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Rapid Generation Advance Methods to Fast-track Crop Breeding: A Review

Swarnadip Ghosh1, Abhik Roy2, Suman Dutta1,*
1Division of Genetics, ICAR-Indian Agricultural Research Institute, New Delhi-110 012, Delhi, India.
2Division of Seed Science and Technology, ICAR-Indian Agricultural Research Institute, New Delhi-110 012, Delhi, India.
Rapid generation advance is a collection of breeding tools for quicker development of homozygous lines from the segregating generations raised from a cross of two divergent parents. An array of techniques including single seed descent, speed breeding, shuttle breeding, doubled haploidy, marker assisted breeding and genomic selection were designed to achieve the maximum genetic gain through reducing the time required for development of such homozygous lines. In addition, utilization of genome editing in agronomically important crops further enhances the genetic advance to alleviate the food supply shortage. Therefore, utilization of these techniques could be more advantageous than the conventional breeding approaches in terms of speed and logistic support. Combination of these methods allows breeders to develop agronomically superior varieties in a very short period of time.
With the increase in global population at an alarming rate, there is an urgent need to increase food production at the same rate or even faster to fulfill the food and nutritional requirements. As there is a little scope for increase in the area of cultivation, plant breeders need to focus on development of new varieties with increased productivity as well as ability to tolerate various biotic and abiotic stress. Besides, recent climate change and global warming demand climate-smart agriculture with new crop varieties that can minimize crop loss due to adverse conditions and emergence of new pests and diseases. In this context, plant breeders should focus on stability and sustainability of crop yields. However, development of new varieties is a tedious and time-consuming process. The time required in a breeding program majorly depends on number of years required to develop homozygous lines from segregating generations from crossing of two parents. Conventional pedigree breeding method takes around six to seven years or even more to develop homozygous lines if only a single crop is grown in a season. In addition, subsequent few more years are required for evaluation of the advanced generation breeding materials for release as a new variety. Therefore, special tools and techniques are required for modern-day crop improvement programmes to meet the increasing demands. Rapid generation advance (RGA) is a novel way of reducing the time for the breeding cycle to enhance the genetic gain (Li et al., 2018).
 
Rapid generation advance
 
Rapid generation advance (RGA) is a bunch of breeding tools for faster development of fixed lines from the segregating generations (Fig 1). RGA allows several generations per year by manipulating growth conditions of plants such as temperature, relative humidity, photoperiod and daylength for rapid induction of flowering and seed set. Often, this is achieved by shortening the crop growth cycles and producing immature seeds (Carandang et al., 2006). The main objective of RGA is to reduce time required to develop lines for breeding program. RGA is superior to other approaches in terms of speed, technical simplicity, cost and logistic requirement. It reduces the time for variety development through a stringent selection cycle and thereby enhances the genetic gain. An array of methods can be employed for RGA to fast-track crop breeding. Therefore, the current context aimed for a comprehensive discussion of various breeding schemes which allow us to shorten the overall time required for varietal developmental process.

Fig 1: Rapid generation advancement to meet the global food demand.


 
Single seed descent method
 
Single seed descent (SSD) method is a modification of bulk breeding method for handling segregating populations. SSD method mainly targets at maintaining maximum possible genotypes from the original segregating populations by avoiding early generation selections and thereby creating a large genetic variation among the individual homozygous lines after F6 or later generations (Brim, 1966). In SSD method, following crossing two suitable parents, the F1 generation is grown to generate F2 generation from where a single seed from each plant is selected and bulked seeds to grow the next generation. The same process is repeated up to F6 or F7 generation to obtain nearly homozygous lines. Furthermore, it allows off-season nurseries to advance segregating material rapidly by taking two to three or even more generations in a single year to attain desired level of homozygosity. The F1 generation is grown in the field for obtaining F2 seeds followed by subsequent generation’s advancement in off-season nurseries. SSD method allows the maintenance of maximum amount of genetic diversity and thereby permits breeder for development of recombinant inbred lines (RILs). As a routine practice, development of RILs can be hastened by growing three generations in a single year (Gaur et al., 2007). For instance, the application of SSD method in rapid generation advance has been undertaken in rice breeding for advancing the breeding materials (Ikehashi and Hille Rislambers 1977). Currently, SSD method is being used for RGA for breeding rice varieties conducted by IRRI, Philippines for photoperiod sensitivity, cold and submergence tolerance (Suh et al., 2003; Sarkar et al., 2021).
 
