Modeling and optimization of protein extraction from sunflower seed Cake: RSM and ANN-GA approaches
Sunflower seed cake (SSC) is an agricultural waste that is rich in proteins and numerous biologically active compounds. Moreover, SSC is devoid of any anti-nutritional compounds. Therefore, it can be leveraged for many food applications. In this work, SSC was explored for the extraction of proteins....
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Elsevier
2025-08-01
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| Series: | Journal of Agriculture and Food Research |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666154325004594 |
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| author | Pooja Vartiya Piyush Kashyap Bhagya Raj Maanas Sharma Mohd Adnan Syed Amir Ashraf Rahul Mehra |
| author_facet | Pooja Vartiya Piyush Kashyap Bhagya Raj Maanas Sharma Mohd Adnan Syed Amir Ashraf Rahul Mehra |
| author_sort | Pooja Vartiya |
| collection | DOAJ |
| description | Sunflower seed cake (SSC) is an agricultural waste that is rich in proteins and numerous biologically active compounds. Moreover, SSC is devoid of any anti-nutritional compounds. Therefore, it can be leveraged for many food applications. In this work, SSC was explored for the extraction of proteins. Preliminary experiments on defatted and de-phenolized SSC were carried out using one-factor analysis. Protein extraction from sunflower seed cake was performed following isoelectric precipitation, and the amino acid profile was analyzed. Response surface methodology (RSM) and artificial neural networks (ANNs) were used to optimize the extraction conditions, i.e., pH (8.5–10.5), temperature (25–45 °C), solvent-solid ratio (10–30 mL/g) and time (1–3 h). Under optimized conditions, the protein yield and protein content were 24.24 % (RSM), 28.03 % (ANN-GA), 87.17 % (RSM), and 88.69 % (ANN-GA). Compared to RSM, the ANN model demonstrated a notably more significant coefficient of determination in the overall output values (RSM (0.969 (protein yield), 0.989 (protein content) and ANN-GA (0.996 (protein yield), 0.996 (protein content)), showing superior performance during validation. The SSC protein isolates contained considerable quantities of all the essential amino acids except lysine. Its good nutritional index (61.87) and high crucial amino acid score (70.98) make it a high-quality protein. According to FAO standards, the amino acid score indicates the abundance of all essential amino acids, making it a helpful protein supplement for meeting dietary requirements. Furthermore, this research highlights the potential to utilize industrial byproducts as economical substrates for protein isolation efficiently. |
| format | Article |
| id | doaj-art-c4207e78ffff409cac3aa81a7c44c12f |
| institution | DOAJ |
| issn | 2666-1543 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of Agriculture and Food Research |
| spelling | doaj-art-c4207e78ffff409cac3aa81a7c44c12f2025-08-20T02:47:24ZengElsevierJournal of Agriculture and Food Research2666-15432025-08-012210208810.1016/j.jafr.2025.102088Modeling and optimization of protein extraction from sunflower seed Cake: RSM and ANN-GA approachesPooja Vartiya0Piyush Kashyap1Bhagya Raj2Maanas Sharma3Mohd Adnan4Syed Amir Ashraf5Rahul Mehra6Department of Food Technology and Nutrition, School of Agriculture, Lovely Professional University, Phagwara, 144411, (Punjab), IndiaDepartment of Food Technology and Nutrition, School of Agriculture, Lovely Professional University, Phagwara, 144411, (Punjab), India; Corresponding author. Dept. of Food Technology & Nutrition, School of Agriculture, Lovely Professional University, Phagwara, 144411, Punjab, India.Post Harvest Technology Centre, Acharya N.G. Ranga Agricultural University, Bapatla, 522101, (Andhra Pradesh), IndiaDepartment of Food Technology and Home Science, Vivekananda College, University of Delhi, Vivek Vihar, 11095, (New Delhi), IndiaDepartment of Biology, College of Science, University of Ha'il, PO Box 2440, Ha'il, Saudi ArabiaDepartment of Clinical Nutrition, College of Applied Medical Sciences, University of Ha'il, PO Box 2440, Ha'il, Saudi ArabiaUniversity Centre for Research & Development, Chandigarh University, Gharuan, Mohali, Punjab, 140413, IndiaSunflower seed cake (SSC) is an agricultural waste that is rich in proteins and numerous biologically active compounds. Moreover, SSC is devoid of any anti-nutritional compounds. Therefore, it can be leveraged for many food applications. In this work, SSC was explored for the extraction of proteins. Preliminary experiments on defatted and de-phenolized SSC were carried out using one-factor analysis. Protein extraction from sunflower seed cake was performed following isoelectric precipitation, and the amino acid profile was analyzed. Response surface methodology (RSM) and artificial neural networks (ANNs) were used to optimize the extraction conditions, i.e., pH (8.5–10.5), temperature (25–45 °C), solvent-solid ratio (10–30 mL/g) and time (1–3 h). Under optimized conditions, the protein yield and protein content were 24.24 % (RSM), 28.03 % (ANN-GA), 87.17 % (RSM), and 88.69 % (ANN-GA). Compared to RSM, the ANN model demonstrated a notably more significant coefficient of determination in the overall output values (RSM (0.969 (protein yield), 0.989 (protein content) and ANN-GA (0.996 (protein yield), 0.996 (protein content)), showing superior performance during validation. The SSC protein isolates contained considerable quantities of all the essential amino acids except lysine. Its good nutritional index (61.87) and high crucial amino acid score (70.98) make it a high-quality protein. According to FAO standards, the amino acid score indicates the abundance of all essential amino acids, making it a helpful protein supplement for meeting dietary requirements. Furthermore, this research highlights the potential to utilize industrial byproducts as economical substrates for protein isolation efficiently.http://www.sciencedirect.com/science/article/pii/S2666154325004594Sunflower seed cakeProteinAmino acidsResponse surface methodologyArtificial neural network |
| spellingShingle | Pooja Vartiya Piyush Kashyap Bhagya Raj Maanas Sharma Mohd Adnan Syed Amir Ashraf Rahul Mehra Modeling and optimization of protein extraction from sunflower seed Cake: RSM and ANN-GA approaches Journal of Agriculture and Food Research Sunflower seed cake Protein Amino acids Response surface methodology Artificial neural network |
| title | Modeling and optimization of protein extraction from sunflower seed Cake: RSM and ANN-GA approaches |
| title_full | Modeling and optimization of protein extraction from sunflower seed Cake: RSM and ANN-GA approaches |
| title_fullStr | Modeling and optimization of protein extraction from sunflower seed Cake: RSM and ANN-GA approaches |
| title_full_unstemmed | Modeling and optimization of protein extraction from sunflower seed Cake: RSM and ANN-GA approaches |
| title_short | Modeling and optimization of protein extraction from sunflower seed Cake: RSM and ANN-GA approaches |
| title_sort | modeling and optimization of protein extraction from sunflower seed cake rsm and ann ga approaches |
| topic | Sunflower seed cake Protein Amino acids Response surface methodology Artificial neural network |
| url | http://www.sciencedirect.com/science/article/pii/S2666154325004594 |
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