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Non-Destructive Analysis Using Near-Infrared Spectroscopy to Predict Albumin, Globulin, Glutelin, and Total Protein Content in Sunflower Seeds

Author

Listed:
  • Cecile Levasseur-Garcia

    (Laboratoire de Chimie Agro-Industrielle (LCA), Toulouse University, INRAE, INPT, INP-Purpan, 31000 Toulouse, France)

  • Pierre Castellanet

    (Caussade Semences, 82300 Caussade, France)

  • Camille Henry

    (MAS Seeds, 40280 Haut Mauco, France)

  • Christelle Florin

    (MAS Seeds, 40280 Haut Mauco, France)

  • Marion Laporte

    (RAGT 2n, 12000 Rodez, France)

  • Virginie Mirleau-Thebaud

    (Syngenta France, 31790 Saint-Sauveur, France)

  • Sandrine Plut

    (SOLTIS, 31700 Mondonville, France)

  • Anne Calmon

    (Laboratoire de Chimie Agro-Industrielle (LCA), Toulouse University, INRAE, INPT, INP-Purpan, 31000 Toulouse, France)

Abstract

This pilot study explores the potential of near-infrared spectroscopy (NIRS) for predicting sunflower seed protein content, focusing on both crushed and husked samples to address agricultural sustainability concerns. Sunflower seeds are renowned for their richness in both oil and protein content. The important role of sunflower seeds in the food and feed industries underscores the importance of using precise analytical tools to determine their composition. In essence, the nature of the hull of sunflower seeds, which skews the interaction between the seed and light, necessitates a sophisticated analysis. This study analyzes 326 samples using a near-infrared spectrometer to develop robust partial least squares (PLS) models. High accuracy is achieved in predicting total protein for crushed samples (r²c = 0.97, RMSEC 0.54%, RPDc 6; r²p = 0.78, RMSEP 1.24%, RPDp 2.1). Extending the scope to husked samples, promising results emerge for crude protein prediction (r²c = 0.93, RMSEC 0.86%, RPDc 3.9; r²cv = 0.83, RMSECV 1.39%, RPDcv 2.4). Additionally, this study delves into protein fractions (globulin, albumin, and glutelin) in crushed seeds, adding depth to the analysis. In conclusion, NIR spectroscopy proves valuable for rapid prescreening in breeding, especially when working with hulled grains, offering non-destructive efficiency and predictive accuracy in agricultural analysis. The novel exploration of protein fractions in sunflower seeds further enhances this study’s importance, providing a valuable contribution to the field and underscoring the practical applications of NIR spectroscopy in sustainable agriculture. In conclusion, the opacity of sunflower seed hulls poses challenges in infrared spectroscopy, limiting light penetration and accuracy. Dehulled seeds are preferred for reliable results, overcoming hull-related limitations. Although grinding provides the advantages of uniformity and reproducibility for near-infrared (NIR) spectroscopy, the preference for dehulled grains persists. The practical need for accurate analysis in agriculture and breeding drives the choice of spectroscopy on dehulled seeds, allowing for replanting.

Suggested Citation

  • Cecile Levasseur-Garcia & Pierre Castellanet & Camille Henry & Christelle Florin & Marion Laporte & Virginie Mirleau-Thebaud & Sandrine Plut & Anne Calmon, 2024. "Non-Destructive Analysis Using Near-Infrared Spectroscopy to Predict Albumin, Globulin, Glutelin, and Total Protein Content in Sunflower Seeds," Sustainability, MDPI, vol. 16(2), pages 1-13, January.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:2:p:737-:d:1319206
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