ISI International Journals:

7. Yamaç, S.S., 2021. Artificial intelligence methods reliably predict crop evapotranspiration with different combinations of meteorological data for sugar beet in a semiarid area. Agricultural Water Management, 254, 106968. DOI: 10.1016/j.agwat.2021.106968

6. Yamaç, S.S., 2021. Reference evapotranspiration estimation with kNN and ANN models using different climate input combinations in the semi-arid environment. Journal of Agricultural Sciences, 27(02), 129-137. DOI: 10.15832/ankutbd.630303     

5. Yamaç, S.S., Şeker C., Negiş, H., 2020. Evaluation of machine learning methods to predict soil moisture constants with different combinations of soil input data for calcareous soils in a semi arid area. Agricultural Water Management, 234, 106121. DOI: 10.1016/j.agwat.2020.106121

4. Yamaç, S.S., Todorovic, M., 2020. Estimation of daily potato crop evapotranspiration using three different machine learning algorithms and four scenarios of available meteorological data. Agricultural Water Management, 228, 105875. DOI: 10.1016/j.agwat.2019.105875

3. Capelli, G., Yamaç, S.S., Stella, T., Francone, C., Paleari, L., Confalonieri, R., 2015. Are advantages from partial replacement of corn with second generation energy crops undermined by climate change? A case study for giant reed in Northern Italy. Biomass and Bioenergy, 80, 85-93. DOI: 10.1016/j.biombioe.2015.04.038

2. Stella, T., Francone, C., Yamaç, S.S., Ceotto, E., Pagani, V., Pilu, R., Confalonieri, R., 2015. Reimplementation and reuse of the Canegro model: From sugarcane to giant reed. Computers and Electronics in Agriculture, 113, 193-202. DOI: 10.1016/j.compag.2015.02.009

1. Cantore, V., Wassar, F., Yamaç, S.S., Sellami, M.H., Albrizio, R., Stellacci, A.M., Todorovic, M., 2014. Yield and water use efficiency of early potato grown under different irrigation regimes. International Journal of Plant Production, 8, 409-428. DOI: 10.22069/IJPP.2014.1617


1. Özgür A., Yamaç S.S., 2020. Modelling of daily reference evapotranspiration using deep neural network in different climates.

Other Peer-Reviewed Journals:

3.  Yamaç S.S., 2020. Forecasting of long-tern sugar beet water requirement in the Middle Anatolia, Turkey. Alınteri Journal of Agriculture Science, 35(2), 7-13. DOI: 10.47059/alinteri/V35I2/AJAS20068

2. Yamaç S.S., 2018. Estimation of long-term reference evapotranspiration using limited weather data in sugar beet plantation area from Middle Anatolian, Turkey. Süleyman Demirel Üniversitesi Ziraat Fakültesi Dergisi, 1. Uluslararası Tarımsal Yapılar ve Sulama Kongresi Özel Sayısı, 160-165.

1. Kumar N., Yamaç S.S., Velmurugan A., 2015. Applications of remote sensing and GIS in natural resource management. Journal of the Andaman Science Association, 20, 1-6.