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Abstract Phase retrieval methods used in computer generated holograms such as Gerchberg-Saxton and gradient descent give results which are prone to noise and other defects. This work builds up on the idea of time-averaging multiple hologram frames, first introduced in methods like One-Step Phase-Retrieval and Adaptive One-Step Phase-Retrieval. The proposed technique called Multi-Frame Holograms Batched Optimization uses the L-BFGS optimization algorithm to simultaneously generate a batch of binary phase holograms which result in an average reconstructed image of improved fidelity and fast algorithmic convergence, both in the Fraunhoffer and the Fresnel regimes. The results are compared to One-Step Phase-Retrieval and Adaptive One-Step Phase-Retrieval in simulation and experimentally, proving the superiority of the proposed approach. This technique can be easily extended to other spatial modulation methods.

Sweet potato (Ipomoea batatas) noodles are a traditional Chinese food with a high nutritional value; however, starch adulteration is a big concern. The objective of this study was to develop a reliable method for the rapid detection of cassava (Manihot esculenta) components in sweet potato noodles to protect consumers from commercial adulteration. Five specific Loop-mediated Isothermal Amplification (LAMP) primers targeting the internal transcribed spacer (ITS) of cassava were designed, genomic DNA was extracted, the LAMP reaction system was optimized, and the specificity of the primers was verified with genomic DNA of cassava, Ipomoea batatas, Zea mays, and Solanum tuberosum; the detection limit was determined with a serial dilution of adulterated sweet potato starch with cassava starch, and the real-time LAMP method for the detection of the cassava-derived ingredient in sweet potato noodles was established. The results showed that the real-time LAMP method can accurately and specifically detect the cassava component in sweet potato noodles with a detection limit of 1%. Furthermore, the LAMP assay was validated using commercial sweet potato noodle samples, and results showed that 57.7% of sweet potato noodle products (30/52) from retail markets were adulterated with cassava starch in China. This study provides a promising solution for facilitating the surveillance of the commercial adulteration of sweet potato noodles from retail markets.