SmartSun projekat: multidisciplinarni pristup u potrazi za “klimatski pametnim” suncokretom

Abstract

Klimatske promene negativno utiču na proizvodnju ratarskih useva, posebno tokom dugih sušnih perioda. Jedan od ključnih pristupa za ublažavanje uticaja ekstremnih klimatskih uslova je oplemenjivanje useva kako bi se poboljšala njihova prilagodljivost različitim uslovima gajenja. Međutim, tradicionalne metode oplemenjivanja su često dugotrajne, radno intenzivne i rezultati evaluacije mogu biti pristrasni. U cilju dubljeg razumevanja adaptivnog odgovora suncokreta na sušne stresove uzrokovane klimatskim promenama, SmartSun projekat primenjuje holistički pristup koji obuhvata digitalnu fenotipizaciju korena suncokreta, analizu epigenetskih mehanizama i integraciju dobijenih podataka mašinskim učenjem. Do sada je razvijen protokol za rani rast korena suncokreta kroz fenotipizaciju u rizotronima pod različitim uslovima zalivanja (70, 42 i 50% zapreminskog sadržaja vode). Testirane su inbred linije suncokreta sa Instituta za ratarstvo i povrtarstvo kako bi se identifikovali tolerantni i osetljivi genotipovi. Identifikovane su ključne morfološke osobine korena koje su pouzdane u razlikovanju osetljivosti na sušu.

Climate change has a negative impact on the production of field crops, especially during extended periods of drought. One of the key strategies to mitigate the effects of extreme climate conditions is crop breeding aimed at enhancing their adaptability to various growing conditions. However, traditional breeding methods are often time-consuming, labor-intensive, and the evaluation outcomes may be biased. To gain a deeper understanding of the adaptive response of sunflowers to drought stress caused by climate change, the SmartSun Project employs a holistic approach encompassing digital root phenotyping, analysis of epigenetic mechanisms, and the integration of acquired data through machine learning. A protocol for early sunflower root growth has been developed using phenotyping in rhizotrons under different watering conditions (70%, 42%, and 50% volumetric water content). Inbred sunflower lines from the Institute of Field and Vegetable Crops (IFVCNS) were tested to identify tolerant and sensitive genotypes. Key morphological root traits that reliably differentiate drought sensitivity have been identified.