Non-Destructive evaluation of the leaf nitrogen concentration by In-Field visible/Near-Infrared spectroscopy in pear orchards

Sensors (Switzerland)

Volumn 17, Issue 3, 2017, Pages

  Wang, Jie ^a   Shen, Changwei ^a   Liu, Na ^a   Jin, Xin ^a   Fan, Xueshan ^a   Dong, Caixia ^a   Xu, Yangchun ^a  

^a NANJING AGRICULTURAL UNIVERSITY   (China)

Author keywords

Leaf nitrogen; Non destructive; Pear; PLSR; Visible near infrared spectroscopy

Indexed keywords

BACKPROPAGATION; FARMS; LEAST SQUARES APPROXIMATIONS; LINEAR REGRESSION; NEURAL NETWORKS; NITROGEN; NONDESTRUCTIVE EXAMINATION; ORCHARDS; PLANTS (BOTANY); PRINCIPAL COMPONENT ANALYSIS; PROBES; REGRESSION ANALYSIS; VEGETATION;

LEAF NITROGEN; NON DESTRUCTIVE; PEAR; PLSR; VISIBLE/NEAR-INFRARED SPECTROSCOPIES;

FRUITS;

NITROGEN;

LEAST SQUARE ANALYSIS; NEAR INFRARED SPECTROSCOPY; PYRUS; STATISTICAL MODEL;

LEAST-SQUARES ANALYSIS; LINEAR MODELS; NITROGEN; PYRUS; SPECTROSCOPY, NEAR-INFRARED;

EID: 85014794385     PISSN: 14248220     EISSN: None     Source Type: Journal    
DOI: 10.3390/s17030538     Document Type: Article

References (50)

