Comparison of Different Tools and Methods in the Measurement of Leaf Area in Alfalfa

Abstract

Leaf area measurements in the field are very difficult to determine the yield. Use of the mobile application has come to the fore due to its practical use and ease of transportation. Therefore, in this study, the ease of use and accuracy were tested by determining area of leaf with an automatic leaf area meter and a mobile application called 'PETIOLE'. The leaf area of alfalfa plants (Medicago sativa L. cv Nimet) grown in the field, and measured in the field with the 'PETIOLE' mobile application and in laboratory conditions with automatically leaf area measurement device was measured. The automated leaf area meter mean for total leaf area was 61.65 ± 3.50; meanwhile the mean for the PETIOLE App assessment was 61.56 ± 3.15. As a result, the PETIOLE app measures the area of each leaf separately, more quickly and efficiently than before, particularly in the field.

Keywords

• Alfalfa
• PETIOLE App
• LICOR
• LI-3100C
• Leaf area
• Medicago sativa L cv

References

1. Acharya JP, Lopez Y, Gouveia BT, de Bem Oliveira I, Resende Jr MF, Muñoz PR, Rios EF. 2020. Breeding alfalfa (Medicago sativa L.) adapted to subtropical agroecosystems. Agronomy, 10(5): 742.
2. Blanco FF, Folegatti MV. 2003. A new method for estimating the leaf area index of cucumber and tomato plants. Horticult Brasileira, 21: 666-669.
3. Clarke JM, McCaig TN. 1985. A versatile, inexpensive microcomputer‐based leaf area measurement system 1. Agronomy J, 77(6): 966-968.
4. Dale BE. 1983. Biomass refining: protein and ethanol from alfalfa. Indust Eng Chem Prod Res Devel, 22(3): 466-472.
5. Díaz S, Kattge J, Cornelissen JH, Wright IJ, Lavorel S, Dray S, Gorné LD. 2016. The global spectrum of plant form and function. Nature, 529(7585): 167-171.
6. Garnier E, Stahl U, Laporte MA, Kattge J, Mougenot I, Kühn I, Klotz S. 2017. Towards a thesaurus of plant characteristics: an ecological contribution. J Ecol, 105(2): 298-309.
7. Janmohammadi M, Dezfuli PM, Sharifzadeh F. 2008. Seed invigoration techniques to improve germination and early growth of inbred line of maize under salinity and drought stress. Gen Appl Plant Physiol, 34(3-4): 215-226.
8. Jetz IJ, Reich PB, Westoby M, Ackerly DD, Baruch Z, Bongers F, Villar R. 2004. The worldwide leaf economics spectrum. Nature, 428(6985): 821-827.

9. Jetz W, Cavender-Bares J, Pavlick R, Schimel D, Davis FW, Asner GP, Ustin SL. 2016. Monitoring plant functional diversity from space. Nature Plants, 2(3): 1-5.
10. Lane ND, Miluzzo E, Lu H, Peebles D, Choudhury T, Campbell AT. 2010. A survey of mobile phone sensing. IEEE Commun Mag, 48(9): 140-150.
11. Perez-Harguindeguy N, Diaz S, Garnier E, Lavorel S, Poorter H, Jaureguiberry P, Cornelissen JHC. 2013. New handbook for standardised measurement of plant functional traits worldwide. Aust Bot, 61: 167-234.
12. Ramirez GM, Zullo Júnior J. 2010. Estimation of biophysical parameters of coffee fields based on high-resolution satellite images. Engenharia Agrícola, 30: 468-479.
13. Singh J, Kumar A, Singh L. 2021. Performance of the petiole mobile application on the leaf area estimation as varied with calibration height. The Pharma Innov J, 10(4): 337-341.
14. Teacher AG, Griffiths DJ, Hodgson DJ, Inger R. 2013. Smartphones in ecology and evolution: A guide for the app‐rehensive. Ecol Evol, 3(16): 5268-5278.
15. Welsh K, France D. 2012. Smartphones and fieldwork. Geography, 97(1): 47-51.
16. Wissuwa M. Smith SE. 1997. Morphological and physiological characteristics associated with tolerance to summer irrigation termination in alfalfa. Crop Sci, 37(3): 704-711.