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Islam SS, Uddin Sarker MB, Rana MM, Hasan AK, Karim MR, Khomphet T. Comprehensive Assessment of the Genotype-Environment Interaction and Yield Stability of Boro Rice Genotypes under Four Environments in Bangladesh Using AMMI Analysis. SCIENTIFICA 2024; 2024:7800747. [PMID: 38994231 PMCID: PMC11239232 DOI: 10.1155/2024/7800747] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/02/2023] [Revised: 05/18/2024] [Accepted: 06/16/2024] [Indexed: 07/13/2024]
Abstract
Yield stability, alongside high yield potential and broad adaptation to various agroclimatic environments, is a key objective for rice breeders aiming to ensure food security. This study aimed to explore the most suitable and stable Boro rice genotypes for Bangladesh. Ten Boro rice genotypes underwent testing in four environments during the 2022 Boro season to investigate genotype-environment interaction (GEI) and yield stability performance. The experiment utilized three replications of a completely randomized block design. Yield stability performance was assessed through combined analysis and the additive main effects and multiplicative interaction (AMMI) model. The combined ANOVA revealed that the environment explained 10.23%, while GEI accounted for 9.17%, and the genotypes captured 80.60% of the variance, significantly impacting grain yield. Significance was observed in the environment, genotype main effects, and GEI. Analysis indicated that BRRI dhan 68 yielded the highest (6,754 kg·ha-1) and BRRI dhan 88 the lowest (5,620 kg·ha-1) among the investigated genotypes. In addition, genotypes BRRI dhan 84, BRRI dhan 81, and BRRI dhan 67 exhibited the highest grain yields. The Rangpur environment demonstrated considerable stability across the four environments with a high mean value of grain yield (7,206 kg·ha-1). Therefore, the AMMI model emerges as a valuable tool for identifying the most suitable and stable Boro rice genotypes with high-yielding potential across various regions in Bangladesh, as well as under diverse conditions.
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Affiliation(s)
- Shams Shaila Islam
- Department of AgronomyFaculty of AgricultureHajee Mohammad Danesh Science and Technology University, Dinajpur 5200, Bangladesh
| | - Md. Borhan Uddin Sarker
- Department of AgronomyFaculty of AgricultureHajee Mohammad Danesh Science and Technology University, Dinajpur 5200, Bangladesh
| | - Md. Masud Rana
- Department of AgronomyFaculty of AgricultureHajee Mohammad Danesh Science and Technology University, Dinajpur 5200, Bangladesh
| | - Ahmed Khairul Hasan
- Department of AgronomyFaculty of AgricultureBangladesh Agricultural University, Mymensingh 2202, Bangladesh
| | - Md. Rashed Karim
- Department of Geography and EnvironmentNew Government Degree College, Rajshahi 6000, Bangladesh
| | - Thanet Khomphet
- School of Agricultural Technology and Food IndustryWalailak University, Nakhon Si Thammarat 80160, Thailand
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2
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Mukaro R, Chaingeni D, Sneller C, Cairns JE, Musundire L, Prasanna BM, Mavankeni BO, Das B, Mulanya M, Chivasa W, Mhike X, Ndhlela T, Matongera N, Matova PM, Muungani D, Mutimaamba C, Wegary D, Zaman-Allah M, Magorokosho C, Chingwara V, Kutywayo D. Genetic trends in the Zimbabwe's national maize breeding program over two decades. FRONTIERS IN PLANT SCIENCE 2024; 15:1391926. [PMID: 38988630 PMCID: PMC11234322 DOI: 10.3389/fpls.2024.1391926] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/26/2024] [Accepted: 05/16/2024] [Indexed: 07/12/2024]
Abstract
Monitoring genetic gains within breeding programs is a critical component for continuous improvement. While several national breeding programs in Africa have assessed genetic gain using era studies, this study is the first to use two decades of historical data to estimate genetic trends within a national breeding program. The objective of this study was to assess genetic trends within the final two stages of Zimbabwe's Department of Research & Specialist Services maize breeding pipeline between 2002 and 2021. Data from 107 intermediate and 162 advanced variety trials, comprising of 716 and 398 entries, respectively, was analyzed. Trials were conducted under optimal, managed drought stress, low nitrogen stress, low pH, random stress, and disease pressure (maize streak virus (MSV), grey leaf spot (GLS), and turcicum leaf blight under artificial inoculation. There were positive and significant genetic gains for grain yield across management conditions (28-35 kg ha-1 yr-1), under high-yield potential environments (17-61 kg ha-1 yr-1), and under low-yield potential environments (0-16 kg ha-1 yr-1). No significant changes were observed in plant and ear height over the study period. Stalk and root lodging, as well as susceptibility to MSV and GLS, significantly decreased over the study period. New breeding technologies need to be incorporated into the program to further increase the rate of genetic gain in the maize breeding programs and to effectively meet future needs.
