Abstract
All the plant breeders tend to develop the concept of a plant in order to enhance the yield by selection of the individual traits to encompass the breeding model plants or ideotypes. Therefore, researchers must identify the factors limiting the performance and control the factors making the yield gap so as to determine the ideotype. Hence, this study was conducted to identify the superior traits for selecting the ideotype of local rice cultivars. The experiment was carried out with a randomized complete blocks design consisting of four replications, and 15 required local rice cultivars were collected for using the regression model, path coefficient analysis, and Mahalanobis distance analysis. The results revealed that nine variables were entered into the production equation and justified 65% of the yield variation, respectively. Increase in the yield due to the difference in yields in the maximal and average states of days to 50% of flowering was equal to 232 kg ha−1 accounting for 9% of the total yield increase. The field’s actual yield and potential yield using the model were equal to 4868 and 7545 kg ha−1, and the calculated yield gap was equal to 2677 kg ha−1. All the local cultivars were close to each other in terms of the genetic distance, showing that this ideotype yield gap can be compensated. According to the findings, the high level of PY changes and contribution of each factor influencing it shows a significant part of this change can be compensated leading to the potential yield through the proper management.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Andrivon D, Giorgetti C, Baranger A, Calonnec A, Cartolaro P, Faivre R, Guyader S, Lauri PE, Lescourret F, Parisi L, Ney B, Tivoli B, Sache I (2013) Defining and designing plant architectural ideotypes to control epidemics? Eur J Plant Pathol 135(4):611–617. https://doi.org/10.1007/s10658-012-0126-y
Bhakal M, Lal G (2015) Studies on genetic diversity in groundnut (Arachis hypogaea L.) germplasm. J Plant Sci Res 2(2):1–4
Chakravorty A, Ghosh P, Sahu P (2013) Multivariate analysis of phenotypic diversity of landraces of rice of West Bengal. Am J Exp Agric 3(1):110–123
Dastan S, Ghareyazie B, Abdollahi S (2020a) Field trial evidence of non-transgenic and transgenic Bt. rice genotypes in north of Iran. J Genet Eng Biotechnol 18:12. https://doi.org/10.1186/s43141-020-00028-8
Dastan S, Ghareyazie B, Teixeria da Silva JA (2020b) Selection of ideotype to increase yield potential of GM and non-GM rice cultivars. Plant Sci 297:110519. https://doi.org/10.1016/j.plantsci.2020.110519
Dubin HJ, Brennan JP (2009) Combating stem and leaf rust of wheat; historical perspective, impacts and lessons learned. IFPRI Discussion Paper 00910. International Food Policy Research Institute; Washington, DC
Espe MB, Cassman KG, Yang H, Guilpart N, Grassini P, Van Wart J, Anders M, Beighley D, Harrell D, Linscombe S, McKenzie K, Mutters R, Wilson LT, Linquist BA (2016a) Yield gap analysis of US rice production systems shows opportunities for improvement Matthew. Field Crops Res 196:276–283. https://doi.org/10.1016/j.fcr.2016.07.011
Espe MB, Yang H, Cassman KG, Guilpart N, Sharifi H, Linquist BA (2016b) Estimating yield potential in temperate high-yielding, direct-seeded US rice production systems. Field Crops Res 193:123–132. https://doi.org/10.1016/j.fcr.2016.04.003
Fageria NK, dos Santos AB, Coelho AM (2011) Growth, yield and yield components of lowland rice as influenced by ammonium sulphate and urea fertilization. J Plant Nutr 34(3):371–386
Fageria NK, Gheyi HR, Carvalho CS (2014) Yield, potassium uptake, and use efficiency in upland rice genotypes. II INOVAGRI International Meeting, 13–16 April, Fortaleza, Brazil. pp 4515–4520
