity of blast pathogen. Experiments were conducted for screening 50 rice genotypes under natural epidemic condition against seedling blast (Pyricularia grisea) in Randomized complete block design at Chitwan. Rice grains were sown on July 6, 2015 at field and disease scoring was done on 21, 24, 27 and 30 DAS; Scoring was done based on the standard scale of 0-9 developed by IRRI. Based on the result Taichung-176 and Sankharika showed the highest percentage of incidence and severity of disease. Sabitri, however, was found to be most resistant among genotypes with the lowest percentage of incidence and severity during observation.

Keywords

Rice blast; Pyriculariagrisea;Sabitri; Blast susceptible

Introduction

Blast is caused by Pyriculariagrisea. It occurs in nearly all rice growing areas of the world. It is considered the most serious disease in both temperate and tropical rainfedenviroments. With increasing nitrogenous fertilizer and higher plant density, blast is known to be devastating [1].Blast was first recorded in china in 1637. The causal organism was named Pyriculariaoryzaeby Cavara in italy in 1891 and was renamed by Rossman 1990 to Pyriculariagrisea [2].

Rice is truly a crop of global importance. Almost half the world’s population, particularly in east and south east asia, depends on rice as the major source of nutritional calories [3]. Every year it is estimated that rice blast destroy food more than enough to eat for 60 million people and 50% of the rice yield is lost in the field by the occurrence of blast [4] Rice is the most prestigious food crop of Nepal. It is grown in a diverse environment ranging from tropical plains to foot of the mountain and higher elevation (3050 masl) in Chhumchure, Jumla. Nepal is considered as one of the origin center of rice. It is one of the most important cereal crops in Nepal. Rice is grown in 1440 thousand ha and the productivity is 2.56 t/ha. It contributes nearly 20 per cent to the agricultural gross domestic product. Nepal has released fifty five rice varieties with full package of growing practices in the last 40 years. The coverage by improved varieties is 85 percent of the total rice cultivated land. Popularly cultivated improved varieties are Radha-4, Radha-12, Masuli, Sabitri, CH-45, Bindeswori in terai, Khumal-4, Khumal-11, Taichung-176, chaining in mid-hills and Chandanaath-3 in high hills (NARC 2014). Radha-12, sabitri, janaki possess higher level of resistance [5]. Seedlings of high yielding masuli were affected in late june in saradanagar, Rampur, kiranganj, mangalpur and ratanagar area of the chitwan district [6]. Radha-12 had 7 fold less neck blast than masuli whereas other genotypes showed less neck blast than masuli [5].

Rice blast genetic analysis confirmed gene for gene interaction that control cultivar specificity in fungal plant interactions. Nuclear and mitochondrial genomes molecular analyses suggest that M. grisea pathogen remain in nature as different types of genetically distinct asexually reproducing population [7]. An understanding of the molecular mechanism that govern host specificity should aid in the development of new strategies for control of rice blast [8]. Mechanism controlling host species specificity differ in basic compatibility factor that allows pathogen to infect particular species. PWL2 host species specificity gene has properties analogous to classical avirulence genes, which function to prevent infection of certain cultivars of particular host species. The PWL2 gene encodes a glycine-rich, hydrophilic protein with a putative secretion signal sequence [8]. Blast, caused by Pyricularia grisea Sacc has been a continuous threat to rice production in Nepal [9,10]. Blast epidemics result in a complete loss of seedlings in the seedbed [6,11-16]

Varying tools have been used as a blast management toolkit such as knowledge tools, communication, physical and policy tools. Each tool is rationalized in terms of having an effect either on initial inoculum or disease (x0), the epidemic infection rate(R) or duration of epidemic (D). Certain tools like biological control agents and confirmatory serological tools are still unknown to blast control. Nepalese farmers do not have efficient knowledge and understanding about the use of fungicide and the effect of nutrient (nitrogen, phosphorus, potassium), and nonnutrient (silicon) amendments on blast epidemic development. Water management to reduce stress on plants at blast susceptible stages [17] are still in the dark to the Nepalese common farmers. Cultural practices seem ineffective due to no clear cut fallow period between any two rice seasons making blast pathosystem a continuous pathosystem and given the dispersal pattern of conidia initial inoculum will always be available for matching alloinfection. Hence, the most effective physical tool seems to be provision of resistant genotype. Seed possessing resistant genes to blast have been the basis for plant protection for centuries [13].