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Affiliation(s)
- Ronica Mukaro
- Crop Breeding Institute, Department of Research & Specialist Services, Harare, Zimbabwe
| | - Davison Chaingeni
- Crop Breeding Institute, Department of Research & Specialist Services, Harare, Zimbabwe
| | - Clay Sneller
- Department of Horticulture and Crop Science, The Ohio State University College of Food, Agriculture and Environmental Science, Columbus, OH, United States
| | - Jill E Cairns
- Global Maize Program, International Maize and Wheat Improvement Center (CIMMYT), Harare, Zimbabwe
| | - Lennin Musundire
- Accelerated Breeding Initiative (ABI)-Transform, International Maize and Wheat Improvement Centre (CIMMYT), Nairobi, Kenya
| | - Boddupalli M Prasanna
- Global Maize Program, International Maize and Wheat Improvement Centre (CIMMYT), Nairobi, Kenya
| | - Busiso Olga Mavankeni
- Crop Breeding Institute, Department of Research & Specialist Services, Harare, Zimbabwe
| | - Biswanath Das
- Accelerated Breeding Initiative (ABI)-Transform, International Maize and Wheat Improvement Centre (CIMMYT), Nairobi, Kenya
| | - Mable Mulanya
- Integrated Breeding Platform (IBP), International Maize and Wheat Improvement Centre (CIMMYT), Nairobi, Kenya
| | - Walter Chivasa
- Global Maize Program, International Maize and Wheat Improvement Centre (CIMMYT), Nairobi, Kenya
| | - Xavier Mhike
- Crop Breeding Institute, Department of Research & Specialist Services, Harare, Zimbabwe
- Global Maize Program, International Maize and Wheat Improvement Center (CIMMYT), Harare, Zimbabwe
| | - Thokozile Ndhlela
- Crop Breeding Institute, Department of Research & Specialist Services, Harare, Zimbabwe
- Global Maize Program, International Maize and Wheat Improvement Center (CIMMYT), Harare, Zimbabwe
| | - Nakai Matongera
- Crop Breeding Institute, Department of Research & Specialist Services, Harare, Zimbabwe
- Scientific and Industrial Research and Development Center (SIRDC), Harare, Zimbabwe
| | - Prince Muchapondwa Matova
- Crop Breeding Institute, Department of Research & Specialist Services, Harare, Zimbabwe
- Scientific and Industrial Research and Development Center (SIRDC), Harare, Zimbabwe
| | - Dean Muungani
- Crop Breeding Institute, Department of Research & Specialist Services, Harare, Zimbabwe
- Mukushi Seeds (Pvt) Ltd, Harare, Zimbabwe
| | - Charles Mutimaamba
- Crop Breeding Institute, Department of Research & Specialist Services, Harare, Zimbabwe
- Research for Development (R4D), International Institute of Tropical Agriculture (IITA), Ibadan, Nigeria
| | - Dagne Wegary
- Global Maize Program, International Maize and Wheat Improvement Center (CIMMYT), Harare, Zimbabwe
| | - Mainassara Zaman-Allah
- Global Maize Program, International Maize and Wheat Improvement Center (CIMMYT), Harare, Zimbabwe
| | - Cosmos Magorokosho
- Global Maize Program, International Maize and Wheat Improvement Center (CIMMYT), Harare, Zimbabwe
| | - Victor Chingwara
- Crop Breeding Institute, Department of Research & Specialist Services, Harare, Zimbabwe
| | - Dumisani Kutywayo
- Crop Breeding Institute, Department of Research & Specialist Services, Harare, Zimbabwe
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Khanna A, Anumalla M, Ramos J, Cruz MTS, Catolos M, Sajise AG, Gregorio G, Dixit S, Ali J, Islam MR, Singh VK, Rahman MA, Khatun H, Pisano DJ, Bhosale S, Hussain W. Genetic gains in IRRI's rice salinity breeding and elite panel development as a future breeding resource. TAG. THEORETICAL AND APPLIED GENETICS. THEORETISCHE UND ANGEWANDTE GENETIK 2024; 137:37. [PMID: 38294550 PMCID: PMC10830834 DOI: 10.1007/s00122-024-04545-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Accepted: 01/05/2024] [Indexed: 02/01/2024]
Abstract
