DoE-Guided Multi-Response Optimization of Harvesting and Drying for Maximized Macromolecule Recovery in Chlorella sp.

Harvesting and drying are critical post-harvest operations in microalgal biomass processing because they strongly influence biomass conditioning and the subsequent recoverability of major macromolecular fractions. Accordingly, this study evaluated and optimized harvesting and drying conditions to identify processing windows associated with carbohydrate, protein, and lipid responses in Chlorella sp. (UFPS012). An I-optimal design was applied to assess drying temperature (40–60 °C), drying time (18–30 h), equipment (oven vs. food-grade dehydrator), and harvesting method (chemical flocculation vs. electroflotation). Subsequently, temperature and time were optimized using a central composite design while keeping electroflotation and the food-grade dehydrator fixed. The harvesting method was consistently significant across responses, whereas drying factors showed metabolite-dependent effects. During the screening stage, carbohydrates were mainly influenced by drying time and harvesting method, proteins by drying time and equipment, and lipids by drying temperature, equipment, and harvesting method. In the optimization stage, the fitted quadratic models showed high goodness of fit (R2 = 0.9778–0.9959), and the desirability function identified a compromise condition at 56.78 °C and 41.28 h. Under these conditions, the model predicted approximately 155.0 mg/L of total carbohydrates, 368.4 mg/L of total proteins, and 15.2 mg/L of total lipids. Process validation showed no significant difference between predicted and observed values for proteins, whereas carbohydrates and lipids differed significantly. In parallel, the moisture ratio approached zero at approximately 2460 min, consistent with the late stage of drying. Overall, electroflotation, coupled with food-grade dehydration, defined a laboratory-scale post-harvest configuration for the simultaneous conditioning of Chlorella biomass for multi-metabolite recovery. Future studies should evaluate specific energy demand, techno-economic feasibility, alternative drying technologies, and other Chlorella-relevant high-value compounds such as carotenoids.

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Publication Details

Journal
Phycology
Published
2026-03-27
DOI
https://doi.org/10.3390/phycology6020035
Primary Topic
Algal biology and biofuel production
Type
article
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article

DoE-Guided Multi-Response Optimization of Harvesting and Drying for Maximized Macromolecule Recovery in Chlorella sp.

Néstor A. Urbina-Suarez, Roberto Lavecchia, Janet B. García-Martínez, Antonio Zuorro et al.
Phycology
Algal biology and biofuel production
article

DoE-Guided Multi-Response Optimization of Harvesting and Drying for Maximized Macromolecule Recovery in Chlorella sp.

Néstor A. Urbina-Suarez, Roberto Lavecchia, Janet B. García-Martínez, Antonio Zuorro, Andrés F. Barajas-Solano, Jefferson E. Contreras-Ropero, German L. Lopez-Barrera
article en

Abstract

Harvesting and drying are critical post-harvest operations in microalgal biomass processing because they strongly influence biomass conditioning and the subsequent recoverability of major macromolecular fractions. Accordingly, this study evaluated and optimized harvesting and drying conditions to identify processing windows associated with carbohydrate, protein, and lipid responses in Chlorella sp. (UFPS012). An I-optimal design was applied to assess drying temperature (40–60 °C), drying time (18–30 h), equipment (oven vs. food-grade dehydrator), and harvesting method (chemical flocculation vs. electroflotation). Subsequently, temperature and time were optimized using a central composite design while keeping electroflotation and the food-grade dehydrator fixed. The harvesting method was consistently significant across responses, whereas drying factors showed metabolite-dependent effects. During the screening stage, carbohydrates were mainly influenced by drying time and harvesting method, proteins by drying time and equipment, and lipids by drying temperature, equipment, and harvesting method. In the optimization stage, the fitted quadratic models showed high goodness of fit (R2 = 0.9778–0.9959), and the desirability function identified a compromise condition at 56.78 °C and 41.28 h. Under these conditions, the model predicted approximately 155.0 mg/L of total carbohydrates, 368.4 mg/L of total proteins, and 15.2 mg/L of total lipids. Process validation showed no significant difference between predicted and observed values for proteins, whereas carbohydrates and lipids differed significantly. In parallel, the moisture ratio approached zero at approximately 2460 min, consistent with the late stage of drying. Overall, electroflotation, coupled with food-grade dehydration, defined a laboratory-scale post-harvest configuration for the simultaneous conditioning of Chlorella biomass for multi-metabolite recovery. Future studies should evaluate specific energy demand, techno-economic feasibility, alternative drying technologies, and other Chlorella-relevant high-value compounds such as carotenoids.

PhycologyVol. 6(2)
Francisco de Paula Santander University (CO), Sapienza University of Rome (IT)
Openalex Percentile: Top 9%
Algal biology and biofuel production
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