Speed breeding
 
Speed breeding is another novel approach that can be followed for long day to day-neutral crops. This technique involves extending photoperiod and controlled conditions such as temperature, soil media and appropriate spacing in glasshouses to shorten breeding cycles, thereby leading to RGA. With speed breeding, almost three to nine generations can be grown in a year, as compared to one to two generations per year in case of conventional method (Ghosh et al., 2018). Thus, it promotes rapid development of stable and homozygous genotypes to facilitate development and release of new crop varieties (Watson et al., 2018). The original concept of speed breeding came from NASA having an objective to grow crops quickly in space. This method may include manipulation of temperature and photoperiod regime, soil moisture, high-density planting, modification of composition of media (nutrients and minerals), use of plant growth regulators and often increasing the level of carbon dioxide in the growth chambers for promoting quick growth from vegetative to reproductive stage (Mobini et al., 2015; Jagadish et al., 2018). Generally, light of 400-700 nm wavelength with LED is used with temperature 22oC/ 17oC for 22 hours supplemented with an alternating 2 hours darkness under 60-70% relative humidity condition. Speed breeding is highly amenable to phenotypic selection for different traits. Several quantitative traits including leaf rust and collar rot in durum wheat were screened using this method (Alahmad et al., 2018) and also amenable for rapid introgression of multiple disease resistance in barley (Hickey et al., 2017). However, conventional selection methods viz, pedigree, bulk and recurrent selection can hardly be used in speed breeding as it does not allow breeders to exert their skill in the selection process. Hence, single plant selection (SPS), single seed descent (SSD) and single pod descent (SPD) may be merged with speed breeding for RGA (Wanga et al., 2021).
 
Shuttle breeding
 
During the phenological stages, crop plants are exposed to several types of stress conditions, like salinity, drought, nutrient deficiency or toxicity, diseases and pest attacks. Therefore, for evaluation of breeding lines for tolerance to these stresses, early generation breeding materials should be exposed to these actual stress environments, if not available in the breeding station. In this context, the concept of shuttle breeding originated from this criterion to evaluate the lines rapidly by shuttling in other locations to facilitate faster development of cultivars with the ability to adapt to those environments (Khush, 1989). Many international institutes including IRRI used this method for crop breeding in collaboration with other partner organizations. In shuttle breeding, selected improved variety or good parental lines are crossed with a locally adapted parent to generate F1 progenies which are grown at experimental station followed by raising F2 generation in the targeted environment where the materials were exposed to the desired stress conditions. Subsequently, better performing adapted lines are selected to obtain F3 generation. In subsequent generations, grain yield and quality are evaluated to select desired segregants having tolerance to stress environments (IRRI 1985). Using this approach, varietal improvement was done in rice under lowland rice growing ecosystem in eastern India (Singh et al., 1998; Mallik et al., 2002). In shuttle breeding, crop cycle can also be maintained in off-season by planting the crop in multiple field locations. Alongside yield and grain quality, this method improves selection efficacy to a particular environmental condition, including diseases, pests and climate. It was primarily designed by CIMMYT and later also used by Dr. Norman Borlaug for development of superior lines in wheat.
 
Doubled haploidy
 
Doubled haploidy is one of the most fascinating tools in plant breeding where haploid set chromosomes are doubled to get diploids, hence called doubled haploids (DH). This can help to obtain completely homozygous lines in just 1-2 years by colchicine treatment to double the chromosome sets. Haploid plants may be obtained through tissue culture techniques like anther, pollen culture (Heberle-Bors 1989) or ovule culture (Keller and Korzun 1996) or by chromosome elimination method using Bulbosum technique in barley (Ho and Kasha 1975) and haploid inducer lines like in maize (Chaikam et al., 2019). Although apparently looks easy, many crops are not amenable to tissue culture and regeneration protocol is not yet available. Artificial chromosome duplication is accomplished by treating with chemicals that restrict mitotic activity of the haploid seedlings. For this purpose, colchicine is most widely used for artificial chromosome doubling in DH development pipelines (Chaikam et al., 2019). Colchicine treated seedlings generally show lack of microtubules in the meristematic cells of the shoot apex during mitosis as colchicine binds to β-tubulin forming tubulin dimers resulting in prevention of chromosome separation towards the polar region.
 