KEY MESSAGE Estimating genetic gains and formulating a future salinity elite breeding panel for rice pave the way for developing better high-yielding salinity tolerant lines with enhanced genetic gains. Genetic gain is a crucial parameter to check the breeding program's success and help optimize future breeding strategies for enhanced genetic gains. To estimate the genetic gains in IRRI's salinity breeding program and identify the best genotypes based on high breeding values for grain yield (kg/ha), we analyzed the historical data from the trials conducted in the IRRI, Philippines and Bangladesh. A two-stage mixed-model approach accounting for experimental design factors and a relationship matrix was fitted to obtain the breeding values for grain yield and estimate genetic trends. A positive genetic trend of 0.1% per annum with a yield advantage of 1.52 kg/ha was observed in IRRI, Philippines. In Bangladesh, we observed a genetic gain of 0.31% per annum with a yield advantage of 14.02 kg/ha. In the released varieties, we observed a genetic gain of 0.12% per annum with a 2.2 kg/ha/year yield advantage in the IRRI, Philippines. For the Bangladesh dataset, a genetic gain of 0.14% per annum with a yield advantage of 5.9 kg/ha/year was observed in the released varieties. Based on breeding values for grain yield, a core set of the top 145 genotypes with higher breeding values of > 2400 kg/ha in the IRRI, Philippines, and > 3500 kg/ha in Bangladesh with a reliability of > 0.4 were selected to develop the elite breeding panel. Conclusively, a recurrent selection breeding strategy integrated with novel technologies like genomic selection and speed breeding is highly required to achieve higher genetic gains in IRRI's salinity breeding programs.
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Affiliation(s)
- Apurva Khanna
- Rice Breeding Innovation Platform, International Rice Research Institute (IRRI), 4031, Los Baños, Laguna, Philippines
| | - Mahender Anumalla
- Rice Breeding Innovation Platform, International Rice Research Institute (IRRI), 4031, Los Baños, Laguna, Philippines
| | - Joie Ramos
- Rice Breeding Innovation Platform, International Rice Research Institute (IRRI), 4031, Los Baños, Laguna, Philippines
| | - Ma Teresa Sta Cruz
- Rice Breeding Innovation Platform, International Rice Research Institute (IRRI), 4031, Los Baños, Laguna, Philippines
| | - Margaret Catolos
- Rice Breeding Innovation Platform, International Rice Research Institute (IRRI), 4031, Los Baños, Laguna, Philippines
| | - Andres Godwin Sajise
- Rice Breeding Innovation Platform, International Rice Research Institute (IRRI), 4031, Los Baños, Laguna, Philippines
| | - Glenn Gregorio
- Southeast Asian Regional Center for Graduate Study and Research in Agriculture (SEARCA) and University of Philippines, 4031, Los Baños, Laguna, Philippines
| | - Shalabh Dixit
- Rice Breeding Innovation Platform, International Rice Research Institute (IRRI), 4031, Los Baños, Laguna, Philippines
| | - Jauhar Ali
- Rice Breeding Innovation Platform, International Rice Research Institute (IRRI), 4031, Los Baños, Laguna, Philippines
| | - Md Rafiqul Islam
- IRRI South Asia Regional Center (IRRI-SA Hub), Hyderabad, Telangana, 502324, India
| | - Vikas Kumar Singh
- IRRI South Asia Regional Center (IRRI-SA Hub), Hyderabad, Telangana, 502324, India
| | - Md Akhlasur Rahman
- Plant Breeding Division, Bangladesh Rice Research Institute (BRRI), Gazipur, 1701, Bangladesh
| | - Hasina Khatun
- Plant Breeding Division, Bangladesh Rice Research Institute (BRRI), Gazipur, 1701, Bangladesh
| | - Daniel Joseph Pisano
- Rice Breeding Innovation Platform, International Rice Research Institute (IRRI), 4031, Los Baños, Laguna, Philippines
| | - Sankalp Bhosale
- Rice Breeding Innovation Platform, International Rice Research Institute (IRRI), 4031, Los Baños, Laguna, Philippines
| | - Waseem Hussain
- Rice Breeding Innovation Platform, International Rice Research Institute (IRRI), 4031, Los Baños, Laguna, Philippines.
