Use of corn height measured with an acoustic sensor improves yield estimation with ground based active optical sensors

Computers and Electronics in Agriculture

Volumn 124, Issue , 2016, Pages 254-262

  Sharma, L K ^a   Bu, H ^b   Franzen, D W ^b   Denton, A ^c  

^a UNIVERSITY OF MAINE   (United States)

^b NORTH DAKOTA STATE UNIVERSITY   (United States)

^c North Dakota State University   (United States)

Author keywords

Acoustic height sensor; Active optical sensor; Corn height; Corn yield; NDVI

Indexed keywords

ACOUSTIC DEVICES; ACOUSTIC EQUIPMENT; ALGORITHMS; LOCATION; NITROGEN FERTILIZERS; OPTICAL SENSORS;

ACTIVE OPTICAL SENSORS; CORN HEIGHT; CORN YIELDS; HEIGHT SENSORS; NDVI;

ADAPTIVE OPTICS;

AGRICULTURAL TECHNOLOGY; ALGORITHM; BIOACOUSTICS; CANOPY ARCHITECTURE; CROP YIELD; ESTIMATION METHOD; EXPERIMENTAL DESIGN; FERTILIZER APPLICATION; HEIGHT; MAIZE; NDVI; OPTICAL METHOD; PREDICTION; SENSOR;

NORTH DAKOTA; UNITED STATES;

ZEA MAYS;

EID: 84964327174     PISSN: 01681699     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compag.2016.04.016     Document Type: Article

References (55)

