000			03587nab a22004577a 4500
999			_c62498 _d62490
001			62498
003			MX-TxCIM
005			20231009164120.0
008			200212s2020 sz |||p|op||| 00| 0 eng d
022			_a1664-462X
024	8		_ahttps://doi.org/10.3389/fpls.2020.00927
040			_aMX-TxCIM
041			_aeng
100	0		_97724 _aMengjiao Yang
245	1	0	_aAssessment of water and nitrogen use efficiencies through UAV-based multispectral phenotyping in winter wheat
260			_aSwitzerland : _bFrontiers, _c2020.
500			_aPeer review
500			_aOpen Access
520			_aUnmanned aerial vehicle (UAV) based remote sensing is a promising approach for non-destructive 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 R2 = 0.69 to 0.89 for water use efficiencies (WUE) calculated from biomass (WUE.BM), and R2 = 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 R2 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.
526			_aWC _cFP2
546			_aText in English
650		7	_2AGROVOC _95218 _aNitrogen content
650		7	_2AGROVOC _93634 _aPhenotypes
650		7	_2AGROVOC _95833 _aVegetation index
650		7	_2AGROVOC _911401 _aUnmanned aerial vehicles
650		7	_2AGROVOC _911688 _aUse efficiency
650		7	_2AGROVOC _912723 _aMoisture content
650		7	_aWheat _gAGROVOC _2 _91310
700	1		_97723 _aHassan, M.A.
700	0		_911188 _aKaijie Xu
700	0		_915517 _aChengyan Zheng
700	1		_aAwais Rasheed _gGlobal Wheat Program _8I1706474 _91938
700	0		_91857 _aYong Zhang
700	0		_97725 _aXiuliang Jin
700	0		_9377 _aXianchun Xia
700	0		_91687 _aYonggui Xiao
700	1		_aHe Zhonghu _gGlobal Wheat Program _8INT2411 _9838
773	0		_dSwitzerland : Frontiers, 2020. _gv. 11, art. 927 _tFrontiers in Plant Science _x1664-462X _wu56875
856	4		_yOpen Access through DSpace _uhttps://hdl.handle.net/10883/20944
942			_2ddc _cJA _n0