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Tarekegne A, Wegary D, Cairns JE, Zaman-Allah M, Beyene Y, Negera D, Teklewold A, Tesfaye K, Jumbo MB, Das B, Nhamucho EJ, Simpasa K, Kaonga KKE, Mashingaidze K, Thokozile N, Mhike X, Prasanna BM. Genetic gains in early maturing maize hybrids developed by the International Maize and Wheat Improvement Center in Southern Africa during 2000-2018. FRONTIERS IN PLANT SCIENCE 2024; 14:1321308. [PMID: 38293626 PMCID: PMC10825029 DOI: 10.3389/fpls.2023.1321308] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Accepted: 12/07/2023] [Indexed: 02/01/2024]
Abstract
Genetic gain estimation in a breeding program provides an opportunity to monitor breeding efficiency and genetic progress over a specific period. The present study was conducted to (i) assess the genetic gains in grain yield of the early maturing maize hybrids developed by the International Maize and Wheat Improvement Center (CIMMYT) Southern African breeding program during the period 2000-2018 and (ii) identify key agronomic traits contributing to the yield gains under various management conditions. Seventy-two early maturing hybrids developed by CIMMYT and three commercial checks were assessed under stress and non-stress conditions across 68 environments in seven eastern and southern African countries through the regional on-station trials. Genetic gain was estimated as the slope of the regression of grain yield and other traits against the year of first testing of the hybrid in the regional trial. The results showed highly significant (p< 0.01) annual grain yield gains of 118, 63, 46, and 61 kg ha-1 year-1 under optimum, low N, managed drought, and random stress conditions, respectively. The gains in grain yield realized in this study under both stress and non-stress conditions were associated with improvements in certain agronomic traits and resistance to major maize diseases. The findings of this study clearly demonstrate the significant progress made in developing productive and multiple stress-tolerant maize hybrids together with other desirable agronomic attributes in CIMMYT's hybrid breeding program.
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Affiliation(s)
- Amsal Tarekegne
- Global Maize Program, International Maize and Wheat Improvement Centre (CIMMYT), Harare, Zimbabwe
| | - Dagne Wegary
- Global Maize Program, International Maize and Wheat Improvement Centre (CIMMYT), Harare, Zimbabwe
| | - Jill E. Cairns
- Global Maize Program, International Maize and Wheat Improvement Centre (CIMMYT), Harare, Zimbabwe
| | - Mainassara Zaman-Allah
- Global Maize Program, International Maize and Wheat Improvement Centre (CIMMYT), Harare, Zimbabwe
| | - Yoseph Beyene
- Global Maize Program, International Maize and Wheat Improvement Centre (CIMMYT), Nairobi, Kenya
| | - Demewoz Negera
- Global Maize Program, International Maize and Wheat Improvement Centre (CIMMYT), Addis Ababa, Ethiopia
| | - Adefris Teklewold
- Global Maize Program, International Maize and Wheat Improvement Centre (CIMMYT), Addis Ababa, Ethiopia
| | - Kindie Tesfaye
- Sustianable Agrifood Systems Program, International Maize and Wheat Improvement Centre (CIMMYT), Addis Ababa, Ethiopia
| | - MacDonald B. Jumbo
- Crop Improvement Program, International Crops Research Institute for Semi-Arid Tropics, Bamako, Mali
| | - Biswanath Das
- Global Maize Program, International Maize and Wheat Improvement Centre (CIMMYT), Nairobi, Kenya
| | - Egas J. Nhamucho
- Instituto de Investigação Agrária de Moçambique (IIAM), Chokwe, Mozambique
| | | | | | | | - Ndhlela Thokozile
- Global Maize Program, International Maize and Wheat Improvement Centre (CIMMYT), Harare, Zimbabwe
| | - Xavier Mhike
- Global Maize Program, International Maize and Wheat Improvement Centre (CIMMYT), Harare, Zimbabwe
| | - Boddupalli M. Prasanna
- Global Maize Program, International Maize and Wheat Improvement Centre (CIMMYT), Nairobi, Kenya
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5
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Seck F, Covarrubias-Pazaran G, Gueye T, Bartholomé J. Realized Genetic Gain in Rice: Achievements from Breeding Programs. RICE (NEW YORK, N.Y.) 2023; 16:61. [PMID: 38099942 PMCID: PMC10724102 DOI: 10.1186/s12284-023-00677-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Accepted: 12/10/2023] [Indexed: 12/18/2023]
Abstract
Genetic improvement is crucial for ensuring food security globally. Indeed, plant breeding has contributed significantly to increasing the productivity of major crops, including rice, over the last century. Evaluating the efficiency of breeding strategies necessitates a quantification of this progress. One approach involves assessing the genetic gain achieved through breeding programs based on quantitative traits. This study aims to provide a theoretical understanding of genetic gain, summarize the major results of genetic gain studies in rice breeding, and suggest ways of improving breeding program strategies and future studies on genetic gain. To achieve this, we present the concept of genetic gain and the essential aspects of its estimation. We also provide an extensive literature review of genetic gain studies in rice (Oryza sativa L.) breeding programs to understand the advances made to date. We reviewed 29 studies conducted between 1999 and 2023, covering different regions, traits, periods, and estimation methods. The genetic gain for grain yield, in particular, showed significant variation, ranging from 1.5 to 167.6 kg/ha/year, with a mean value of 36.3 kg/ha/year. This translated into a rate of genetic gain for grain yield ranging from 0.1% to over 3.0%. The impact of multi-trait selection on grain yield was clarified by studies that reported genetic gains for other traits, such as plant height, days to flowering, and grain quality. These findings reveal that while breeding programs have achieved significant gains, further improvements are necessary to meet the growing demand for rice. We also highlight the limitations of these studies, which hinder accurate estimations of genetic gain. In conclusion, we offer suggestions for improving the estimation of genetic gain based on quantitative genetic principles and computer simulations to optimize rice breeding strategies.