1. Changgui Z., Wenyi F. Error effect of exterior orientation elements on tree height measurement using space intersection theory. J. Northeast Forest. Univ. 2007, 35:86-91.
2. Dammert P.B.G., Askne J. Interferometric tree height observations in boreal forests with SAR interferometry. Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, Seattle, WA, USA 1998, 1363-1366.
3. Fargo, N.D., Franzen, M.D., 2012. A Program for Categorizing Active-Optical Sensor Txt Data with Excel. Unpublished program. North Dakota St. Univ., Fargo, ND.
4. Franzen, D.W., 2010. North Dakota Fertilizer Tables and Equations. North Dakota St. Univ. Ext. Circ. SF-882.
5. Franzen, D.W., Wagner, G., Sims, A., 2003. Application of a ground-based sensor to determine N credits from sugarbeet. In: Sugarbeet Research and Extension Reports. Sugarbeet Research and Education Board of Minnesota and North Dakota, Fargo, ND, vol. 34, pp. 119-123.
6. Franzen, D.W., Sharma, L.K., Bu, H., 2014. Active Optical Sensor Algorithms for Corn Yield Prediction and a Corn Side-dress Nitrogen Rate Aid. NDSU Extension Circular SF1176-5. <> (accessed 12.2015). http://www.ag.ndsu.edu/pubs/plantsci/soilfert/sf1176-5.pdf,
7. Freeman K.W., Girma K., Arnall D.B., Mullen R.W., Martin K.L., Teal R.K. By-plant prediction of corn forage biomass and nitrogen uptake at various growth stages using remote sensing and plant height. Agron. J. 2007, 99:530-536.
8. Gelderman, R.H., Beegle, D., 1998. Nitrate-nitrogen (Revised January 1998). In: Brown, J.R. (Ed.), Recommended Chemical Soil Test Procedure for the North Central Region. North Central Regional Res. Pub. No. 221 (2015 revised). Missouri Agricultural Experiment Station Bulletin SB 1001, Univ. of Missouri, Columbia, pp. 5.1-5.4. <> (accessed 1.25.2016). http://extension.missouri.edu/explorepdf/specialb/sb1001.pdf.
9. Gitelson A.A., Merzlyak M.N. Remote estimation of chlorophyll content in higher plant leaves. Int. J. Rem. Sens. 1997, 18:2691-2697.
10. Haboudane D., Miller J.R., Pattey E., Zarco-Tejada P.J., Strachan I.B. Hyperspectral vegetation indices and novel algorithms for predicting green LAI of crop canopies: modeling and validation in the context of precision agriculture. Rem. Sens. Environ. 2004, 90:337-352.
11. Han D. Tree height measurement based on image processing with 3-points correction. Proceedings of the International Conference on Computer Science and Network Technology, Harbin, China 2011, 2281-2284.
12. Holland K.H., Schepers J.S. Derivation of a variable rate nitrogen application model for in-season fertilization of corn. Agron. J. 2010, 102:1415-1424.
13. Hussain I., Olson K.R., Ebelhar S.A. Impacts of tillage and no-till on production of maize and soybean on an eroded Illinois silt loam soil. Soil Tillage Res. 1999, 52:37-49.
14. Kanuma, T., Ganno, K., Hayashi, S., Sakaue, O., 1998. Leaf area measurement using stereo vision. In: Proc. of the 3rd IFAC/CIGR Workshop on Artificial Intelligence in Agriculture, Makuhari Messe, Chiba, Japan, pp. 157-162.
15. Kapusta G., Krausz R.F., Matthews J.L. Corn yield is equal in conventional, reduced, and no tillage after 20 years. Agron. J. 1996, 88:812-817.
16. Katsvairo T.W., Cox W.J., Van Es H.M. Spatial growth and nitrogen uptake availability of corn at two nitrogen levels. Agron. J. 2003, 95:1000-1011.
17. Kitchen N. Variable-rate nitrogen fertilizer application in corn using in-field sensing of leaves and canopy. Agronomy Technical Note MO-35 2006, University of Missouri, Columbia, MO.
18. Kladivko E.J., Griffith D.R., Mannering J.V. Conservation tillage effects on soil properties and yield of corn and soya beans in Indiana. Soil Tillage Res. 1986, 8:277-287.
19. Kwak D., Lee W., Lee J., Biging G.S., Gong P. Detection of individual trees and estimation of tree height using LiDAR data. J. Forest. Res. 2007, 12:425-434.
20. 2 on the growth, seed yield, and water use efficiency of soybean (Glycine max (L.) Merr.) under drought stress. Agric. Water Manage. 2013, 129:105-112.
21. Lindsay W.L., Norvell W.A. Development of a DTPA soil test for zinc, iron, manganese, and copper. Soil Sci. Soc. Am. J. 1978, 42:421-428.
22. Lines J.A., Tillett R.D., Ross L.G., Chan D., Hockaday S., McFarlane N.J.B. An automatic image-based system for estimating the mass of freeswimming fish. Comput. Electron. Agr. 2001, 31:151-168.
23. Machado S., Bynum E.D., Archer T.L., Lascano R.J., Wilson L.T., Bordovsky J. Spatial and temporal variability of corn growth and grain yield: implications for site-specific farming. Crop Sci. 2002, 42:1564-1576.
24. Magnussen S., Eggermonth P., Riccia V.L. Recovering tree heights from airborne LIDAR data. J. For. Sci. 1999, 45:407-422.
25. Martin K.L., Raun W.R., Solie J.B. By-plant prediction of corn grain yield using optical sensor readings and measured plant height. J. Plant Nutr. 2012, 35:1429-1439.
26. Matsuura, Y., He, D., Kozai T., 2001. Development of a Transplant Population Analysis System. ASAE Paper No. 01-7051. ASAE, St. Joseph, MI.
27. Morden, R.E., Ling, P.P., Giacomelli, G.A., 1997. An Automated Plant Growth Monitoring Systems Using Machine Vision. ASAE Paper No. 974033. ASAE, St. Joseph, MI.
28. Nilsson M. Estimation of tree heights and stand volume using an airborne LIDAR system. J. Rem. Sens. Environ. 1996, 56:1-7.