Genomic selection
 
Genomic Selection (GS) is a form of marker assisted selection (MAS) that simultaneously estimate the effects associated with all the marker loci covering the entire genome, irrespective of whether the effects are significant or not and selects favorable individuals based on genomic estimated breeding values (GEBVs) (Crossa et al., 2017). GS uses a ‘training population’ of individuals that have been genotyped and phenotyping is done to build a model to estimate marker effects which in turn is used to predict GEBVs. It has been predicted for over two decades that molecular marker technology would reshape breeding programs and facilitate rapid gains from selection. Despite important strides in marker technologies, the use of MAS has stagnated for the improvement of quantitative traits. Current MAS methods are effective for the manipulation of large effect alleles with known association to a marker, but ineffective for small effect alleles of quantitative traits. However, in GS, GEBVs say nothing about the function of the underlying genes but they are used as selection criterion. A key to the success of GS is that it incorporates all marker information in the prediction model, thereby avoiding biased marker effect estimates and capturing even small-effect QTLs (Cerrudo et al., 2018). Several statistical approaches viz., Step-wise regression, Ridge regression-best linear unbiased prediction (RR-BLUP) and a Bayesian regression, kernel regression and non-parametric regression models have been proposed for the prediction of GEBVs. The accuracy of GS prediction methods is largely affected by various factors. GS is expected to accelerate the breeding cycle (selection gain per unit time) and change the role of phenotyping. GS may be regarded as a potent, attractive and valuable approach for plant breeding that leads to the next phase of MAS. Machine learning (ML) is a field of computer science that uses algorithms and existing samples to capture characteristics of target patterns. Several ML methods like Artificial Neural Network (ANN), Convolutional Neural Networks (CNN), Multilayer Perceptron (MLP), random forest (RF), Support Vector Machines (SVM), Radial Basis Function Neural Network (RBFNN) could be applied in GS for estimating the GEBV along with higher order interaction (Gonzalez-Camacho et al., 2018). Haploid breeding pipeline conjugated with GS in CIMMYT has revolutionized the Maize Breeding.
 
Marker assisted breeding
 
Conventional breeding mostly utilizes phenotypic evaluation for a trait of interest. This is often inefficient, time consuming, biased, destructive, dependent on threshold conditions and specific to developmental stages. Marker assisted selection is one of the means of indirect selection where a desirable allele or quantitative trait loci (QTLs) are selected based on some markers tightly linked to it (Soller and Beckmann 1983; Das et al., 2022). The use of molecular markers helps to select the desired ones more efficiently, thereby reducing time as compared to conventional methods which usually take several years for phenotype-based selection (Frisch and Melchinger, 2005; Dutta et al., 2020a, 2021a and b). Marker assisted backcrossing is a process of incorporating traits into a well-established variety with the help of molecular markers for selection for the target trait and simultaneously recovery of the recurrent parental genome (Jiang, 2015). Marker assisted backcross breeding efficiently detects targeted trait or QTL with maximum recovery of recurrent parent genome. Plant breeders regularly use marker assisted backcross breeding to integrate various traits like grain yield and submergence tolerance (Pandit et al., 2021), fertility restorer gene (Ponnuswamy et al., 2020), disease resistance like for bacterial blight in rice (Sundaram et al., 2011). By employing this method, selection of desired plants can be done more rapidly, thereby reducing time required for varietal improvement. Furthermore, marker assisted backcrossing can be used for gene pyramiding and breeding for tolerance or resistance to abiotic and biotic stresses.
 
