FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4386078689> ?p ?o ?g. }

• W4386078689 endingPage "108147" @default.
• W4386078689 startingPage "108147" @default.
• W4386078689 abstract "Plant nitrogen content (PNC) is vital for evaluating crop nitrogen nutrient status and for net primary productivity. Therefore, rapid and accurate acquisition of crop PNC information can help reduce fertilizer and increase efficiency in modern agriculture. This study investigated whether an optimized texture index constructed from hyperspectral characteristic wavelength images acquired from a unmanned aerial vehicle (UAV) may be used to estimate PNC in potatoes over multiple growth stages. A potato field trial conducted in 2019 in Beijing, China, included different planting densities, nitrogen fertilizer gradients, and potato varieties with three replicates. A UAV remote sensing platform served to acquire hyperspectral images during three critical N demand periods for potatoes. In addition, we simultaneously conducted field sampling to obtain ground-truth PNC measurements. Following the classical form of vegetation indices, 12 texture indices were constructed based on hyperspectral texture features, and an arbitrary variable combination optimization algorithm was used to optimize these indices. Finally, the texture index, which had the highest correlation with potato PNC, was used as the best indicator for estimating the PNC status of potato at multiple growth stages and whether this indicator, in combination with spectral information, could further improve the accuracy of potato PNC estimation was subsequently explored. The results showed that (i) the optimal texture index TTI3 (R494-Cor, R578-Hom, R514-Sem) maintained a good linear relationship with PNC at the late stage of potato growth, and the accuracy and stability of the PNC estimation models constructed based on it was significantly better than that of a single texture metric. (ii) Compared with spectral information alone, the texture index combined with spectral features improved the accuracy of potato PNC estimation. More specifically, TTI3 (R494-Cor, R578-Hom, R514-Sem) combined with the three-band spectral index TBI 5 (530, 734, 514) achieved the best estimation accuracy with calibrated R2, root mean square error (RMSE), and normalized RMSE of 0.77%, 0.28%, and 9.88%, respectively. The results of this study showed that the texture index constructed by combining multiple texture metrics enhanced the association between texture features and potato PNC over multiple growth stages, thus improving the monitoring accuracy of potato nitrogen nutrition status. This study can provide a reference for accurately managing crop nitrogen nutrition." @default.
• W4386078689 created "2023-08-23" @default.
• W4386078689 creator A5000200794 @default.
• W4386078689 creator A5004231524 @default.
• W4386078689 creator A5004660225 @default.
• W4386078689 creator A5013377352 @default.
• W4386078689 creator A5020713851 @default.
• W4386078689 creator A5039880991 @default.
• W4386078689 creator A5054846604 @default.
• W4386078689 creator A5067332063 @default.
• W4386078689 creator A5070653331 @default.
• W4386078689 creator A5090269831 @default.
• W4386078689 date "2023-09-01" @default.
• W4386078689 modified "2023-10-10" @default.
• W4386078689 title "Using an optimized texture index to monitor the nitrogen content of potato plants over multiple growth stages" @default.
• W4386078689 cites W1964217023 @default.
• W4386078689 cites W1969112481 @default.
• W4386078689 cites W1973680308 @default.
• W4386078689 cites W2001232772 @default.
• W4386078689 cites W2030106896 @default.
• W4386078689 cites W2036003376 @default.
• W4386078689 cites W2037708626 @default.
• W4386078689 cites W2037798659 @default.
• W4386078689 cites W2047454491 @default.
• W4386078689 cites W2070047344 @default.
• W4386078689 cites W2071915122 @default.
• W4386078689 cites W2091493105 @default.
• W4386078689 cites W2098630016 @default.
• W4386078689 cites W2102831150 @default.
• W4386078689 cites W2116730904 @default.
• W4386078689 cites W2118703810 @default.
• W4386078689 cites W2128438912 @default.
• W4386078689 cites W2167799103 @default.
• W4386078689 cites W2171747502 @default.
• W4386078689 cites W2539185528 @default.
• W4386078689 cites W2551562355 @default.
• W4386078689 cites W2786072233 @default.
• W4386078689 cites W2807715987 @default.
• W4386078689 cites W2808245662 @default.
• W4386078689 cites W2809791866 @default.
• W4386078689 cites W2891621712 @default.
• W4386078689 cites W2904950031 @default.
• W4386078689 cites W2920653747 @default.
• W4386078689 cites W2937578908 @default.
• W4386078689 cites W3007045993 @default.
• W4386078689 cites W3010955769 @default.
• W4386078689 cites W3011105383 @default.
• W4386078689 cites W3127244552 @default.
• W4386078689 cites W3151033386 @default.
• W4386078689 cites W3152977856 @default.
• W4386078689 cites W3162086186 @default.
• W4386078689 cites W4206254883 @default.
• W4386078689 cites W4210685960 @default.
• W4386078689 cites W4220785610 @default.
• W4386078689 cites W4281751969 @default.
• W4386078689 cites W4292471179 @default.
• W4386078689 cites W4306157663 @default.
• W4386078689 cites W4318305674 @default.
• W4386078689 cites W804512072 @default.
• W4386078689 doi "https://doi.org/10.1016/j.compag.2023.108147" @default.
• W4386078689 hasPublicationYear "2023" @default.
• W4386078689 type Work @default.
• W4386078689 citedByCount "1" @default.
• W4386078689 crossrefType "journal-article" @default.
• W4386078689 hasAuthorship W4386078689A5000200794 @default.
• W4386078689 hasAuthorship W4386078689A5004231524 @default.
• W4386078689 hasAuthorship W4386078689A5004660225 @default.
• W4386078689 hasAuthorship W4386078689A5013377352 @default.
• W4386078689 hasAuthorship W4386078689A5020713851 @default.
• W4386078689 hasAuthorship W4386078689A5039880991 @default.
• W4386078689 hasAuthorship W4386078689A5054846604 @default.
• W4386078689 hasAuthorship W4386078689A5067332063 @default.
• W4386078689 hasAuthorship W4386078689A5070653331 @default.
• W4386078689 hasAuthorship W4386078689A5090269831 @default.
• W4386078689 hasConcept C118518473 @default.
• W4386078689 hasConcept C120217122 @default.
• W4386078689 hasConcept C127413603 @default.
• W4386078689 hasConcept C154945302 @default.
• W4386078689 hasConcept C159078339 @default.
• W4386078689 hasConcept C159390177 @default.
• W4386078689 hasConcept C159750122 @default.
• W4386078689 hasConcept C168741863 @default.
• W4386078689 hasConcept C175963888 @default.
• W4386078689 hasConcept C18903297 @default.
• W4386078689 hasConcept C205649164 @default.
• W4386078689 hasConcept C25989453 @default.
• W4386078689 hasConcept C2780560099 @default.
• W4386078689 hasConcept C33923547 @default.
• W4386078689 hasConcept C39432304 @default.
• W4386078689 hasConcept C41008148 @default.
• W4386078689 hasConcept C62649853 @default.
• W4386078689 hasConcept C6557445 @default.
• W4386078689 hasConcept C86803240 @default.
• W4386078689 hasConcept C88463610 @default.
• W4386078689 hasConceptScore W4386078689C118518473 @default.
• W4386078689 hasConceptScore W4386078689C120217122 @default.
• W4386078689 hasConceptScore W4386078689C127413603 @default.
• W4386078689 hasConceptScore W4386078689C154945302 @default.

• next