Cultivated sunflower is gaining attention given the current geopolitical situation, the climate change, and the expected 46% increase of vegetable oil world demand. It is essential to work on the development of new hybrids. To enhance sunflower crop, one of the available options is to encourage the cultivation of high oleic hybrids that are characterised by a high oleic acid content that reaches up to 90% of total fatty acids. The aim of the current work is to apply proximal sensing techniques to facilitate the evaluation of new sunflower hybrids in experimental fields. More in detail, the objective is to correlate spectral data acquired by a spectroradiometer and crop parameters measured by the research center. Two field tests have been carried out on sunflower, the first one during stem elongation stage and the second one during inflorescence emergence stage. Both surveys were made under sunny condition with a spectroradiometer which wavelengths range is between 325 and 1075 nanometres. At the same time, the research center has acquired a series of data including plant height at harvest, yield, achene moisture, oil content on dry matter. In addition, an analysis of the composition of fatty acids was made by gas chromatography. Both datasets have been processed by performing data normalisation and principal component analysis. Four wavelengths have been identified that influence the spectrum more, while the fatty acid composition was found to be more influential among discrete variables. In the end, hyperdata and fatty acid composition were correlated by Pearson correlation index. Weak correlations have been found. However, these results will be compared to the available literature and allow to set up a better acquisition of parameters that are increasingly closer to the objective. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
Preliminary Study of Sunflower Hyperdata Related to Fatty Acid Composition
Fiorentino C.;D'Antonio P.;
2025-01-01
Abstract
Cultivated sunflower is gaining attention given the current geopolitical situation, the climate change, and the expected 46% increase of vegetable oil world demand. It is essential to work on the development of new hybrids. To enhance sunflower crop, one of the available options is to encourage the cultivation of high oleic hybrids that are characterised by a high oleic acid content that reaches up to 90% of total fatty acids. The aim of the current work is to apply proximal sensing techniques to facilitate the evaluation of new sunflower hybrids in experimental fields. More in detail, the objective is to correlate spectral data acquired by a spectroradiometer and crop parameters measured by the research center. Two field tests have been carried out on sunflower, the first one during stem elongation stage and the second one during inflorescence emergence stage. Both surveys were made under sunny condition with a spectroradiometer which wavelengths range is between 325 and 1075 nanometres. At the same time, the research center has acquired a series of data including plant height at harvest, yield, achene moisture, oil content on dry matter. In addition, an analysis of the composition of fatty acids was made by gas chromatography. Both datasets have been processed by performing data normalisation and principal component analysis. Four wavelengths have been identified that influence the spectrum more, while the fatty acid composition was found to be more influential among discrete variables. In the end, hyperdata and fatty acid composition were correlated by Pearson correlation index. Weak correlations have been found. However, these results will be compared to the available literature and allow to set up a better acquisition of parameters that are increasingly closer to the objective. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
