USING THE WATER STRESS INDEX FOR TOMATO IRRIGATION CONTROL
Abstract
The temperature of the leaf surface of plants can be used as an indicator of the water stress of agricultural crops. Since plant temperature is affected by weather factors, it is usually expressed through the crop water stress index (CWSI). To calculate the CWSI, two input parameters must be known that relate plant temperature under and without maximum water stress to the water vapor pressure deficit. These basic equations are specific to each culture and locale. Many studies on the definition of CWSI and basic dependencies for tomatoes have been conducted abroad, such a study has not yet been conducted in Ukraine. The purpose of the research is to establish CWSI values and basic equations that are needed for the purpose of watering tomatoes in the south of Ukraine under subsurface drip irrigation. The paper presents the results of determining the theoretical and empirical water stress index of tomatoes under subsurface drip irrigation. The research results confirm that the water stress index can be used to plan the irrigation of tomatoes both independently and in combination with other methods to increase the accuracy of decision-making. An analysis of the daily dynamics of the CWSI was carried out, according to the results of which it was established that in the morning hours the water stress index on average during the observation period was almost 0, then, as the intensity of solar radiation increased, the CWSI also increased and reached its maximum value (1,08) at 20:00. The correlation coefficient between the water stress index and the intensity of solar radiation was 0,63. The relationship between irrigation rate, soil moisture, change in plant stem diameter, and CWSI was established, the correlation coefficients are -0,60, -0,55, and -0,51, respectively. Theoretical and imperial methods estimate CWSI equally, there is a high correlation between both methods (r=0,92). It is necessary to prescribe irrigation or increase the irrigation rate according to the theoretical and empirical methods of determining CWSI, respectively, for its values of 0,3 and -2,2. The empirical method of calculating CWSIE using the resulting equations is easier to use. The CWSI values obtained for tomatoes in this study are closely correlated with the other irrigation methods.
References
2. Shatkovskyi, A.P., & Cherevychnyi, Yu. O. (2013). Vodospozhyvannia ta vrozhainist paslonovykh kultur za kraplynnoho zroshennia v umovakh Stepu Ukrainy [Water consumption and yield of nightshade crops under drip irrigation in the steppe of Ukraine]. Melioratsiia i vodne hospodarstvo, 100(1), 27-33. [in Ukrainian]. Retrieved from: http://nbuv.gov.ua/UJRN/Mivg_2013_100(1)_6
3. Cícero, J., César, A., Carlos, A., Adelmo, G., Luiz, F., & José, A. (2018). Tomato water stress index as a function of irrigation depths. R. Bras. Eng. Agríc. Ambiental, 22(2), 95-100. DOI: http://dx.doi.org/10.1590/1807-1929/agriambi.v22n2p95-100
4. Shatkovskyi, A., Zhuravlov, O., & Vasiuta, V. (2022). The use of the phytomonitoring method to control the irrigation of tomato plantations: A case study. Journal of Water and Land Development, 54, 21-26. DOI: https://doi.org/10.24425/jwld.2022.141551
5. Zhuravlov, O.V., Shatkovskyi, A.P., Vasyuta, V.V., Cherevychnyi, Y.O., Marinkov, O.A., Kovalenko, I.O., & Gulenko, O.I. (2022). Porivnyannia rozrahunkovyh metodiv vyznachennia evapotranspiracii za kraplynnoho zroshennia [Comparison of calculation methods for determining evapotranspiration under drip irrigation]. Melioratsiia i vodne hospodarstvo, 115(1), 40-49. [in Ukrainian]. DOI: https://doi.org/10.31073/mivg202201-324
6. Shatkovskyi, A.P., & Zhuravlov, O.V. (2016). Upravlinnya kraplynnym polyvom na osnovi vykorystannya internet-meteostantsiy iMETOS® [Drip irrigation management based on the use of iMETOS® internet weather stations]. Naukovi dopovidi NUBiP Ukrayiny, 2 (59).
DOI https://doi.org/10.31548/dopovidi2016.02.007.
