Dynamics of luminescence characteristics of Haematococcus lacustris cultures in different cultivation conditions

Luminescence ◽  
2022 ◽  
Author(s):  
Vladislav E. Erokhin ◽  
Galina S. Minyuk ◽  
Alla P. Gordienko ◽  
Sergey V. Kapranov
2013 ◽  
Vol 38 (7) ◽  
pp. 1286-1294 ◽  
Author(s):  
Zong-Xin LI ◽  
Yuan-Quan CHEN ◽  
Qing-Cheng WANG ◽  
Kai-Chang LIU ◽  
Wang-Sheng GAO ◽  
...  

2021 ◽  
pp. 2100023
Author(s):  
Kong‐Chao Shen ◽  
Jing‐Kun Wang ◽  
Yang Shen ◽  
Yan‐Qing Li ◽  
Ming‐Lei Guo ◽  
...  

2021 ◽  
Vol 60 (3) ◽  
pp. 1480-1490
Author(s):  
Shi-Ping Wang ◽  
Yuan Li ◽  
Zhi-Xiang Zhang ◽  
Yu Zhang ◽  
Yu Wang ◽  
...  

Horticulturae ◽  
2021 ◽  
Vol 7 (4) ◽  
pp. 81
Author(s):  
Yunduan Li ◽  
Yuanyuan Zhang ◽  
Xincheng Liu ◽  
Yuwei Xiao ◽  
Zuying Zhang ◽  
...  

Volatile compounds principally contribute to flavor of strawberry (Fragaria × ananassa) fruit. Besides to genetics, cultivation conditions play an important role in fruit volatile formation. Compared to soil culture as control, effects of substrate culture on volatile compounds of two strawberry cultivars (‘Amaou’ and ‘Yuexin’) were investigated. GC-MS analysis revealed significant difference in volatile contents of ‘Amaou’ strawberry caused by substrate culture. No significant effect was observed for cultivar ‘Yuexin’. For ‘Amaou’ strawberry from soil culture produced higher volatile contents compared with substrate culture. This difference is contributed by high contents of esters, lactones, ketones, aldehydes, terpenes, hydrocarbons, acids, furans and phenols in ‘Amaou’ strawberry fruit from soil culture. Furanones, beta-linalool, trans-Nerolidol and esters are major contributor to strawberry aroma, whose contents are higher in soil culture planted fruit when compared to substrate culture. Moreover, strawberry fruit from soil culture had higher transcripts related to volatile biosynthesis were observed, including FaQR, FaOMT, FaNES1, FaSAAT and FaAAT2.


Agronomy ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 1353
Author(s):  
Michela Palumbo ◽  
Bernardo Pace ◽  
Maria Cefola ◽  
Francesco Fabiano Montesano ◽  
Francesco Serio ◽  
...  

Computer Vision Systems (CVS) represent a contactless and non-destructive tool to evaluate and monitor the quality of fruits and vegetables. This research paper proposes an innovative CVS, using a Random Forest model to automatically select the relevant features for classification, thereby avoiding their choice through a cumbersome and error-prone work of human designers. Moreover, three color correction techniques were evaluated and compared, in terms of classification performance to identify the best solution to provide consistent color measurements. The proposed CVS was applied to fresh-cut rocket, produced under greenhouse soilless cultivation conditions differing for the irrigation management strategy and the fertilization level. The first aim of this study was to objectively estimate the quality levels (QL) occurring during storage. The second aim was to non-destructively, and in a contactless manner, identify the cultivation approach using the digital images of the obtained product. The proposed CVS achieved an accuracy of about 95% in QL assessment and about 65–70% in the discrimination of the cultivation approach.


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