Genome editing in plant breeding
 
The ability to precisely edit DNA sequences within the genome of living cells has been a major challenge for past few decades (Adli 2018). Precision genome editing, including altering single bases, is become a versatile tool to accelerate crop improvement worldwide (Zhang et al., 2018). RNA guided CRISPR-associated (Cas) nucleases have been used to achieve this goal in various major crops ranging from cereals (Hillary and Ceasar 2019; Ansari et al., 2020), pulses (Wang et al., 2017), oilseeds (Jiang et al., 2017) and horticultural crops (Karkute et al., 2017). Genome editing primarily occurs due to double strand breakage followed by cellular repair responses like non-homologous end joining and microhomology-mediated end joining (Jeggo et al., 1998; Rouet et al., 1994). In addition, precise DNA editing can also be achieved through cellular homology-directed repair by supplementing exogenously supplied DNA template with desired DNA change flanked by sequence homologous to the regions upstream and downstream of the double strand break (Rudin et al., 1989; Rouet et al., 1994). Additionally, the edited line can further be utilized in studying the function of a particular gene family spatially and temporally across the species (Dutta 2018; Dutta et al., 2019 a and b).
The use of molecular techniques and genomics in modern plant breeding has made selection easier, indirect and more accurate than traditional crop breeding. Rapid generation advances can accelerate the development of high-yielding cultivars by reducing the number of selection cycles and thereby enhancing genetic gain. Integration of speed breeding and other methods with marker assisted breeding and/or genomics assisted breeding can further reduce the time and make selection for novel traits like nutritional qualities, resistance of diseases and pests and tolerance to abiotic stresses more efficient. Speed breeding with employing embryo culture and crop management practices, like irrigation, control of temperature and light can reduce generation cycles in wheat and barley (Zheng et al., 2013). They showed that maximum of 8 generations per year in wheat and 9 generations per year in barley can be achieved by employing speed breeding techniques. RGA methods enabling speed breeding may lead to growing up to Seven generations per year in case of chickpea (Samineni et al., 2020). These methods advance generations with sufficient genetic diversity that may lead to rapid development of RILs and NILs as compared to conventional methods. It was reported that increased flower development in some crops like peanut was achieved by SSD under a controlled environment (OConnor et al., 2013). However, lack of infrastructure, funding and trained human resources are the major constraints towards adoption of RGA methods to fast-track crop breeding.
Swarnadip Ghosh, Abhik Roy and Suman Dutta drafted the article; Swarnadip Ghosh and Suman Dutta reviewed the manuscript; Swarnadip Ghosh and Suman Dutta conceptualized the article.
SG and AR are thankful to ICAR-Junior Research Fellowship (JRF) for pursuing the master’s programme. SD acknowledges Human Resource Development Group (HRDG) division of Council of Scientific and Industrial Research (CSIR), New Delhi, India for JRF to pursue the Ph.D. programme. 
The authors declare no conflict of interest.

  1. Adli, M. (2018). The CRISPR tool kit for genome editing and beyond. Nature communications. 9(1): 1-13.

  2. Alahmad, S., Dinglasan, E., Leung, K.M., Riaz, A., Derbal, N., Voss- Fels, K.P., Able, J.A., Bassi, F.M., Christopher, J. and Hickey, L.T. (2018). Speed breeding for multiple quantitative traits in durum wheat. Plant methods. 14(1): 1-15.

  3. Ansari, W.A., Chandanshive, S.U., Bhatt, V., Nadaf, A.B., Vats, S., Katara, J.L., Sonah, H. and Deshmukh, R. (2020). Genome editing in cereals: approaches, applications and challenges.  International Journal of Molecular Sciences. 21(11): 4040.

  4. Brim, C.A. (1966). A modified pedigree method of selection in soybeans 1. Crop science. 6(2): 220-220.

  5. Carandang, F.M., Sundar, S. and Carpena, A.L. (2006). Rapid generation advancement in soyabeans using immature seeds. Philippine Journal of Crop Science. 31(2): 53-59.