7. Usoltsev, S.F., & Nestyak, V.S. (2018). Primenenie fitomonitoringa dlya otsenki indeksa vodnogo stressa [Applicationof phytomonitoring for estimating the water stress index]. Sibirskii vestnik sel’skokhozyaistvennoi nauki, 48( 5), 77-85 [In Russian]. DOI: https://doi.org/10.26898/0370-8799-2018-5-10
8. López, R. L., Ramirez, R. A., Peña, M. A. V., Cruz, I. L., Cohen, I. S., & Garcia, A. R. (2009). Índice de estrés hídrico del cultivo de tomate de cáscara (Physalis ixocarpa Brot.). Revista Chapingo, 15, 259-267. https://www.scielo.org.mx/pdf/rcsh/v15n3/v15n3a6.pdf
9. Ramírez, A. J. F., Coelho, R. D., Pizani, M. A. M., & Silva C. J. da. (2015). Determinação do índice de estresse hídrico em tomateiros cereja (Lycopersicum Solanum var. Cerasiforme.) com câmara infravermelha. Revista Brasileira de Agricultura Irrigada, 9, 218-224.
DOI: https://doi.org/10.7127/rbai.v9n400356
10. Khorsand, A., Rezaverdinejad, V., Asgarzadeh, H., Majnooni‑Heris, A., Rahimi, A., Besharat, S., & Sadraddini, A. A. (2021). Linking plant and soil indices for water stress management in black gram. Scientific reports, 11, 869. DOI: https://doi.org/10.1038/s41598-020-79516-3
11. Carroll, D. A., Hansen, N. C., Hopkins, B. G., & DeJonge, K. C. (2017). Leaf temperature of maize and crop water stress index with variable irrigation and nitrogen supply. Irrig. Sci., 35(6), 549–560. DOI: https://doi.org/10.1007/s00271-017-0558-4
12. O’Shaughnessy, S. A., Evett, S. R., Colaizzi, P. D., & Howell, T. A. (2012). A crop water stress index and time threshold for automatic irrigation scheduling of grain sorghum. Agricultural Water Management, 107, 122–132. DOI: https://doi.org/10.1016/j.agwat.2012.01.018
13. Yuan, G., Luo, Yi., Sun, X., & Tang, D. (2004). Evaluation of a crop water stress index for detecting water stress in winter wheat in the North China Plain. Agricultural Water Management, 64, 29-40. DOI: https://doi.org/10.1016/S0378-3774(03)00193-8
14. Khorsand, A., Majnooni, A, Beshart, S., Asgarzadeh, H., Rezaverdinejad, V., & Rahimi, A. (2019). Irrigation scheduling of maize based on plant and soil indices with surface drip irrigation subjected to different irrigation regimes. Agric. Water Manag., 224, 105740.
DOI: https://doi.org/10.1016/j.agwat.2019.105740
15. Taghvaeian, S., Chávez, J. L., Bausch, W. C., DeJonge, K. C. & Trout, T. J. (2013). Minimizing instrumentation requirement for estimatingcrop water stress index and transpiration of maize. Irrig. Sci, 32(1), 53–65. DOI: https://doi.org/10.1007/s00271-013-0415-z
16. Idso, S. B., Jackson, R. D., Pinter, PJ. Jr., Reginato, R. J., & Hatfield, J. L. (1981). Normalizing the stress-degree-day parameter for environmental variability. Agric. Meteorol., 24, 45-55.
DOI: https://doi.org/10.1016/0002-1571(81)90032-7
17. Jackson, R. D, Idso, S. B, Reginato, R. J, & Pinter, PJ. Jr. (1981). Canopy temperature as crop water stress indicator. Water Resour. Res., 17(4), 1133-1138. DOI: https://doi.org/10.1029/WR017i004p01133
18. Jackson, R.D., Kustas, W.P., Choudhury, B.J. (1988). A Reexamination of the Crop Water Stress Index. Irrigation Science, 9, 309-317. DOI: https://doi.org/10.1007/BF00296705
19. Prior, A., Apolo-Apolo, O.E., Castro-Valdecantos, P., Pérez-Ruiz, M., & Egea, G. (2021). Long-Term Assessment of Reference Baselines for the Determination of the Crop Water Stress Index in Maize under Mediterranean Conditions. Water, 13, 3119.