29. Olsen S.R., Cole C.V., Watanabe F.S., Dean L.A. Estimation of Available Phosphorus in Soils by Extraction with Sodium Bicarbonate. USDA Circular 939 1954, U.S. Government Printing Office, Washington, D.C.
30. Persson Å., Holmgren J., Söderman U. Detecting and measuring individual trees using an airborne LIDAR. Photogramm. Eng. Rem. Sens. 2002, 68:925-932.
31. Raun W.R., Solie J.B., Johnson G.V., Stone M.L., Lukina E.V., Thomason W.E., Schepers J.S. In-season prediction of potential grain yield in winter wheat using canopy reflectance. Agron. J. 2001, 93:131-138.
32. Raun W.R., Solie J.B., Johnson G.V., Stone M.L., Mullen R.W., Freeman K.W., Thomason W.E., Lukina E.V. Improving nitrogen use efficiency in cereal grain production with optical sensing and variable rate application. Agron. J. 2002, 94:815-820.
33. Raun W.R., Solie J.B., Stone M.L., Martin K.L., Freeman K.W., Mullen R.W. Optical sensor-based algorithm for crop nitrogen fertilization. Commun. Soil Sci. Plant Anal. 2005, 36:2759-2781.
34. Sadler E.J., Bauer P.J., Busscher W.J. Site-specific analysis of a droughted corn crop: I. Growth and grain yield. Agron. J. 2000, 92:395-402.
35. Sammis T.W., Smeal D., Williams S. Predicting corn yield under limited irrigation using plant height. Trans. ASAE 1988, 31:830-838.
36. Schulte, E.E., Hopkins, B.G., 1996. Estimation of soil organic matter by weight-loss-on ignition. In: Magdoff, F.R. et al. (Eds.), Soil Organic Matter: Analysis and Interpretation. SSSA Special Publication 46. SSSA, Madison, WI, pp. 21-31 (Chapter 3).
37. Sharma L.K., Franzen D.W. Use of corn height to improve relationships between active optical sensor readings and yield estimates. Prec. Agric. 2013, 15:331-345.
38. Sharma L.K., Franzen D.W. Use of corn height to improve the relationship between active optical sensor readings and yield estimates. Precision Agric. 2014, 15:331-345. 10.1007/s11119-013-9330-9.
39. Shimada M., Muhtar Q., Tadono T., Wakabayashi H. Tree height estimation using an airborne L-band polarimetric interferometric SAR. Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, Australia, Sydney 2001, 1430-1432.
40. Shrestha, D.S., Steward, B.L., 2001. Automatic Corn Plant Population Measurement Using Machine Vision. ASAE Paper No. 01-1067. ASAE, St. Joseph, MI.
41. Shrestha, D.S., Steward, B.L., Birrell, S.J., Kaspar, T.C., 2002. Plant height estimation using two sensing systems. In: Proceedings of the ASAE Annual International Meeting, 2002. CD-ROM, St. Joseph, MI.
42. Soil Survey Staff Natural Resources Conservation Service, USDA, Web Soil Survey Available online at, (accessed 08/15/2013). http://www.elsevier.com/xml/linking-roles/text/html.
43. Tarbell K.A., Tcheng D.K., Reid J.F. Corn growth and development attributes obtained using inductive learning techniques. Trans. ASAE 1991, 34(5):2264-2271.
44. Tarbell K.A., Reid J.F. A computer vision system for characterizing corn growth and development. Trans. ASAE 1991, 34(5):2245-2255.
45. Thomas, G.W., 1982. Exchangeable cations. In: Page, A.L. et al. (Eds.), Methods of Soil Analysis. Part 2 (Agronomy Monographs 9). ASA and SSSA, Madison, WI, pp. 159-165.
46. Ulander L.M.H., Dammert P.B.G., Hagberg J.O. Measuring tree height using ERS-1 SAR interferometry. Proceedings of the IEEE International Geoscience and Remote Sensing Symposium, Firenze, Italy 1995, 2189-2193.
47. Van Henten E.J., Bontsema J. Non-destructive crop measurement by image processing for crop growth control. J. Agric. Eng. Res. 1995, 61:97-105.
48. Venuprasad R., Sta Cruz M.T., Amante M., Magbanua R., Kumar A., Atlin G.N. Response to two cycles of divergent selection for grain yield under drought stress in four rice breeding populations. J. Field Crops Res. 2008, 107:232-244.
49. Watson, D., Brown, J.R., 1998. pH and lime requirement. In: Brown, J.R. (Ed.) Recommended Chemical Soil Test Procedure for the North Central Region. North Central Regional Res. Pub. No. 221 (2015 revised). Missouri Agric. Exp. Stat. SB 1001, Univ. of Missouri, Columbia, pp. 13.
50. Wilhelm, W., Ruwe, K., Schlemmer, M.R., 2000. Comparison of three Leaf Area Index Meters in a Corn Canopy. Publication from USDA-ARS/UNL Faculty Paper 71. <>. http://digitalcommons.unl.edu/usdaarsfacpug/71.
51. Yamamoto K., Takahashi T., Miyachi Y., Kondo N., Morita S., Nakao M., Takashi S., Shibayama T., Takaichi Y., Tsuzuku M. Estimation of mean tree height using small-footprint airborne LiDAR without a digital terrain model. J. Forest. Res. 2011, 16:425-431.
52. Yin X., Jaja N., McClure M.A., Hayes R.M. Comparison of models in assessing relationship of corn yield with plant height measured during early- to mid-season. J. Agr. Sci. 2011, 3:14-24.
53. Yin X., McClure M.A., Jaja N., Tyler D.D., Hayes R.M. In-season prediction of corn yield using plant height under major production systems. Agron. J. 2011, 103:923-929.
54. Zhang L., Grift T.E. A LIDAR-based crop height measurement system for Miscanthus giganteus. Comput. Electron. Agr. 2012, 85:70-76.
55. Zhang J., Huang X. Measuring method of tree height based on digital image processing technology. Proceedings of the First International Conference on Information Science and Engineering, Nanjing, China 2009, 1327-1331.