Foley JA, Ramankutty N, Brauman KA, Cassidy ES, Gerber JS, Johnston M, Mueller ND, O’Connell C, Ray DK, West PC, Balzer C, Bennett EM, Carpenter SR, Hill J, Monfreda C, Polasky S, Rockstrom J, Sheehan J, Siebert S, Tilman D, Zaks DPM (2011) Solutions for a cultivated planet. Nature 478(7639):337–342. https://doi.org/10.1038/nature10452
Gonzalez FG, Slafer GA, Miralles DJ (2002) Vernalization and photoperiod response in wheat pre-flowering reproductive phases. Field Crops Res 74(2/3):183–195. https://doi.org/10.1016/S0378-4290(01)00210-6
Haghshenas H, Soltani A, Ghanbari Malidarreh A, Ajam Norouzi H, Dastan S (2019) Selecting the ideotype of improved rice cultivars using multiple regression and multivariate models. Arch Agron Soil Sci. https://doi.org/10.1080/03650340.2019.1658866
Hochman Z, Gobbett D, Holzworth D, McClelland T, van Rees H, Marinoni O, Garcia JN, Horan H (2013) Reprint of “Quantifying yield gaps in rain-fed cropping systems: a case study of wheat in Australia”. Field Crops Res 143:65–75. https://doi.org/10.1016/j.fcr.2013.02.001
Huang M, Zou YB, Jiang P, Xia B, Md I, Ao HJ (2011) Relationship between grain yield and yield components in super hybrid rice. Agric Sci China 10:1537–1544. https://doi.org/10.1016/S1671-2927(11)60149-1
Islam M, Akter K, Rashid E, Khalequzzaman M, Bashar M (2011) Genetic diversity of local irrigated rice (Oryza sativa L.). Bang J Plant Breed Genet 22(2):51–56
Islam M, Khalequzzaman M, Bashar M, Ivy N, Haque M, Mian M (2016) Variability assessment of aromatic and fine rice germplasm in Bangladesh based on quantitative traits. Sci World J 2016:Article ID 2796720
Islam MZ, Khalequzzaman M, Prince MFRK, Siddique MA, Rashid ESMH, Ahmed MSU, Pittendrigh BR, Ali MP (2018) Diversity and population structure of red rice germplasm in Bangladesh. PLoS ONE. https://doi.org/10.1371/journal.pone.0196096
Li R, Jiang T, Xu C, Li X, Wang X (2000) Relationship between morphological and genetic differentiation in rice (Oryza sativa L.). Euphytica 114(1):1–8
Licker R, Johnston M, Foley JA, Barford C, Kucharik CJ, Monfreda C, Ramankutty N (2010) Mind the gap: how do climate and agricultural management explain the ‘yield gap’ of croplands around the world? Glob Ecol Biogeogr 19:769–782. https://doi.org/10.1111/j.1466-8238.2010.00563.x
Lobell DB, Cassman KG, Field CB (2009) Crop yield gaps: their importance, magnitudes, and causes. Ann Rev Environ Resour 34:179–204. https://doi.org/10.1146/annurev.environ.041008.093740
Lorenceti C, Felix de Carvalho FI, de Oliviera AC, Valerio IP, Hartwig I, Benin G, Schmidt DAM (2006) Applicability of phenotypic and path coefficient in the selection of oat genotypes. Sci Agric 63(1):11–19. https://doi.org/10.1590/S0103-90162006000100003
Martre P, Quilot-Turion B, Luquet D, Memmah MMOS, Chenu K, Debaeke P (2015) Chapter 14—Model-assisted phenotyping and ideotype design. Academic Press, San Diego, pp 349–373
Meng Q, Hou P, Wu L, Chen X, Cui Z, Zhang F (2013) Understanding production potentials and yield gaps in intensive maize production in China. Field Crops Res 143:91–97. https://doi.org/10.1016/j.fcr.2012.09.023
Mueller ND, Gerber JS, Johnston M, Ray DK, Ramankutty N, Foley JA (2012) Closing yield gaps through nutrient and water management. Nature 490:254–257. https://doi.org/10.1038/nature11420
Nalley L, Tack J, Barkley A, Jagadish K, Brye K (2016) Quantifying the agronomic and economic performance of hybrid and conventional rice varieties. Agron J 108(4):1514–1523. https://doi.org/10.2134/agronj2015.0526
Nhamo N, Jonne R, Negussie Z, Godswill M, Ashura LK (2014) Narrowing the rice yield gap in East and Southern Africa: using and adapting existing technologies. Agric Syst 131:45–55
Nicolas FM, Bollero G, Bullock DG (2005) Associations between field characteristics and soybean plant performance using canonical correlation analysis. Plant Soil 273(1/2):39–55. https://doi.org/10.1007/s11104-004-6639-1