DOI: https://doi.org/10.3390/w13213119
20. Stockle, C. O., & Dugas, W. A. (1992). Evaluating canopy temperature-based indices for irrigation scheduling. Irrig. Sci., 13(1), 31–37. DOI: https://doi.org/10.1007/BF00190242
21. Ghaemi, A., Moazed, H., Rafiee, M. R., & Nasab, S. B. (2015). Determining CWSI to estimate eggplant evapotranspiration and yield under greenhouse and outdoor conditions. Iran Agricultural Research, 34, 49-60. DOI: https://doi.org/10.22099/IAR.2016.3438
22. Çolak, Y. B., Yazar, A., Çolak, I., Akça, H., & Duraktekin, G. (2015). Evaluation of crop water stress index (CWSI) for eggplant under varying irrigation regimes using surface and subsurface drip systems. Agriculture and Agricultural Science Procedia, 4, 372-382.
DOI: https://doi.org/10.1016/j.aaspro.2015.03.042
23. Erdem, Y., Erdem, T., Orta, A., & Okursoy, H. (2005). Irrigation scheduling for watermelon with crop water stress index (CWSI). Journal of Central European Agriculture, 6, 449-460.
DOI: https://doi.org/10.1016/S0304-4238(02)00215-7
24. Ünlü, M., Kanber, R., Kapur, B., Tekin, S., & Koç, D. L. (2011). The crop water stress index (CWSI) for drip irrigated cotton in a semi-arid region of Turkey. African Journal of Biotechnology, 10, 2258-2273. DOI: https://doi.org/10.4314/AJB.V10I12
25. Sezen, S. M., Yazar, A., Dasgan, Y., Yucel, S., Akyildiz, A., Tekin, S., & Akhoundnejad, Y. (2014). Evaluation of crop water stress index (CWSI) for red pepper with drip and furrow irrigation under varying irrigation regimes. Agricultural Water Management, 143, 59-70.
DOI: https://doi.org/10.1016/j.agwat.2014.06.008
26. We grow tomato paste. Agrofusion. Retrieved from:https://www.inagro.ua/
27. Klimatychni dani po m. Askaniya-Nova za period z 1899 roku [Climate data for Askaniya-Nova for the period from 1899]. Ukrainian Hydrometeorological Center. Retrieved from: https://meteo.gov.ua/en/33902/climate/climate_stations/159/24/
28. Technical catalogue Metos ® by Pessl Instruments. (2017). Pessl Instruments GmbH. Werksweg 107, 8160 Weiz, Austria, 132 r.
29. FieldClimate by Pessl instrument. Retrieved from: https://ng.fieldclimate.com
30. Bio-Instrument S.R.L. An Independent Genuine Manufacturer of Phyto-Sensors. Retrieved from: http://phyto-sensor.com
31. Ilnitskiy, O.A., Ushkarenko, V.A., Fedorchuk, M.I., Radchenko, S.S., & Bondarchuk, S.V. (2012). Metodologiya i pribornaya baza fitomonitoringa [Methodology and instrumental base of phytomonitoring] Kherson: Kherson State Agrarian University.
32. Thom, A.S., & Oliver, H.R. (1977). On penman’s equation for estimating regional evaporation. Quart. J. Roy. Meteorol, 103, 345–357. DOI: https://doi.org/10.1002/qj.49710343610
33. Allen, R.G., Pereira, L.S., Raes, D., & Smith, M. (1998). Crop evapotranspiration – Guidelines for computing crop water requirements. FAO Irrigation and Drainage Paper No. 56. Rome: FAO. Retrieved from: http://www.fao.org/3/x0490e/x0490e00.htm
34. Geiser, K. M., Slack, D. C., Allred, E. R., & Stange, K. W. (1982). Irrigation scheduling using crop canopy-air temperature difference. Trans. ASAE, 25(3), 689-694.
DOI: https://doi.org/10.13031/2013.33595
