OBJECTIVE To evaluate the quality of Amomum tsao -ko from different origins and harvesting periods comprehensively. METHODS The contents of total volatile oil in A. tsao -ko were determined by volatile oil measurement method A stated in 2020 edition of Chinese Pharmacopoeia （part Ⅳ）；the contents of total flavonoids and total polyphenols in A. tsao -ko were determined by aluminum nitrate-sodium nitrite colorimetry and folin-ciocalteu method. The contents of α-pinene，β-pinene， 1，8-cineole，α-terpineol，geraniol and trans-nerolidol in the volatile oil of A. tsao -ko were determined by gas chromatography ；the contents of protocatechuate and vanillic acid in A. tsao -ko were determined by ulta high performance liquid chromatography. The above 11 indicators were selected ，and entropy weight TOPSIS method was used to comprehensively evaluate the quality of 16 batches of A. tsao -ko. RESULTS The contents of total volatile oil ，total flavonoids ，total polyphenols ，α-pinene，β-pinene， 1，8-cineole，α-terpineol，geraniol，trans-nerolidol，protocatechuate and vanillic acid in 16 batches of A. tsao -ko were 15.833 3- 28.000 0 μL/g，29.100 5-78.199 6 mg/g，6.789 8-35.797 7 mg/g，0.088 7-0.401 3 mg/g，0.106 3-0.408 0 mg/g，3.709 6-8.533 1 mg/g，0.259 8-0.599 6 mg/g，0.314 8-1.324 1 mg/g，0.272 3-0.576 4 mg/g，9.301 2-19.818 5 μg/g，8.180 9-27.666 3 μg/g， respectively. Entropy weight TOPSIS results showed that the top three of relative closeness rankings were A. tsao -ko produced by Yunnan Baoshan in July ，Yunnan Honghe in October ，Yunnan Wenshan in September ；the last three of relative closeness rankings were A. tsao -ko produced by Yunnan Dehong in September ，Yunnan Dehong in November ，Yunnan Dehong in December. CONCLUSIONS A. tsao -ko produced by Yunnan Baoshan in July ，Yunnan Honghe in October and Yunnan Wenshan in September present better quality.

OBJECTIVE Optimizing the water extraction technology of Xiangqin jiere granules. METHODS The orthogonal test of 3 factors and 3 levels was designed， and comprehensive scoring was conducted for the above indexes by using G1-entropy weight to obtain the optimized water extraction technology of Xiangqin jiere granules with water addition ratio， extraction time and extraction times as factors， using the contents of forsythoside A， baicalin， phillyrin， oroxylin A-7-O-β-D-glycoside， wogonoside， baicalein and wogonin， and extraction rate as evaluation indexes. BP neural network modeling was used to optimize the network model and water extraction process using the results of 9 groups of orthogonal tests as test and training data， the water addition multiple， decocting time and extraction times as input nodes， and the comprehensive score as output nodes. Then the two analysis methods were compared by verification test to find the best water extraction process parameters. RESULTS The water extraction technology optimized by the orthogonal test was 8-fold water， extracting 3 times， extracting for 1 h each time. Comprehensive score was 96.84 （RSD＝0.90%）. The optimal water extraction technology obtained by BP neural network modeling included 12-fold water， extracting 4 times， extracting for 0.5 h each time. The comprehensive score was 92.72 （RSD＝0.77%）， which was slightly lower than that of the orthogonal test. CONCLUSIONS The water extraction technology of Xiangqin jiere granules is optimized successfully in the study， which includes adding 8-fold water， extracting 3 times， and extracting for 1 hour each time.