1. Brunetto, G., Melo, G.W.B.D., Toselli, M., Quartieri, M., Tagliavini, M. The role of mineral nutrition on yields and fruit quality in grapevine, pear and apple. Rev. Bras. Frutic. 2015, 37, 1089-1104.
2. Sugar, D., Righetti, T.L., Sanchez, E.E., Khemira, H. Management of nitrogen and calcium in pear trees for enhancement of fruit resistance to postharvest decay. HortTechnology 1992, 2, 382-387.
3. Tagliavini, M., Scudellari, D., Marangoni, B., Toselli, M. Nitrogen fertilization management in orchards to reconcile productivity and environmental aspects. Nutr. Cycl. Agroecosys. 1995, 43, 93-102.
4. El-Jendoubi, H., Abadía, J., Abadía, A. Assessment of nutrient removal in bearing peach trees (Prunus persica L. Batsch) based on whole tree analysis. Plant Soil 2013, 369, 421-437.
5. Quartieri, M., Millard, P., Tagliavini, M. Storage and remobilization of nitrogen by pear (Pyrus communis L.) trees as affected by timing of N supply. Eur. J. Agron. 2002, 17, 105-110.
6. Luo, C., Xue, L., Liu, M. Nondestructive measurement of sugar content in navel orange based on Vis-NIR spectroscopy. In Computer and Computing Technologies in Agriculture IV, Springer: Berlin/Heidelberg Germany, 2010, pp. 467-473.
7. Bo, S., Jonsson, A., Börjesson, T. Use of near infrared reflectance spectroscopy to predict nitrogen uptake by winter wheat within fields with high variability in organic matter. Plant Soil 2005, 269, 251-258.
8. Shi, J.Y., Zou, X.B., Zhao, J.W., Wang, K.L., Chen, Z.W., Huang, X.W. Nondestructive diagnostics of nitrogen deficiency by cucumber leaf chlorophyll distribution map based on near infrared hyperspectral imaging. Sci. Hortic. 2012, 138, 190-197.
9. Ulissi, V., Antonucci, F., Benincasa, P. Nitrogen content estimation in tomato leaves by VIS-NIR non-destructive spectroscopy. Sensors 2011, 11, 6411-6424.
10. Liu, F., Jin, Z.L., Naeem, M.S. Applying Near-Infrared Spectroscopy and Chemometrics to Determine Total Amino Acids in Herbicide-Stressed Oilseed Rape Leave. Food Bioprocess Tech. 2011, 4, 1314-1321.
11. Wang, J., Zhao, H., Shen, C., Chen, Q., Dong, C., Xu, Y. Determination of Nitrogen Concentration in Fresh Pear Leaves by Visible/Near-Infrared Reflectance Spectroscopy. Agron. J. 2014, 106, 1867-1872.
12. Yoder, B.J., Pettigrew-Crosby, R.E. Predicting nitrogen and chlorophyll content and concentrations from reflectance spectra (400-2500 nm) at leaf and canopy scales. Remote Sens. Environ. 1995, 53, 199-211.
13. Zhu, Y., Li, Y., Feng, W., Yao, X., Cao, W. Monitoring leaf nitrogen in wheat using canopy reflectance spectra. Can. J. Plant Sci. 2006, 86, 1037-1046.
14. Potůčková, M., Červená, L., Kupková, L., Lhotáková, Z., Lukeš, P., Hanuš, J. Comparison of reflectance measurements acquired with a contact probe and an integration sphere: Implications for the spectral properties of vegetation at a leaf level. Sensors 2016, 16, 1801.
15. Menesattia, P., Antonuccia, F., Pallottinoa, F. Estimation of plant nutritional status by Vis-NIR spectrophotometric analysis on orange leaves [Citrus sinensis (L) Osbeck cv Tarocco]. Biosyst. Eng. 2010, 105, 448-454.
16. Martens, B.H., Naes, K.H.T. Chapter Multivariate Calibration by Data Compression. In Near-Infrared Technology in the Agricultural and Food Industries, 2nd ed., American Association of Cereal Chemists, Inc.: St. Pual, MN, USA, 2010, pp. 57-87.
17. Wold, S., Sjostrom, M., Eriksson, L. PLS-regression: A basic tool of chemometrics. Chemome Intell. Lab. 2001, 58, 109-130.
18. Atzberger, C., Guerif, M., Baret, F., Werner, W. Comparative analysis of three chemometric techniques for the spectroradiometric assessment of canopy chlorophyll content in winter wheat. Comput. Electron. Agric. 2010, 73, 165-173.
19. Broge, N.H., Mortensen, J.V. Deriving green crop area index and canopy chlorophyll density of winter wheat from spectral reflectance data. Remote Sens. Environ. 2002, 81, 45-57.
20. Rondeaux, G. Vegetation monitoring by remote sensing: A review of biophysical indices. Photo Interpret. 1995, 3, 197-216.
21. Jago, R.A., Cutler, M.E.J., Curran, P.J. Estimating canopy chlorophyll concentration from field and airborne spectra. Remote Sens. Environ. 1999, 68, 217-224.
22. Darvishzadeh, R., Atzberger, C., Skidmore, A.K., Abkar, A.A. Leaf area index derivation from hyperspectral vegetation indices and the red edge position. Int. J. Remote Sens. 2009, 30, 6199-6218.
23. Hansen, P.M., Schjoerring, J.K. Reflectance measurement of canopy biomass and nitrogen status in wheat crops using normalized difference vegetation indices and partial least squares regression. Remote Sens. Environ. 2003, 86, 542-553.
24. Xue, L., Cao, W., Luo, W., Dai, T., Zhu, Y. Monitoring leaf nitrogen status in rice with canopy spectral reflectance. Agron. J. 2004, 196, 135-142.
25. Feng, W., Yao, X., Zhu, Y., Tian, Y., Cao, W. Monitoring leaf nitrogen status with hyperspectral reflectance in wheat. Eur. J. Agron. 2008, 28, 394-404.