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Affiliation(s)
- Fallou Seck
- Rice Breeding Innovation Platform, International Rice Research Institute, DAPO Box7777, Metro Manila, Philippines
- University Iba Der Thiam of Thiès, GrandStanding, Thiès, Senegal
| | - Giovanny Covarrubias-Pazaran
- Rice Breeding Innovation Platform, International Rice Research Institute, DAPO Box7777, Metro Manila, Philippines
| | - Tala Gueye
- University Iba Der Thiam of Thiès, GrandStanding, Thiès, Senegal
| | - Jérôme Bartholomé
- CIRAD, UMR AGAP, Cali, Colombia.
- AGAP, Univ Montpellier, CIRAD, INRA, Montpellier SupAgro, Montpellier, France.
- Alliance Bioversity-CIAT, Cali, Colombia.
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Biswas PS, Ahmed MME, Afrin W, Rahman A, Shalahuddin AKM, Islam R, Akter F, Syed MA, Sarker MRA, Ifterkharuddaula KM, Islam MR. Enhancing genetic gain through the application of genomic selection in developing irrigated rice for the favorable ecosystem in Bangladesh. Front Genet 2023; 14:1083221. [PMID: 36911402 PMCID: PMC9992429 DOI: 10.3389/fgene.2023.1083221] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Accepted: 01/18/2023] [Indexed: 02/24/2023] Open
Abstract
Increasing selection differential and decreasing cycle time, the rate of genetic improvement can be accelerated. Creating and capturing higher genetic with higher accuracy within the shortest possible time is the prerequisite for enhancing genetic gain for any trait. Comprehensive yield testing at multi-locations at early generations together with the shortest line fixation time can expedite the rapid recycling of parents in the breeding program through recurrent selection. Genomic selection is efficient in capturing high breeding value individuals taking additive genetic effects of all genes into account with and without extensive field testing, thus reducing breeding cycle time enhances genetic gain. In the Bangladesh Rice Research Institute, GS technology together with the trait-specific marker-assisted selection at the early generation of RGA-derived breeding lines showed a prediction accuracy of 0.454-0.701 with 0.989-2.623 relative efficiency over the four consecutive years of exercise. This study reports that the application of GS together with trait-specific MAS has expedited the yield improvement by 117 kg ha-1·year-1, which is around seven-fold larger than the baseline annual genetic gain and shortened the breeding cycle by around 1.5 years from the existing 4.5 years.
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Affiliation(s)
- Partha S Biswas
- Plant Breeding Division, Bangladesh Rice Research Institute, Gazipur, Bangladesh
| | - M M Emam Ahmed
- Plant Breeding Division, Bangladesh Rice Research Institute, Gazipur, Bangladesh
| | - Wazifa Afrin
- Plant Breeding Division, Bangladesh Rice Research Institute, Gazipur, Bangladesh
| | - Anisar Rahman
- Plant Breeding Division, Bangladesh Rice Research Institute, Gazipur, Bangladesh
| | - A K M Shalahuddin
- Plant Breeding Division, Bangladesh Rice Research Institute, Gazipur, Bangladesh
| | - Rafiqul Islam
- Plant Breeding Division, Bangladesh Rice Research Institute, Gazipur, Bangladesh
| | - Fahamida Akter
- Plant Breeding Division, Bangladesh Rice Research Institute, Gazipur, Bangladesh
| | - Md Abu Syed
- Plant Breeding Division, Bangladesh Rice Research Institute, Gazipur, Bangladesh
| | - Md Ruhul Amin Sarker
- Plant Breeding Division, Bangladesh Rice Research Institute, Gazipur, Bangladesh
| | - K M Ifterkharuddaula
- Plant Breeding Division, Bangladesh Rice Research Institute, Gazipur, Bangladesh
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