Materials and Methods

Experimental setup

Field experiment was set up in Agronomy farm of IAAS, Rampur, Chitwan. The experiment was conducted in single factorial RCBD design with 3 replication. Each plot was 5 mX1 m, in each replication 50 rows was made to sow the 50 different genotypes. Seed was sown randomly in such a way that, genotypes was not repeated in line in the replications. Seeding was done in 2nd week of July.

Observation

Disease assessment

Disease incidence: Appearance of first symptoms of disease among all the plants germinated will be recorded. Here, total no. of plants in a row and Number of plants showing the symptoms will be recorded (Figures 1 and 2).

advances-crop-science-and-technology-Disease-incidence-observed

Figure 1: Disease incidence was observed at 21, 24, 27 and 30 DAS. At 21 DAS, lowest disease incidence was observed in Kanchi Masuli followed by sabitri whereas highest disease incidence was observed in NR 10676-B-1-3-3-3-2 followed by sankharika and Pusa basmati. Similarly, during 24 DAS, 27 DAS and 30 DAS lowest disease incidence was observed in Sabitri whereas highest disease incidence at 24 DAS NR 11050-B-B-B-B-2 followed by NR 11050-B-B-B-B-1, NR 11016-B-5-2-3-3-2; at 27 DAS, NR 11050-B-B-B-B-2 followed by NR 11050-B-B-B-B-2 and NR 11016-B-5-2-3-3-2 were found to be highest and during 30 DAS NR 11050-B-B-B-B-2 followed by NR 11050-B-B-B-1 and NR 11105-B-B-27 were found highest.

advances-crop-science-and-technology-standard-scoring-scale

Figure 2: Based on the standard scoring scale of 0-9 developed by IRRI, disease were scored at 21, 24, 27 and 30 DAS and disease severity % was calculated as above mentioned formula(materials and methods). During 21 DAS lowest disease severity was observed on kanchi masuli followed by sabitri whereas on all other days of observation lowest disease severity % was observed on sabitri. However, during all days of observation Taichung-176 showed highest disease severity percentage along with varieties sankharika, pusa basmati, NR 11050-B-B-B-1 and NR 11111-B-B-23-2.

Percent disease incidence will be calculated by using the formula:

Equation

Disease scoring: Disease scoring will be done according to standard scoring scale developed by International Rice Research Institute (IRRI) using a scale of 0-9.

• Small brown specks of pin point size.

• Small roundish to slightly elongated, necrotic gravy spots, about 1-2 mm in diameter, with a distinct brown margin, lesions are mostly found on the lower leaves.

• Lesion type is the same as in 2, but significant number of lesion are on the upper leaves.

• Typical susceptible blast lesions, 3 mm or longer, infecting less than 4% of the leaf area.

• Typical susceptible blast lesions, 3 mm or longer, infecting less than 4-10% of the leaf area.

• Typical susceptible blast lesions, 3 mm or longer, infecting less than 11-25% of the leaf area.

• Typical susceptible blast lesions, 3 mm or longer, infecting less than 26-50% of the leaf area.

• Typical susceptible blast lesions, 3 mm or longer, infecting less than 51-75% of the leaf area, many leaves dead.

• Typical susceptible blast lesions, 3 mm or longer, infecting more than 75% of the leaf area

Disease intensity/index: Disease severity will be scored on the basis of standard scoring scale developed by International Rice Research institute (IRRI). 5 plants from each row showing the symptoms will be selected at random for observation and scored at a scale of 0-9 and average will be taken.

Disease severity will be calculated as:

Equation

AUDPC:

Equation

Where, yi: initial infection percentage (disease score)

Yi+1: progressive infection percentage

Ti+1-ti: time interval between the readings

Area under disease progressive curve

Total AUDPC value lied in the range of 17.78-210%. AUDPC 1&2 were calculated based on the disease severity percentage and calculated using formula as presented in the materials and methods above. Lowest total AUDPC was observed on Sabitri whereas highest was observed on Taichung-176 followed by pusa basmati, NR 11111-B-B-23-2, Sankharika and NR 10490-89-3-2-1. Based on the Total AUDPC value rice genotypes were listed on the five categories from resistant to highly susceptible which are shown in the Tables 1 and 2.