  6. Cerrudo, D., Cao, S., Yuan, Y., Martinez, C., Suarez, E.A., Babu, R., Zhang, X. and Trachsel, S. (2018). Genomic selection outperforms marker assisted selection for grain yield and physiological traits in a maize doubled haploid population across water treatments. Frontiers in Plant Science. 9: 366. https://doi.org/10.3389/fpls.2018.00366.

  7. Chaikam, V., Molenaar, W., Melchinger, A.E. and Boddupalli, P.M. (2019). Doubled haploid technology for line development in maize: technical advances and prospects. Theoretical and Applied Genetics. 132(12): 3227-3243.

  8. Crossa, J., Pérez-Rodríguez, P., Cuevas, J., Montesinos-López, O., Jarquín, D., De Los Campos, G., Burgueño, J., González- Camacho, J.M., Pérez-Elizalde, S., Beyene, Y. and Dreisigacker, S. (2017). Genomic selection in plant breeding: methods, models and perspectives. Trends in plant science. 22(11): 961-975.

  9. Das, A., Singh, S., Islam, Z., Munshi, A.D., Behera, T.K., Dutta, S., Weng, Y. and Dey, S.S. (2022). Current progress in genetic and genomics-aided breeding for stress resistance in cucumber (Cucumis sativus L.). Scientia Horticulturae. 300: 111059. https://doi.org/10.1016/j.scienta.2022.111059.

  10. Dutta, S. (2018). Analysis of genetic variability and validation of candidate gene (s) affecting retention of kernel carotenoids in maize during storage (Post graduate dissertation, Division of Genetics ICAR-Indian Agricultural Research Institute New Delhi.

  11. Dutta, S., Muthusamy, V., Chhabra, R., Baveja, A., Zunjare, R.U., Mondal, T.K., Yadava, D.K. and Hossain, F. (2021a). Low expression of carotenoids cleavage dioxygenase 1 (ccd1) gene improves the retention of provitamin-A in maize grains during storage. Molecular Genetics and Genomics. 296(1): 141-153.

  12. Dutta, S., Muthusamy, V., Chhabra, R., Zunjare, R.U. and Hossain, F. (2019a). Characterization of diverse provitamin: A rich inbreds for lipoxygenase (LOXs) gene governing oxidative deterioration in maize. IJCS. 7(5): 841-846.

  13. Dutta, S., Muthusamy, V., Hossain, F., Baveja, A., Abhijith, K.P., Saha, S., Zunjare, R.U. and Yadava, D.K. (2021b). Effect of storage period on provitamin A carotenoids retention in biofortified maize hybrids. International Journal of Food Science and Technology. 56(7): 3148-3156.

  14. Dutta, S., Muthusamy, V., Hossain, F., Baveja, A., Chhabra, R., Jha, S.K., Yadava, D.K. and Zunjare, R.U. (2020a). Analysis of genetic variability for retention of kernel carotenoids in sub-tropically adapted biofortified maize under different storage conditions. Journal of Cereal Science. 93: 102987.

  15. Dutta, S., Muthusamy, V., Zunjare, R.U. and Hossain, F. (2019b). Analysis of paralogous genes of carotenoid dioxygenase affecting carotenoid biosynthesis pathway in maize (Zea mays L.). Journal of Pharmacognosy and Phytochemistry. 8(2): 524-530.

  16. Frisch, M. and Melchinger, A.E. (2005). Selection theory for marker- assisted backcrossing. Genetics. 170(2): 909-917.

  17. Gaur, P.M., Samineni, S., Gowda, C.L.L. and Rao, B.V. (2007). Rapid generation advancement in chickpea. Journal of SAT Agricultural Research. 3(1).

  18. Ghosh, S., Watson, A., Gonzalez-Navarro, O.E., Ramirez-Gonzalez, R.H., Yanes, L., Mendoza-Suárez, M., Simmonds, J., Wells, R., Rayner, T., Green, P. and Hafeez, A. (2018). Speed breeding in growth chambers and glasshouses for crop breeding and model plant research. Nature protocols. 13(12): 2944-2963.

  19. Gonzalez-Camacho, J.M., Ornella, L., Pérez-Rodríguez, P., Gianola, D., Dreisigacker, S. and Crossa, J. (2018). Applications of machine learning methods to genomic selection in breeding wheat for rust resistance.

