AIMC Topic: Starch

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From root to result: Portable NIRS-based non-destructive prediction of cassava quality traits.

PloS one
Cassava (Manihot esculenta Crantz) is a staple food and a key industrial crop across tropical regions, but traditional phenotyping for critical quality traits like dry matter content (DMC) and starch content (StC) is a laborious and low-throughput pr...

Morphological characterization and machine learning-based hyperspectral identification of naturally pigmented traditional Chinese starches.

Food chemistry
As an intangible cultural heritage, food products derived from naturally pigmented traditional starches are facing a market trust crisis due to the adulteration of dyed starch. This study aimed to develop an integrated identification system to differ...

3D-printed chitosan-starch mesh filled with minocycline-alginate hydrogel for dual anti-Staphylococcus aureus and osteogenic effects.

Carbohydrate polymers
Bone infections, particularly those caused by Staphylococcus aureus, pose clinical challenges due to biofilm formation and association with bone loss. To address this, we developed a three-dimensional (3D) printed hydrogel-based drug delivery device ...

Genetically engineered 3D printed functionally graded-lignin, starch, and cellulose-derived sustainable biopolymers and composites: A critical review.

International journal of biological macromolecules
The integration of plant biotechnology with Fused Deposition Modeling (FDM) is emerging as a transformative approach for sustainable manufacturing. This review explores the application of genetically engineered biopolymers including starch-based, cel...

Direct estimation of amylose and amylopectin in single starch granules by machine learning assisted Raman spectroscopy.

Carbohydrate polymers
Starch is a fundamental carbohydrate with nutritional and physicochemical properties governed by relative proportions of amylose and amylopectin. Variations in amylose-to-amylopectin ratio significantly influence starch digestibility, texture, glycem...

Advanced data-driven interpretable analysis for predicting resistant starch content in rice using NIR spectroscopy.

Food chemistry
Resistant starch (RS) is a vital dietary component with notable health benefits, but tradition quantification methods are labor-intensive, costly, and unsuitable for large-scale applications. This study introduced an innovative data-driven framework ...

Advanced 3D Food Printing with Simultaneous Cooking and Generative AI Design.

Advanced materials (Deerfield Beach, Fla.)
3D food printing is an indispensable technology for emerging food technologies. However, conventional nonconcurrent postprocessing methods limit the final food quality, including the unappealing nature of food ink modification, imperfections in retai...

Fusion of convolutional neural network with XGBoost feature extraction for predicting multi-constituents in corn using near infrared spectroscopy.

Food chemistry
Near-infrared (NIR) spectroscopy has been widely utilized to predict multi-constituents of corn in agriculture. However, directly extracting constituent information from the NIR spectra is challenging due to many issues such as broad absorption band,...

Novel strategy for optimizing of corn starch-based ink food 3D printing process: Printability prediction based on BP-ANN model.

International journal of biological macromolecules
Although starch has been intensively studied as a raw material for 3D printing, the relationship between several important process parameters in the preparation of starch gels and the printing results is unclear. In this study, the relationship betwe...

Rice Origin Tracing Technology Based on Fluorescence Spectroscopy and Stoichiometry.

Sensors (Basel, Switzerland)
The origin of agricultural products is crucial to their quality and safety. This study explored the differences in chemical composition and structure of rice from different origins using fluorescence detection technology. These differences are mainly...