Genotypes      AUDPC1     AUDPC2      AUDPC 3 TOTAL AUDPC
NR 10676-B-1-3-3-3
NR 10490-89-3-2-1
NR 11105-B-B-27
NR 11052-B-B-B-B_6
08FAN10
NR10769-4-2-2
NR 10676-B-5-3
NR 11011-B-B-B-B-3
NR 11011-B-B-B-B-2
Sugandha-2
NR 11050-B-B-B-1
NR 11037-B-B-B-B-5
NR 11022-2-2-3-3-1
NR 11092-B-B-B-12
NR 11042-B-B-B-1-1
NR 11082-B-B-B-5-3
NR 11016-B-5-2-3-3-2
NR 11011-B-B-B-B-6
NR 11139-B-B-B-21
NR 11050-B-B-B-B-2
NR 11115-B-B-31-3
NR 11130-B-B-B-19
NR 11105-B-B-16-2
NR 11111-B-B-23-2
NR 11109-B-B-12-3-2
Madhya dhan -845
Sonamansuli
Radha-22
Sankharika
Radha-11
IR87751-20-4-4-2
NR 11111-B-B-23
Manjushree-2
Taichung-176
Khumal-4
Kalomasino
Radha-4
Sawamansuli
Ramdhan
Sabitri
Bindeshwari
Sukkah-3
Savashab-1
Jethimansuli
Basmati seto
Pusa basmati
Sarju
Hardinath
Kanchi
Makwanpure
44.44bcdefg
53.33ab
44.44bcdefg
47.78abcde
25.56hijkl
33.33defghijkl
35.56cdefghijk
26.67hijkl
20.00klm
24.44hijkl
38.89bcdefghij
32.22defghijkl
24.44hijkl
30.00fghijkl
31.11efghijkl
27.78ghijkl
40.00bcdefghi
37.78bcdefghij
37.77bcdefghij
32.22defghijkl
40.00bcdefghi
41.11bcdefgh
37.78bcdefghij
41.11bcdefgh
46.67bcdef
36.67bcdefghijk
46.67bcdef
40.00bcdefghi
53.33ab
30.00fghijkl
33.33defghijkl
48.89abcde
35.56cdefghijk
64.44a
37.78bcdefghij
22.22jkl
17.78lm
37.78bcdefghij
26.67hijkl
4.44m
48.89abcd
23.33ijkl
20.00klm
30.00fghijkl
32.22defghijkl
52.22abc
35.56cdefghijk
24.44hijkl
17.78lm
22.22jkl
48.49bcdefghi
57.78abcd
53.33abcdef
56.67abcde
35.56ghijklmn
40.00fghijkl
44.44cdefghijkl
37.78fghijklm
31.11klm
42.22defghijkl
58.89abc
37.78fghijklmn
33.33ijklm
36.67ghijklm
43.33cdefghijkl
41.11efghijkl
43.33cdefghijkl
46.67bcdefghijk
48.89bcdefghi
44.44cdefghijkl
56.67abcde
41.11efghijkl
47.78bcdefghij
47.78bcdefghij
51.11bcdefg
45.56bcdefghijk
53.33abcdef
47.78bcdefghij
58.89abc
32.22jklm
42.22defghijkl
58.89abc
44.44cdefghijkl
68.89a
43.33cdefghijkl
28.89lm
22.22m
50.00bcdefgh
40.00fghijkl
5.56n
53.33abcdef
31.11klm
31.11klm
38.89fghijkl
41.11efghijkl
61.11ab
45.56bcdefghijk
34.44hijklm
37.78fghijklm
33.33ijklm
53.33bcdefghij
64.44abc
61.11abcde
63.33abc
38.89fghijk
44.44cdefghij
53.33bcdefghij
44.44cdefghij
37.78ghijk
53.33bcdefghij
68.89ab
41.11efghijk
37.78ghijk
45.56cdefghij
51.11bcdefghij
47.78cdefghij
47.78cdefghij
57.78abcdefghij
60.00abcde
53.33bcdefhij
62.22abcd
45.56cdefghij
50.00bcdefghij
54.44bcdefghi
56.67abcdefgh
52.22bcdefghij
58.89abcdef
54.44bcdefghij
64.44abc
33.33jk
46.67cdefghij
70.00ab
53.33bcdefghij
76.67a
47.78cdefghij
36.67hijk
22.22kl
55.56bcdefghi
50.00bcdefghij
7.77l
58.88abcdef
35.55ijk
41.11efghijk
47.78cdefghij
51.11bcdefghij
68.89ab
55.56bcdefghi
42.22defghijk
44.44cdefghij
41.11efghijk
146.67bcdefghij
175.56abcd
158.89bcdefgh
167.78abcde
100.00jklm
117.78fghijkl
133.33bcdefghijkl
108.89ijklm
88.89lm
120.00efghijkl
166.66abcdef
111.11hijklm
95.56klm
112.22ghijkl
125.56efghijkl
116.67ghijkl
131.11cdefghijkl
142.22bcdefghijk
146.67bcdefghij
130.00cdefghijkl
158.89bcdefgh
127.78defghijkl
135.56bcdefghijkl
143.33bcdefghijk
154.44bcdefghi
134.44bcdefghijkl
158.89bcdefgh
142.22bcdefghijk
176.67abcd
95.56klm
122.22efghijkl
177.78abc
133.33bcdefghijkl
210.00a
128.89cdefghijkl
87.78lm
62.22mn
143.33bcdefghijk
116.67ghijkl
17.78n
161.11abcdefg
90.00lm
92.22lm
116.67ghijkl
124.44efghijkl
182.22ab
136.67bcdefghijkl
101.11jklm
100.00jklm
96.67klm

