No abstract

Spirulina acts as a good dietary nutritional supplement. However, few research studies have been conducted on its fermentation. Three groups of probiotic combinations, lactic acid bacteria, Bacillus strains, and their mixture, were used to investigate Spirulina fermentation. The results showed that lactic acid bacteria significantly increased the content of amino acids and the ratio of essential amino acids to total amino acids in the fermented Spirulina, compared with the unfermented Spirulina, and this trend was enhanced by the strains' mixture. However, compared to unfermented Spirulina, the amino acid levels were significantly decreased after fermentation with Bacillus strains and so was the total free amino acid and essential amino acid content. Fermentation significantly reduced the contents of the offensive components of Spirulina, with significant differences among the three mixed bacterial treatments. Moreover, Bacillus strain fermentation increased the contents of flavonoids and polyphenols compared to the unfermented Spirulina, and significantly enhanced 1,1‐diphenyl‐2‐trinitrophenylhydrazine free‐radical scavenging ability and total antioxidant ability. On the contrary, treatments with lactic acid bacteria and the mixture of lactic acid bacteria and Bacillus strains endowed the fermented supernatants with good antibacterial ability. The results showed that probiotic fermentation has a good effect on Spirulina and can serve as a new procedure for developing new Spirulina‐containing food items.

It has important theoretical value and practical significance to study the impact of agricultural mechanization (AM) on agriculture environment efficiency (AEE), as AM is an important way to improve the level of rural modernization and accelerate the high-quality development of agriculture, while the increase of energy consumption of AM has brought greenhouse gas emissions. Using the panel data of 30 provinces in China from 2001 to 2019, this article adopts stochastic frontier analysis method with output oriented distance function to measure AEE based on net carbon sink, and empirically analyzes the impact of AM on AEE. The empirical analysis finds that the AEE of the whole country and all provinces shows an upward trend with time, and has significant spatial positive autocorrelation characteristics. There is a Kuznets inverted "U" relationship between AM and AEE.Meanwhile, AM has spatial spillover effect and time cumulative effect on AEE, and this basic conclusion is still robust after using instrumental variables, spatial autoregressive model, sub sample regression, changing spatial weight matrix and independent. Further research shows that the effect of AM on AEE depends on the input effect and output effect caused by AM, and the mechanism is mainly reflected in agricultural technology progress, expansion of the scale of agricultural operation, optimization of resource allocation and spatial spillover. Given these findings, the paper adds considerable value to the empirical literature and also provides various policy-and practical implications.

No abstract

It has important theoretical value and practical significance to study the impact of agricultural mechanization (AM) on agriculture environment efficiency (AEE), as AM is an important way to improve the level of rural modernization and accelerate the high-quality development of agriculture, while the increase of energy consumption of AM has brought greenhouse gas emissions. Using the panel data of 30 provinces in China from 2001 to 2019, this article adopts stochastic frontier analysis method with output oriented distance function to measure AEE based on net carbon sink, and empirically analyzes the impact of AM on AEE. The empirical analysis finds that the AEE of the whole country and all provinces shows an upward trend with time, and has significant spatial positive autocorrelation characteristics. There is a Kuznets inverted "U" relationship between AM and AEE. Meanwhile, AM has spatial spillover effect and time cumulative effect on AEE, and this basic conclusion is still robust after using instrumental variables, spatial autoregressive model, sub sample regression, changing spatial weight matrix and independent. Further research shows that the effect of AM on AEE depends on the input effect and output effect caused by AM, and the mechanism is mainly reflected in agricultural technology progress, expansion of the scale of agricultural operation, optimization of resource allocation and spatial spillover. Given these findings, the paper adds considerable value to the empirical literature and also provides various policy- and practical implications.