  20. Heberle-Bors, E. (1989). Isolated pollen culture in tobacco: plant reproductive development in a nutshell. Sexual Plant Reproduction. 2(1): 1-10.

  21. Hickey, L.T., Germán, S.E., Pereyra, S.A., Diaz, J.E., Ziems, L.A., Fowler, R.A., Platz, G.J., Franckowiak, J.D. and Dieters, M.J. (2017). Speed breeding for multiple disease resistance in barley. Euphytica. 213(3): 64.

  22. Hillary, V.E. and Ceasar, S.A. (2019). Application of CRISPR/Cas9 Genome Editing System in Cereal Crops. The Open Biotechnology Journal. 13(1).

  23. Ho, K.M. and Kasha, K.J. (1975). Genetic control of chromosome elimination during haploid formation in barley. Genetics. 81(2): 263-275.

  24. Ikehashi, H. and Hille Rislambers, D. (1977). Single Seed Descent with the Use of Rapid Generation Advance [a Guide to a Modified Rice Breeding Procedure]. In: International Rice Research Conference, College, Laguna (Philippines). 18 Apr 1977.

  25. IRRI-International Rice Research Institute (1985) Annual report for 1984. P.O. Box 933, Manila, Philippines. 504.

  26. Jagadish, S.V., Bahuguna, R.N., Djanaguiraman, M., Gamuyao, R., Prasad, P.V. and Craufurd, P.Q. (2016). Implications of high temperature and elevated CO2 on flowering time in plants. Frontiers in Plant Science. 7: 913. DOI:10.3389/ fpls.2016.00913.

  27. Jeggo, P.A. (1998). 5 DNA Breakage and Repair. Advances in genetics, 38: 185-218.

  28. Jiang, G.L. (2015). Molecular marker-assisted breeding: a plant breeder’s review. In Advances in plant breeding strategies: breeding, biotechnology and molecular tools. 431-472: Springer, Cham.

  29. Jiang, W.Z., Henry, I.M., Lynagh, P.G., Comai, L., Cahoon, E.B. and Weeks, D.P. (2017). Significant enhancement of fatty acid composition in seeds of the allohexaploid, Camelina sativa, using CRISPR/Cas9 gene editing. Plant biotechnology journal. 15(5): 648-657.

  30. Karkute, S.G., Singh, A.K., Gupta, O.P., Singh, P.M. and Singh, B. (2017). CRISPR/Cas9 mediated genome engineering for improvement of horticultural crops. Frontiers in plant science. 8: 1635. https://doi.org/10.3389/fpls.2017.01635.

  31. Keller, E.J. and Korzun, L. (1996). Ovary and ovule culture for haploid production. In In vitro haploid production in higher plants. 217-235. Springer, Dordrecht.

  32. Khush, G.S. (1989). Innovative approaches to rice improvement. In Rice Farming Systems: New Directions: Proceedings of an International Symposium 31 January-3 February 1987, Rice Research and Training Center, Sakha, Egypt. Int. Rice Res. Inst. 4: 71-78.

  33. Li, H., Rasheed, A., Hickey, L.T. and He, Z. (2018). Fast-forwarding genetic gain. Trends in Plant Science. 23(3): 184-186.

  34. Mallik, S., Mandal, B.K., Sen, S.N. and Sarkarung, S. (2002). Shuttle-breeding: An effective tool for rice varietal improvement in rainfed lowland ecosystem in eastern India. Current Science. 83(9): 1097-1102.

  35. Mobini, S.H., Lulsdorf, M., Warkentin, T.D. and Vandenberg, A. (2015). Plant growth regulators improve in vitro flowering and rapid generation advancement in lentil and faba bean. In Vitro Cellular and Developmental Biology-Plant. 51(1): 71-79.

  36. OConnor, D.J., Wright, G.C., Dieters, M.J., George, D.L., Hunter, M.N., Tatnell, J.R. and Fleischfresser, D.B. (2013). Development and application of speed breeding technologies in a commercial peanut breeding program. Peanut Science. 40(2): 107-114.