Table 1: AUDPC values of rice genotypes.

Category Range Genotypes
Resistant 0-70 Sabitri
Radha-4
Moderately resistant 71-120 Kalomasino
Sukkah-3
NR 11011-B-B-B-B-2
Savashab-1
NR 11022-2-2-3-3-1
KanchiMansulimasuli
Hardinath
Radha-11
08FAN10
Makwanpure
NR 11092-B-B-B-12
NR 11037-B-B-B-B-5
NR 11011-B-B-B-B-3
NR 11082-B-B-B-5-3
Ramdhan
Jethimansuli
NR 10769-4-2-2
Sugandha-2
  Moderately susceptible   121-140   IR87751-20-4-4-2
Basmati seto
NR 11042-B-B-B-1-1
NR 11130-B-B-B-19
Khumal-4
NR 11050-B-B-B-B-2
NR 11016-B-5-2-3-3-2
NR 10676-B-5-3
Manjushree-2
Madhya dhan-845
NR 11105-B-B-16-2
Sarju
  Susceptible             Highly susceptible   141-170             171-225   Radha-22
NR 11111-B-B-23-2
NR 11011-B-B-B-6
NR 10676-B-1-3-3-3
NR 11139-B-B-B-21
SawaMansuli
NR 11109-B-B-12-3-2
Bindeshwari
NR 11105-B-B-27
NR 11115-B-B-31-3
NR 11050-B-B-B-1
SonaMansuli
NR 11052-B-B-B-B-6 NR 11111-B-B-23-2
Sankharika
Pusa Basmati
Taichung-176
NR 10490-89-3-2-1

Table 2: Based on the AUDPC value rice genotypes are listed on the five categories from resistant to highly susceptible.

Discussion

Disease incidence was observed at 21, 24, 27 and 30 DAS. At 21 DAS, lowest disease incidence was observed in Kanchi Masuli followed by sabitri whereas highest disease incidence was observed in NR 10676- B-1-3-3-3-2 followed by sankharika and Pusa basmati. Similarly, during 24 DAS, 27 DAS and 30 DAS lowest disease incidence was observed in Sabitri whereas highest disease incidence at 24 DAS NR 11050-B-BB- B-2 followed by NR 11050-B-B-B-B-1, NR 11016-B-5-2-3-3-2; at 27 DAS, NR 11050-B-B-B-B-2 followed by NR 11050-B-B-B-B-2 and NR 11016-B-5-2-3-3-2 were found to be highest and during 30 DAS NR 11050-B-B-B-B-2 followed by NR 11050-B-B-B-1 and NR 11105-B-B-27 were found highest [18-20]. Sabitri was reported to be most resistant by Chaudary et al. [5]. Genotypes starting with NR initial were breeding lines developed by Nepal Agriculture Research Council (NARC) as they were developed for high hills and this experiment being conducted in the terai region might had induced blast incidence on these lines due to unsuitable temperature to the genotypes.

During 21 DAS lowest disease severity was observed on kanchi masuli followed by sabitri whereas on all other days of observation lowest disease severity % was observed on sabitri. However, during all days of observation Taichung-176 showed highest disease severity percentage along with varieties sankharika, pusa basmati, NR 11050-B-B-B-1 and NR 11111-B-B-23-2. Experiment by Manandher et al. [11] presented sankharika to be most susceptible variety and established that it is adversely affected by blast pathogen whereas Taichung-176 were found to be highly susceptible variety by Manandhar et al. [9]. Kumar et al. [21] reported pusa basmati as most susceptible to blast disease.

