Genetic variation in N-use efficiency and associated traits in Indian wheat cultivars

Nehe, Ajit; Misra, Satish Chandra; Murchie, Erik H.; Chinnathambi, Kannan; Foulkes, M. J.

doi:10.1016/j.fcr.2018.06.002

Cited by 51 publications

(58 citation statements)

References 38 publications

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“…Adapazarı may have better soil conditions, with higher total available nitrogen. As we reported for spring wheat [25], if nitrogen-utilization efficiency (grain dry matter yield per unit of crop nitrogen uptake at harvest) is constant, then any higher nitrogen or protein content in the grain is related to higher nitrogen uptake by the plant. Adapazarı also benefits from a relatively longer growing period, longer grain filling period, probably deeper root system, and higher nitrogen take-up, resulting in better grain quality.…”

Section: Discussionmentioning

confidence: 89%

“…[22]. For this purpose, breeding programs in many countries select historical set of cultivars and study them in different environment to determine the genetic gains achieved through breeding and selection over particular breeding period [23–25]. Wheat genetic gains in Turkey have been recently summarized for irrigated winter wheat [26], rainfed winter wheat [27] and spring wheat [28].…”

Section: Introductionmentioning

confidence: 99%

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Genotype x environment interaction and genetic gain for grain yield and grain quality traits in Turkish spring wheat released between 1964 and 2010

et al. 2019

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The study was conducted to determine the effects of genotype (G), environment (E), their interaction (GEI) and genetic gain on yield and grain quality traits in Turkish spring wheat cultivars released between 1964 and 2010. We conducted a multi-environment trial at three testing locations: Adana, Adapazarı, and Izmir, during the 2009, 2011 and 2013 cropping seasons and tested 35 cultivars released by the respective breeding programs. Allelic variations of high and low molecular weight glutenin subunits (HMW-GS and LMW-GS) and 1B/1R translocation was also determined and evaluated in all cultivars. Comparing yield across three locations, Adana (6416 kg ha -1 ) yield was relatively higher than in Izmir (5887 kg ha -1 ) and Adapazarı (5205 kg ha -1 ) (P<0.001). Overall, GY was influenced by the varieties, testing location and breeding programs (P<0.001). Cultivars from Izmir breeding program performed relatively better (6174 kg ha -1 ) than those from Adana (5996 kg ha -1 ) and Adapazarı (5351 kg ha -1 ) (<0.001). We recommend Ziyabey-98, Menemen, and Basribey-95, for stable grain yield in spring wheat production across the studied regions because of their wide adaptability, and Pamukova-97 for future breeding to improve grain quality parameters. We found three breeding programs have successfully increased the grain yield and quality traits for 46 years. As a group, cultivars released after 2000 had the highest yield indicating breeding progress. Genetic gain for GY was 30.9 kg ha −1 per year from 1964 with annual increase compared to the yield of older cultivar Akova B-2 (4102 kg ha -1 ) which constitutes a 0.75% rate of genetic gain. Improvement in grain quality was related to change in protein composition rather than an increase in protein content whereas yield improvement seems to mainly be related to increases in test weight and 1000 kernel weight. High molecular weight glutenin subunit (HMW-GS) 5+10 showed an increase in frequency whereas 2+12 showed a decrease over the breeding period.

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Section: Discussionmentioning

confidence: 89%

Section: Introductionmentioning

confidence: 99%

Genotype x environment interaction and genetic gain for grain yield and grain quality traits in Turkish spring wheat released between 1964 and 2010

et al. 2019

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“…The N supply affects inflorescence development, panicle length, and the number of flowers per panicle ( Yoshida et al 2006 ; Makino, 2011 ). In wheat, N accumulation at anthesis was found to be positively correlated with the onset of flag-leaf senescence, and thus total N accumulated at anthesis is an important trait for enhancing grain yield and NUE under low to moderate N supply ( Nehe et al , 2018 ).…”

Section: Nitrogen Regulation Of Growth and Development In Different Pmentioning

confidence: 99%

How does nitrogen shape plant architecture?