  37. Pandit, E., Pawar, S., Barik, S.R., Mohanty, S.P., Meher, J. and Pradhan, S.K. (2021). Marker-assisted backcross breeding for improvement of submergence tolerance and grain yield in the popular rice variety ‘Maudamani’. Agronomy. 11(7): 1263.

  38. Ponnuswamy, R., Singh, A.K., Raman, M.S., venkata Subbarao, L. and Neeraja, C.N. (2020). Conversion of partial restorer Swarna into restorer by transferring fertility restorer Rf gene (s) through marker assisted back cross breeding (MABB) in rice. Scientific Reports. 10(1): 1-14.

  39. Rouet, P., Smih, F. and Jasin, M. (1994). Introduction of double- strand breaks into the genome of mouse cells by expression of a rare-cutting endonuclease. Molecular and cellular biology. 14(12): 8096-8106.

  40. Rudin, N., Sugarman, E. and Haber, J.E. (1989). Genetic and physical analysis of double-strand break repair and recombination in Saccharomyces cerevisiae. Genetics. 122(3): 519-534.

  41. Samineni, S., Sen, M., Sajja, S.B. and Gaur, P.M. (2020). Rapid generation advance (RGA) in chickpea to produce up to seven generations per year and enable speed breeding. The Crop Journal. 8(1): 164-169.

  42. Sarkar, R.K., Reddy, J.N. and Das, S.R. (2021). Molecular breeding for improving flooding tolerance in rice: Recent progress and future perspectives. Molecular Breeding for Rice Abiotic Stress Tolerance and Nutritional Quality. 75-91. https://doi.org/10.1002/9781119633174.ch4.

  43. Singh, S., Singh, O.N., Singh, R.K., Sarkarung, S., El Bassam, N., Behl, R.K. and Prochnow, B. (1998). A shuttle breeding approach to rice improvement for rainfed lowland eco- system in eastern India.

  44. Soller, M. and Beckmann, J.S. (1983). Genetic polymorphism in varietal identification and genetic improvement. Theoretical and Applied Genetics. 67(1): 25-33.

  45. Suh, J.P., Ahn, S.N., Suh, H.S., Moon, H.P. and Choi, H.C. (2003). Identifying QTLs for cold tolerance-related traits in a Korean weedy rice. In Advances in Rice Genetics. 2:  291-294.

  46. Sundaram, R.M., Laha, G.S., Viraktamath, B.C., Sujatha, K., Natarajkumar, P., Hari, Y., Srinivasa Rao, K., Reddy, C.S., Balachandran, S.M., Madhav, M.S. and Hajira, S.K. (2011). Marker assisted breeding for development of bacterial blight resistant rice. Genomics and Crop Improvement:  Relevance and Reservations, Institute of Biotechnology, Acharya NG Ranga Agricultural University, Hyderabad. 500(030): 154-182.

  47. Wang, L., Wang, L., Zhou, Y. and Duanmu, D. (2017). Use of CRISPR/Cas9 for symbiotic nitrogen fixation research in legumes. Progress in molecular biology and translational science. 149: 187-213.

  48. Wanga, M.A., Shimelis, H., Mashilo, J. and Laing, M.D. (2021). Opportunities and challenges of speed breeding: A review. Plant Breeding. 140(2): 185-194.

  49. Watson, A., Ghosh, S., Williams, M.J., Cuddy, W.S., Simmonds, J., Rey, M.D., Hatta, M.A.M., Hinchliffe, A., Steed, A., Reynolds, D. and Adamski, N.M. (2018). Speed breeding is a powerful tool to accelerate crop research and breeding. Nature Plants. 4(1): 23-29.

  50. Zhang, Y., Massel, K., Godwin, I.D. and Gao, C. (2018). Applications and potential of genome editing in crop improvement. Genome biology. 19(1): 1-11.

  51. Zheng, Z., Wang, H.B., Chen, G.D., Yan, G.J. and Liu, C.J. (2013). A procedure allowing up to eight generations of wheat and nine generations of barley per annum. Euphytica. 191(2): 311-316.

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