Similarly sabitri showed lowest level of AUDPC value and was categorized as the resistant genotype along with Radha-4 which is supported by Chaudary et al. [5] suggesting that Sabitri and Radha varieties to be resistant to blast pathogen; whereas Taichung-176 pusa basmati and Sankharika were categorized as the most susceptible varieties which coincides with the result presented by (Manandhar et al. and Manandhar et al.) and Kumar et al. [9,11,21]. Similary, NR 11111-B-B-23-2 and NR 10490-89-3-2-1 were also categorized as the most susceptible and more conclusive result are yet to be drawn of these genotypes.

Conclusion

50 rice genotypes were sown in 6th July in Randomized complete block design at chitwan. The experiment was only limited to seedling stage and its purpose was to identify the resistant and susceptible variety among the different rice genotypes collected all over the country along with some of the breedling lines provided by the NARC khumaltar. Sankharika, Taichung-176, pusa basmati, NR 11111-B-B-23 and NR 10490-89-3-2-1 were found most susceptible and sabitri and Radha-4 were found to be resistant.

As Taichung-176, sankharika was found to be most susceptible to blast on both field and lab condition as NARC has described Taichung-176 as susceptible variety to mid-hills and sankharika to Terai region. Sabitri was found to be most resistant among all genotypes. Further research is recommended on the varieties mentioned above for further certainty; in addition, further research work such as comparison of plant yield with disease can be done and also molecular study of the plant varieties is further recommended.

Acknowledgements

I would like to express my sincere gratitude to prof. Dr. Sundarman Shrestha and Mr. Shankhar Gaire, Faculty of Plant pathology at Agriculture and Forestry University for their guidance and support during all the activity of this research. I would also like to acknowledge Mr. Bikash adhikari for his help during all the field activities; Mr. Ramesh Acharya for his support; Mrs. Shawantana Ghimire Khanal for her encouragement to write this paper.

References

Select your language of interest to view the total content in your interested language
Post your comment

Share This Article

Relevant Topics

Recommended Conferences

Article Usage

  • Total views: 8740
  • [From(publication date):
    August-2016 - Apr 23, 2018]
  • Breakdown by view type
  • HTML page views : 8613
  • PDF downloads : 127
 

Post your comment

captcha   Reload  Can't read the image? click here to refresh

Peer Reviewed Journals
 
Make the best use of Scientific Research and information from our 700 + peer reviewed, Open Access Journals
International Conferences 2018-19
 
Meet Inspiring Speakers and Experts at our 3000+ Global Annual Meetings

Contact Us

Agri & Aquaculture Journals

Dr. Krish

[email protected]

1-702-714-7001Extn: 9040

Biochemistry Journals

Datta A

[email protected]

1-702-714-7001Extn: 9037

Business & Management Journals

Ronald

[email protected]

1-702-714-7001Extn: 9042

Chemistry Journals

Gabriel Shaw

[email protected]

1-702-714-7001Extn: 9040

Clinical Journals

Datta A

[email protected]

1-702-714-7001Extn: 9037

Engineering Journals

James Franklin

[email protected]

1-702-714-7001Extn: 9042

Food & Nutrition Journals

Katie Wilson

[email protected]

1-702-714-7001Extn: 9042

General Science

Andrea Jason

[email protected]

1-702-714-7001Extn: 9043

Genetics & Molecular Biology Journals

Anna Melissa

[email protected]

1-702-714-7001Extn: 9006

Immunology & Microbiology Journals

David Gorantl

[email protected]

1-702-714-7001Extn: 9014

Materials Science Journals

Rachle Green

[email protected]

1-702-714-7001Extn: 9039

Nursing & Health Care Journals

Stephanie Skinner

[email protected]

1-702-714-7001Extn: 9039

Medical Journals

Nimmi Anna

[email protected]

1-702-714-7001Extn: 9038

Neuroscience & Psychology Journals

Nathan T

[email protected]

1-702-714-7001Extn: 9041

Pharmaceutical Sciences Journals

Ann Jose

[email protected]

1-702-714-7001Extn: 9007

Social & Political Science Journals

Steve Harry

[email protected]

1-702-714-7001Extn: 9042

 
© 2008- 2018 OMICS International - Open Access Publisher. Best viewed in Mozilla Firefox | Google Chrome | Above IE 7.0 version