Indian Journal of Agricultural Research

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Research Article

Indian Journal of Agricultural Research, volume 51 issue 6 (december 2017) : 615-618

Reflectance estimation in cereal/pea intercropping system based on numerical images analysis method   

C. Benider, T. Madani, H.Bouzerzour, A. Guendouz
1Faculty of Life and Natural Sciences, Ecology and Plant Biology Department, VRBN Lab, University of Ferhat Abbas, Setif-1, Algeria.
Cite article:- Benider C., Madani T., H.Bouzerzour, Guendouz A. (2017). Reflectance estimation in cereal/pea intercropping system based on numerical images analysis method . Indian Journal of Agricultural Research. 51(6): 615-618. doi: 10.18805/IJARe.A-289.

ABSTRACT

A Field experiment was carried out during the 2015-2016 growing season at Sersour experimental farm, located in the semi-arid region of Sétif (Algeria). The aim of this study was to evaluate the efficiency of using the numerical image analysis approach to estimate biomass and senescence by mean of appropriate software, the Mesurim Pro (Version 3.3). The results showed a significant difference between leaf reflectance at Red, Green and Blue light; results also registered a positive and significant correlation between leaf reflectance at red and blue, and senescence (r=0.78, r=0.50, respectively). This relationship between senescence and leaf reflectance indicate that the increase in leaf reflectance during senescence stage is due to degradation of leaf chlorophyll content. Over all, the numerical image analysis was very suitable approach to estimate reflectance of vegetal cover and the variation of some physiological traits. 

REFERENCES

  1. Baghdadi1, A., Ridzwan, A H., Ghasemzadeh A., Ebrahimi, M., Radziah, O. and Martini, M. Y.(2016).Effect of intercropping of corn and soybean on dry matter yield and nutritive value of forage corn.Legume Research, 39 (6): 976-981. DOI: 10.18805/    lr.v39i6.6643
  2. Baghdadi1, A., Ridzwan, A .H., Ghasemzadeh A., Radziah O ., Martini. M. Y. and Mahdavi Atashgahi A.R. (2016) Productivity, relative yield and plant growth of forage corn intercropped with soybean under different crop combination ratio. Legume Research, 39 (4) : 558-564 .DOI:10.18805/lr.v0iOF.10755 
  3. Berntsen, J., Hauggaard-Nielsen, H., Olesen, J.E., Petersen, B. M., Jensen, E. S., Thomsen, A.(2004). Modelling dry matter production and resource use in intercrops of pea and barley. Field Crops Res. 88:69-83.
  4. Bushmann, C. and Nagel, E.(1993). In vivo spectroscopy and internal optics of leaves as basis for rmote sensing of vegetation. Int J Remote Sens. 14: 711-722.
  5. Brakke, T. W., Smith, J. A. and Harnden, J. M. (1989). Bidirectional scattering of light from tree leaves. Remote Sensing of Environment, 29: p. 175-183.
  6. Campillo, C., Garcia, M.I.,Daza, C., Prieto, M.H.(2010). Study of a non-destructive method for estimating the leaf area index in vegetable crops using digital images. Hortscience 45 (10): 1459-1463.
  7. Carter, G.A. and Knapp, A.K.(2001). Leaf optical properties in higher plants: linking chlorophyll concentration. Am. J Bot. 84: 677-684.
  8. Fukai, S. (1993) Intercropping - Bases of productivity - Introduction. Field Crops Res. 34: 239-245.
  9. Franklin, K.A. (2008) Shade avoidance. New Phytologist 179: 930–944
  10. Gistelson, A.A., Kanfman, Y.J. and Merzlyak, M.N.(1996).Use of agreen channel in remote sensing of global vegetation from EOS-    MODIS.Remote Sens. Environ. 58: 289-298.
  11. Gistelson, A.A. and Merzlyak, M.N.(1994). Quantitative estimation of chlorophyll a using reflectance spectra: Experiments with antumn chestnut and maple leaves. J. Photo. Photobio (B)22:247-252.
  12. Grant, L.(1987). Diffuse and specular characteristics of leaf reflectance. Rem. Sens. Environ. 22: 309-322.
  13. Guendouz, A., Guessoum, S., Maamri, K. andHafsi, M. (2012). Predicting the efficiency of using the RGB (Red, Green and Blue) reflectance for estimating leaf chlorophyll content of Durum wheat (Triticum durum Desf.) genotypes under semi-arid conditions. American-Eurasian Journal of Sustainable Agriculture 6(2):102-106.
  14. Jahansooz, M. R., Yunusa, I. A. M., Coventry, D. R., Palmer, A. R., Eamus D.(2007).Radiation- and water-use associated with growth and yields of wheat and chickpea in sole and mixed crops. Eur. J. Agron. 26:275-282.
  15. Jones, A.S. and Hamlyn, G.(1992). Plants and Microclimate: a quantitative approach to environmentplant physiology, Second Edition, ref QK754.5J66, 1992, Cambridge University Press.
  16. Klein, R.M. (1992). Effects of green light on biological systems. Biol.Rev. 67:199-284.
  17. Knipling, E.B.(1970). Physical and physiological basis for the reflectance of visible and near-infrared radiation from vegetation. Rem. Sens. Environ.1:155-159.
  18. Midmore, D. J. (1993). Agronomic modification of resource use and intercrop productivity. Field Crops Res. 34: 357-380.
  19. Rosenberg, N.J., Blad, B.L. and Verma,S.B. (1983). Microclimate: The biological environment. Wiley-Interscience, New York, pages 255-257.
  20. Trenbath, B.R. (1983). The dynamic properties of mixed crops. pp. 265-286. In: Frontiers of research in agriculture. Roy, S.K. (Ed.). Calcutta, India: Indian Statistical Institute. 
  21. Tsubo, M., Walker, S. and Mukhala, E. (2001). Comparisons of radiation use efficiency of mono-/inter-cropping systems with different row orientations. Field Crops Research 71(1):17-29.
  22. Varlet-Grancher, C.,Bonhomme, R. andSinoquet, H. (1993). Crop structure and lightmicroclimate. 518 p.
  23. Yan, C.J., Song, S.H., Wang, W.B., Miao, S.J., Cao, Y.Q., Wang, C.L. and Zhang, L.J.(2014). Impacts of fertilization on photosynthesis, growth and yield of two soybean cultivars (Glycine max L. Merr) in Northeast China, Legume Research, 38 (1): 77-84. DOI:10.5958/0976-0571.2015.00013.2
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