Oerke EC (2006) Crop losses to pests. J Agric Sci 144:31–43. https://doi.org/10.1017/S0021859605005708
Peng S, Khush GS, Virk P, Tang Q, Zou Y (2008) Progress in ideotype breeding to increase yield potential in rice. Field Crops Res 108(1):32–38. https://doi.org/10.1016/j.fcr.2008.04.001
Peng S, Tang Q, Zou Y (2009) Current status and challenges of rice production in China. Plant Prod Sci 12(1):3–8. https://doi.org/10.1626/pps.12.3
Rotter RP, Tao F, Hohn JG, Palosuo T (2015) Use of crop simulation modeling to aid ideotype design of future cereal cultivars. J Exp Bot 66(12):3463–3476. https://doi.org/10.1093/jxb/erv098
Savary S, Ficke A, Aubertot JN, Hollier C (2012) Crop losses due to disease and their implications for global production losses and food security. Food Secur 4(4):519–537. https://doi.org/10.1007/s12571-012-0200-5
Sheehy JE, Mitchell PI (2015) Calculating maximum theoretical yield in rice. Field Crops Res 182:68–75. https://doi.org/10.1016/j.fcr.2015.05.013
Siddique M, Khalequzzaman M, Islam M, Ahamed M, Rashid E (2013) Genetic diversity in local Boro rice (Oryza Sativa L.) genotypes of Bangladesh. Bang J Plant Breed Genet 26(1):19–24
Sohrabi M, Rafii M, Hanafi M, Siti Nor Akmar A, Latif M (2012) Genetic diversity of upland rice germplasm in Malaysia based on quantitative traits. Sci World J 2012:Article ID 416291
Soltani A, Galeshi S (2002) Importance of rapid canopy closure for wheat production in a temperate sub-humid environment: experimentation and simulation. Field Crops Res 77:17–30. https://doi.org/10.1016/S0378-4290(02)00045-X
Soltani A, Rezaei A, Khajehpour M, Mirlohi A (2000) Communication and share of various morphological and physiological traits in determining of grain yield sorghum. J Agric Sci Nat Resour 4:85–94
Streck NA, Weiss A, Xue Q, Baenziger PS (2003) Improving predictions of developmental stages in winter wheat: a modified Wang and Engel model. Agric For Meteorol 115(3/4):139–150. https://doi.org/10.1016/S0168-1923(02)00228-9
van Ittersum MK, Cassman KG, Grassini P, Wolf J, Tittonell P, Hochman Z (2013) Yield gap analysis with local to global relevance—a review. Field Crops Res 143:4–17. https://doi.org/10.1016/j.fcr.2012.12.012
Yang W, Duan L, Chen G, Xiong L, Liu Q (2013) Plant phenomics and high-throughput phenotyping: accelerating rice functional genomics using multidisciplinary technologies. Curr Opin Plant Biol 16:180–187. https://doi.org/10.1016/j.pbi.2013.03.005
Zeng L (2005) Exploration of relationships between physiological parameters and growth performance of rice (Oryza sativa L.) seedlings under salinity stress using multivariate analysis. Plant Soil 268(1):51–59. https://doi.org/10.1007/s11104-004-0180-0
Zhang QF (2007) Strategies for developing green super rice. Proc Natl Acad Sci USA (PNAS) 104:16402–16409. https://doi.org/10.1073/pnas.0708013104
Author information
Authors and Affiliations
Contributions
RY designed and performed the experiment; IMH supervised the research; HHS supervised the research; SD supervised the research and analyzed data.
Corresponding author
Ethics declarations
Conflict of interest
The authors have no financial conflicts of interest to declare.
Additional information
Communicated by A. Goyal.
Electronic supplementary material
Below is the link to the electronic supplementary material.
Rights and permissions
About this article
Cite this article
Yadi, R., Heravan, I.M. & Heidari Sharifabad, H. Identifying the superior traits for selecting the ideotype of rice cultivars. CEREAL RESEARCH COMMUNICATIONS 49, 475–484 (2021). https://doi.org/10.1007/s42976-020-00088-z
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s42976-020-00088-z