120 related articles for article (PubMed ID: 36803724)
1. [Hyperspectral monitoring on proline content in winter wheat under water stress].
Xie Y; Song J; Liu M; Meng W; Feng M; Wang C; Yang W; Qiao X; Yang C
Ying Yong Sheng Tai Xue Bao; 2023 Feb; 34(2):463-470. PubMed ID: 36803724
[TBL] [Abstract][Full Text] [Related]
2. Canopy hyperspectral characteristics and yield estimation of winter wheat (Triticum aestivum) under low temperature injury.
Xie Y; Wang C; Yang W; Feng M; Qiao X; Song J
Sci Rep; 2020 Jan; 10(1):244. PubMed ID: 31937859
[TBL] [Abstract][Full Text] [Related]
3. Hyperspectral prediction of leaf area index of winter wheat in irrigated and rainfed fields.
Li G; Wang C; Feng M; Yang W; Li F; Feng R
PLoS One; 2017; 12(8):e0183338. PubMed ID: 28817658
[TBL] [Abstract][Full Text] [Related]
4. Extraction of Sensitive Bands for Monitoring the Winter Wheat (Triticum aestivum) Growth Status and Yields Based on the Spectral Reflectance.
Wang C; Feng M; Yang W; Ding G; Xiao L; Li G; Liu T
PLoS One; 2017; 12(1):e0167679. PubMed ID: 28060827
[TBL] [Abstract][Full Text] [Related]
5. [Retrieval of leaf water content of winter wheat from canopy hyperspectral data using partial least square regression].
Wang YY; Li GC; Zhang LJ; Fan JL
Guang Pu Xue Yu Guang Pu Fen Xi; 2010 Apr; 30(4):1070-4. PubMed ID: 20545164
[TBL] [Abstract][Full Text] [Related]
6. Predicting grain protein content of field-grown winter wheat with satellite images and partial least square algorithm.
Tan C; Zhou X; Zhang P; Wang Z; Wang D; Guo W; Yun F
PLoS One; 2020; 15(3):e0228500. PubMed ID: 32160185
[TBL] [Abstract][Full Text] [Related]
7. [Response of winter wheat (Triticum aestivum L. ) hyperspectral characteristics to low temperature stress].
Ren P; Feng MC; Yang WD; Wang C; Liu TT; Wang HQ
Guang Pu Xue Yu Guang Pu Fen Xi; 2014 Sep; 34(9):2490-4. PubMed ID: 25532351
[TBL] [Abstract][Full Text] [Related]
8. [Estimation of Fraction of Absorbed Photosynthetically Active Radiation for Winter Wheat Based on Hyperspectral Characteristic Parameters].
Zhang C; Cai HJ; Li ZJ
Guang Pu Xue Yu Guang Pu Fen Xi; 2015 Sep; 35(9):2644-9. PubMed ID: 26669183
[TBL] [Abstract][Full Text] [Related]
9. Potential of Multivariate Statistical Technique Based on the Effective Spectra Bands to Estimate the Plant Water Content of Wheat Under Different Irrigation Regimes.
Sun H; Feng M; Xiao L; Yang W; Ding G; Wang C; Jia X; Wu G; Zhang S
Front Plant Sci; 2021; 12():631573. PubMed ID: 33719305
[TBL] [Abstract][Full Text] [Related]
10. [Using canopy hyperspectral ratio index to retrieve relative water content of wheat under yellow rust stress].
Jiang JB; Huang WJ; Chen YH
Guang Pu Xue Yu Guang Pu Fen Xi; 2010 Jul; 30(7):1939-43. PubMed ID: 20828004
[TBL] [Abstract][Full Text] [Related]
11. Comparison of new hyperspectral index and machine learning models for prediction of winter wheat leaf water content.
Zhang J; Zhang W; Xiong S; Song Z; Tian W; Shi L; Ma X
Plant Methods; 2021 Mar; 17(1):34. PubMed ID: 33789711
[TBL] [Abstract][Full Text] [Related]
12. [The spectral characteristics and chlorophyll content at winter wheat growth stages].
Sun H; Li MZ; Zhao Y; Zhang YE; Wang XM; Li XH
Guang Pu Xue Yu Guang Pu Fen Xi; 2010 Jan; 30(1):192-6. PubMed ID: 20302112
[TBL] [Abstract][Full Text] [Related]
13. UAV-based hyperspectral analysis and spectral indices constructing for quantitatively monitoring leaf nitrogen content of winter wheat.
Zhu H; Liu H; Xu Y; Guijun Y
Appl Opt; 2018 Sep; 57(27):7722-7732. PubMed ID: 30462034
[TBL] [Abstract][Full Text] [Related]
14. Hyperspectral Monitoring of Powdery Mildew Disease Severity in Wheat Based on Machine Learning.
Feng ZH; Wang LY; Yang ZQ; Zhang YY; Li X; Song L; He L; Duan JZ; Feng W
Front Plant Sci; 2022; 13():828454. PubMed ID: 35386677
[TBL] [Abstract][Full Text] [Related]
15. Detection of powdery mildew in two winter wheat plant densities and prediction of grain yield using canopy hyperspectral reflectance.
Cao X; Luo Y; Zhou Y; Fan J; Xu X; West JS; Duan X; Cheng D
PLoS One; 2015; 10(3):e0121462. PubMed ID: 25815468
[TBL] [Abstract][Full Text] [Related]
16. Hyperspectral Estimation Models of Winter Wheat Chlorophyll Content Under Elevated CO
Cai Y; Miao Y; Wu H; Wang D
Front Plant Sci; 2021; 12():642917. PubMed ID: 33841469
[TBL] [Abstract][Full Text] [Related]
17. [Study on the difference in canopy spectral reflectance and chlorophyll content of spring wheat at jointing stage in different land].
Jin YH; Xiong HG; Zhang F; Wang LF
Guang Pu Xue Yu Guang Pu Fen Xi; 2013 Apr; 33(4):1043-7. PubMed ID: 23841425
[TBL] [Abstract][Full Text] [Related]
18. [Comparative Research on Estimating the Severity of Yellow Rust in Winter Wheat].
Wang J; Jing YS; Huang WJ; Zhang JC; Zhao J; Zhang Q; Wang L
Guang Pu Xue Yu Guang Pu Fen Xi; 2015 Jun; 35(6):1649-53. PubMed ID: 26601384
[TBL] [Abstract][Full Text] [Related]
19. [Exploring novel hyperspectral band and key index for leaf nitrogen accumulation in wheat].
Yao X; Zhu Y; Feng W; Tian YC; Cao WX
Guang Pu Xue Yu Guang Pu Fen Xi; 2009 Aug; 29(8):2191-5. PubMed ID: 19839336
[TBL] [Abstract][Full Text] [Related]
20. Estimation of SPAD value in waterlogged winter wheat based on characteristic indices of hyperspectral and digital image.
Gao XM; Li YL; Lu BL; Xiong QX; Wu QX; Li JF
Ying Yong Sheng Tai Xue Bao; 2021 Mar; 32(3):959-966. PubMed ID: 33754562
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]