Luo

Zhang

2020

Journal of Experimental Botany

132

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Plant nitrogen (N), acquired mainly in the form of nitrate and ammonium from soil, dominates growth and development, and high-yield crop production relies heavily on N fertilization. The mechanisms of root adaptation to altered supply of N forms and concentrations have been well characterized and reviewed, while reports concerning the effects of N on the architecture of vegetative and reproductive organs are limited and are widely dispersed in the literature. In this review, we summarize the nitrate and amino acid regulation of shoot branching, flowering, and panicle development, as well as the N regulation of cell division and expansion in shaping plant architecture, mainly in cereal crops. The basic regulatory steps involving the control of plant architecture by the N supply are auxin-, cytokinin-, and strigolactone-controlled cell division in shoot apical meristem and gibberellin-controlled inverse regulation of shoot height and tillering. In addition, transport of amino acids has been shown to be involved in the control of shoot branching. The N supply may alter the timing and duration of the transition from the vegetative to the reproductive growth phase, which in turn may affect cereal crop architecture, particularly the structure of panicles for grain yield. Thus, proper manipulation of N-regulated architecture can increase crop yield and N use efficiency.

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“…Low water and nutrient uptake efficiency of crops is one of the most detrimental limitation in agriculture productivity (Chuan et al, 2016;Lesk et al, 2016). Efficient irrigation and nitrogen (N) supply according to the plant requirement is a key regulator for resource-efficient crop yield (Christopher et al, 2016;Chuan et al, 2016;Nehe et al, 2018;Thorp et al, 2018). Amelioration in uptake efficiency can be adjusted by manipulation of dosage of water and N-fertilizer (Ali and Talukder, 2008) or by improving input use efficiency in crop cultivars (Hawkesford, 2017).…”

Section: Introductionmentioning

confidence: 99%

Assessment of Water and Nitrogen Use Efficiencies Through UAV-Based Multispectral Phenotyping in Winter Wheat

Yang

Hassan

et al. 2020

Front. Plant Sci.

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Unmanned aerial vehicle (UAV) based remote sensing is a promising approach for nondestructive and high-throughput assessment of crop water and nitrogen (N) efficiencies. In this study, UAV was used to evaluate two field trials using four water (T0 = 0 mm, T1 = 80 mm, T2 = 120 mm, and T3 = 160 mm), and four N (T0 = 0, T1 = 120 kg ha −1 , T2 = 180 kg ha −1 , and T3 = 240 kg ha −1) treatments, respectively, conducted on three wheat genotypes at two locations. Ground-based destructive data of water and N indictors such as biomass and N contents were also measured to validate the aerial surveillance results. Multispectral traits including red normalized difference vegetation index (RNDVI), green normalized difference vegetation index (GNDVI), normalized difference red-edge index (NDRE), red-edge chlorophyll index (RECI) and normalized green red difference index (NGRDI) were recorded using UAV as reliable replacement of destructive measurements by showing high r values up to 0.90. NGRDI was identified as the most efficient non-destructive indicator through strong prediction values ranged from R 2 = 0.69 to 0.89 for water use efficiencies (WUE) calculated from biomass (WUE.BM), and R 2 = 0.80 to 0.86 from grain yield (WUE.GY). RNDVI was better in predicting the phenotypic variations for N use efficiency calculated from nitrogen contents of plant samples (NUE.NC) with high R 2 values ranging from 0.72 to 0.94, while NDRE was consistent in predicting both NUE.NC and NUE.GY by 0.73 to 0.84 with low root mean square errors. UAV-based remote sensing demonstrates that treatment T2 in both water 120 mm and N 180 kg ha −1 supply trials was most appropriate dosages for optimum uptake of water and N with high GY. Among three cultivars, Zhongmai 895 was highly efficient in WUE and NUE across the water and N treatments. Conclusively, UAV can be used to predict time-series WUE and NUE across the season for selection of elite genotypes, and to monitor crop efficiency under varying N and water dosages.

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Genetic variation in N-use efficiency and associated traits in Indian wheat cultivars

Cited by 51 publications

References 38 publications

Genotype x environment interaction and genetic gain for grain yield and grain quality traits in Turkish spring wheat released between 1964 and 2010

Genotype x environment interaction and genetic gain for grain yield and grain quality traits in Turkish spring wheat released between 1964 and 2010

How does nitrogen shape plant architecture?

Assessment of Water and Nitrogen Use Efficiencies Through UAV-Based Multispectral Phenotyping in Winter Wheat

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