[ 1 ] Taubenhaus JJ, Ezekiel WN, Neblette CB. Airplane photography in the study of cotton root rot. Phytopathology 1929;19(6):1025–9. 链接1

[ 2 ] Colwell RN. Determining the prevalence of certain cereal crop diseases by means of aerial photography. Hilgardia 1956;26(5):223–86. 链接1

[ 3 ] Myers VI. Remote sensing applications in agriculture. In: Colwell RN, editor. Manual of remote sensing. Bethesda: American Society of Photogrammetry and Remote Sensing; 1983. p. 2111–228. 链接1

[ 4 ] Ryerson RA, Curran PJ, Stephens PR. Applications: agriculture. In: Philipson WR, editor. Manual of photographic interpretation. Bethesda: American Society for Photogrammetry and Remote Sensing; 1997. p. 365–97. 链接1

[ 5 ] Nixon PR, Escobar DE, Bowen RL. A multispectral false-color video imaging system for remote sensing applications. In: Proceedings of the 11th Biennial Workshop on Color Aerial Photography and Videography in the Plant Sciences and Related Fields; 1987 Apr 27–May 1; Weslaco, TX, USA. Bethesda: American Society for Photogrammetry and Remote Sensing; 1987. p. 295–305,340. 链接1

[ 6 ] Cook CG, Escobar DE, Everitt JH, Cavazos I, Robinson AF, Davis MR. Utilizing airborne video imagery in kenaf management and production. Ind Crops Prod 1999;9(3):205–10. 链接1

[ 7 ] Fletcher RS, Skaria M, Escobar DE, Everitt JH. Field spectra and airborne digital imagery for detecting Phytophthora foot rot infections in citrus trees. HortScience 2001;36(1):94–7. 链接1

[ 8 ] Zhang M, Qin Z, Liu X. Remote sensed spectral imagery to detect late blight in field tomatoes. Precis Agric 2005;6(6):489–508. 链接1

[ 9 ] Yang C, Fernandez CJ, Everitt JH. Mapping Phymatotrichum root rot of cotton using airborne three-band digital imagery. Trans ASABE 2005;48(4):1619–26. 链接1

[10] Huang W, Lamb DW, Niu Z, Zhang Y, Liu L, Wang J. Identification of yellow rust in wheat using in-situ spectral reflectance measurements and airborne hyperspectral imaging. Precis Agric 2007;8(4–5):187–97. 链接1

[11] MacDonald SL, Staid M, Staid M, Cooper ML. Remote hyperspectral imaging of grapevine leafroll-associated virus 3 in cabernet sauvignon vineyards. Comput Electron Agric 2016;130:109–17. 链接1

[12] Lu J, Zhou M, Gao Y, Jiang H. Using hyperspectral imaging to discriminate yellow leaf curl disease in tomato leaves. Precis Agric 2018;19(3):379–94. 链接1

[13] Du Q, French JV, Skaria M, Yang C, Everitt JH. Citrus pest stress monitoring using airborne hyperspectral imagery. In: Proceedings of the International Geoscience and Remote Sensing Symposium; 2004 Sep 20–24; Anchorage, AK, USA. New York: IEEE; 2004. p. 3981–4. 链接1

[14] Yang C, Fernandez CJ, Everitt JH. Comparison of airborne multispectral and hyperspectral imagery for mapping cotton root rot. Biosyst Eng 2010;107 (2):131–9. 链接1

[15] Kumar A, Lee WS, Ehsani RJ, Albrigo LG, Yang C, Mangan RL. Citrus greening disease detection using aerial hyperspectral and multispectral imaging techniques. J Appl Remote Sens 2012;6(1):063542. 链接1

[16] Li H, Lee WS, Wang K, Ehsani R, Yang C. ‘Extended spectral angle mapping (ESAM)’ for citrus greening disease detection using airborne hyperspectral imaging. Precis Agric 2014;15(2):162–83. 链接1

[17] Chen X, Ma J, Qiao H, Cheng D, Xu Y, Zhao Y. Detecting infestation of take-all disease in wheat using Landsat Thematic Mapper imagery. Int J Remote Sens 2007;28(22):5183–9. 链接1

[18] Franke J, Menz G. Multi-temporal wheat disease detection by multi-spectral remote sensing. Precis Agric 2007;8(3):161–72. 链接1

[19] Santoso H, Gunawan T, Jatmiko RH, Darmosarkoro W, Minasny B. Mapping and identifying basal stem rot disease in oil palms in North Sumatra with QuickBird imagery. Precis Agric 2011;12(2):233–48. 链接1

[20] Yuan L, Pu R, Zhang J, Wang J, Yang H. Using high spatial resolution satellite imagery for mapping powdery mildew at a regional scale. Precis Agric 2016;17 (3):332–48. 链接1

[21] Li X, Lee WS, Li M, Ehsani R, Mishra AR, Yang C, et al. Feasibility study on huanglongbing (citrus greening) detection based on WorldView-2 satellite imagery. Biosyst Eng 2015;132:28–38. 链接1

[22] Garcia-Ruiz F, Sankaran S, Maja JM, Lee WS, Rasmussen J, Ehsani R. Comparison of two aerial imaging platforms for identification of huanglongbing-infected citrus trees. Comput Electron Agric 2013;91:106–15. 链接1

[23] Albetis J, Duthoit S, Guttler F, Jacquin A, Goulard M, Poilvé H, et al. Detection of Flavescence dorée grapevine disease using unmanned aerial vehicle (UAV) multispectral imagery. Remote Sens 2017;9(4):308. 链接1

[24] Mattupalli C, Moffet CA, Shah KN, Young CA. Supervised classification of RGB aerial imagery to evaluate the impact of a root rot disease. Remote Sens 2018;10(6):917. 链接1

[25] Yang C, Odvody GN, Thomasson JA, Isakeit T, Nichols RL. Change detection of cotton root rot infection over 10-year intervals using airborne multispectral imagery. Comput Electron Agric 2016;123:154–62. 链接1

[26] Yang C, Odvody GN, Thomasson JA, Isakeit T, Minzenmayer RR, Drake DR, et al. Site-specific management of cotton root rot using airborne and high resolution satellite imagery and variable rate technology. Trans ASABE 2018;61 (3):849–58. 链接1

[27] Escobar DE, Everitt JH, Noriega JR, Davis MR, Cavazos I. A true digital imaging system for remote sensing applications. In: Proceedings of the 16th Biennial Workshop on Color Photography and Videography in Resource Assessment; 1997 Apr 29–May 1, Weslaco, TX, USA. Bethesda: American Society for Photogrammetry and Remote Sensing; 1997. p. 470–84. 链接1

[28] Yang C. A high-resolution airborne four-camera imaging system for agricultural applications. Comput Electron Agric 2012;88:13–24. 链接1

[29] Yang C, Odvody GN, Fernandez CJ, Landivar JA, Minzenmayer RR, Nichols RL. Evaluating unsupervised and supervised image classification methods for mapping cotton root rot. Precis Agric 2015;16(2):201–15. 链接1

[30] Bramley RGV. Lessons from nearly 20 years of precision agriculture research, development, and adoption as a guide to its appropriate application. Crop Pasture Sci 2009;60(3):197–217. 链接1

[31] Schimmelpfennig D, Ebel R. On the doorstep of the information age: recent adoption of precision agriculture. Washington, DC: USDA Economic Research Service; 2011. 链接1

[32] Zhang Q. Precision agriculture technology for crop farming. Boca Raton: CRC Press; 2016. 链接1