26. Lamb, D.W., Steyn-ross, M., Schaare, P., Hanna, M.M., Silvester, W., Steyn-Ross, A. Estimating leaf nitrogen concentration in ryegrass (Lolium spp.) pasture using the chlorophyll red-edge: The oretical modelling and experimental observations. Int. J. Remote Sens. 2002, 23, 3619-3648.
27. Serrano, L. Remote sensing of biomass and yield of winter wheat under different nitrogen supplies. Crop Sci. 2000, 40, 723-731.
28. Weber, V.S., Araus, J.L., Cairns, J.E., Sanchez, C., Melchinger, A.E., Orsini, E. Prediction of grain yield using reflectance spectra of canopy and leaves in maize plants grown under different water regimes. Field Crops Res. 2012, 128, 82-90.
29. Sepulcre-Cantó, G., Zarco-Tejada, P.J., Jiménez-Muñoz, J.C., Sobrino, J.A., Soriano, M.A., Fereres, E. Monitoring yield and fruit quality parameters in open-canopy tree crops under water stress. Implications for aster. Remote Sens. Environ. 2007, 107, 455-470.
30. Ye, X., Sakai, K., Sasao, A., Asada, S. Potential of airborne hyperspectral imagery to estimate fruit yield in citrus. Chemometr. Intell. Lab. 2008, 90, 132-144.
31. Lu, R.K. Soil Chemical Analysis Methods in Agriculture, China Agricultural Sciences and Technical Press: Beijing, China, 2000. (In Chinese)
32. Olsen, S.R. Estimation of Available Phosphorus in Soils by Extraction with Sodium Bicarbonate, Miscellaneous Paper Institute for Agricultural Research Samaru: Washington, DC, USA, 1954.
33. Sommers, L.E. Chemical analysis of ecological materials. J. Environ. Qual. 1977, 41, 494-495.
34. Tagliavini, M., Quartieri, M., Millard, P. Remobilised nitrogen and root uptake of nitrate for leaf growth, flowers and developing fruits of pear (P. communis) trees. Plant Soil 1997, 195, 137-142.
35. Liu, Y., Sun, X., Ouyang, A. Nondestructive measurement of soluble solid content of navel orange fruit by visible-NIR spectrometric technique with PLSR and PCA-BPNN. LWT Food Sci. Technol. 2010, 43, 602-607.
36. Yao, X., Zhu, Y., Tian, Y.C., Feng, W., Cao, W. X. Exploring hyperspectral bands and estimation indices for leaf nitrogen accumulation in wheat. Int. J. Appl. Earth. Obs. 2010, 12, 89-100.
37. Saeys, W., Mouazen, A.M., Ramon, H. Potential for onsite and online analysis of pig manure using visible and near infrared reflectance spectroscopy. Biosyst. Eng. 2005, 91, 393-402.
38. Gomez, A.H., He, Y., Pereira, A.G. Non-destructive measurement of acidity, soluble solids and firmness of Satsuma mandarin using Vis/NIR-spectroscopy techniques. J. Food Eng. 2006, 77, 313-319.
39. Haboudane, D., Miller, J.R., Tremblay, N., Zarco-Tejada, P.J., Dextraze, L. Integrated narrow-band vegetation indices for prediction of crop chlorophyll content for application to precision agriculture. Remote Sens. Environ. 2002, 81, 416-426.
40. Rotbart, N., Schmilovitch, Z., Cohen, Y., Alchanatis, V., Erel, R., Ignat, T., Shenderey, C., Dag, A., Yermiyahu, U. Estimating olive leaf nitrogen concentration using visible and near-infrared spectral reflectance. Biosyst. Eng. 2013, 114, 426-434.
41. Sims, D.A., Gamon, J.A. Relationships between leaf pigment content and spectral reflectance across a wide range of species, leaf structures and developmental stages. Remote Sens. Environ. 2002, 81, 337-354.
42. Barankova, B., Lazar, D., Naus, J. Analysis of the effect of chloroplast arrangement on optical properties of green tobacco leaves. Remote Sens. Environ. 2016, 174, 181-196.
43. Serbin, S.P., Dillaway, D.N., Kruger, E.L., Townsend, P.A. Leaf optical properties reflect variation in photosynthetic metabolism and its sensitivity to temperature. J. Exp. Bot. 2012, 63, 489-502.
44. Nguyen, H.T., Lee, B.W. Assessment of rice leaf growth and nitrogen status by hyperspectral canopy reflectance and partial least square regression. Eur. J. Agron. 2006, 24, 349-356.
45. Gobron, N. Theoretical limits to the estimation of the leaf area index on the basis of visible and near-infrared remote sensing data. IEEE Trans. Geosci. Remote Sens. 1997, 35, 1438-1445.
46. Blackburn, G.A. Relationships between Spectral Reflectance and Pigment Concentrations in Stacks of Deciduous Broadleaves. Remote Sens. Environ. 1999, 70, 224-237.
47. Gitelson, A.A., Gritz, Y., Merzlyak, M.N. Relationships between leaf chlorophyll content and spectral reflectance and algorithms for non-destructive chlorophyll assessment in higher plant leaves. J. Plant Physiol. 2003, 160, 271-282.
48. 2 exchange response to environment for small sample size in cucumber. Comput. Electron. Agric. 2014, 108, 39-45.
49. Sanchez, E.E., Righetti, T.L., Sugar, D., Lombard, P.B. Recycling of nitrogen in field-grown ‘Comice’ pears. J. Hort. Sci. 1991, 66, 541-546.
50. Graeff, S., Claupein, W. Quantifying nitrogen status of corn (Zea mays L.) in the field by reflectance measurements. Eur. J. Agron. 2003, 19, 611-618.