The strains with large vacuales is more suitable since these strains can store more lipids inside

Criteria do not fall from the sky themselves. They need to be developed. This is usually done on the basis of empirical data and the results of objective measurements or expert assessments. A normative approach is used for this purpose. This approach is based on the concept of norm. The average is usually chosen as the norm. But what to take this average about is a question. Either from the source data or from secondary data obtained by processing the primary data. I'm sure the 2nd option is better. There is a software system a personal level system (with a zero threshold of entry) that allows you to implement a normative approach and develop scientifically based criteria for their further application in the criteria approach.

Критерии с неба сами не падают. Их надо разрабатывать. Обычно это делается на основе эмпирических данных и результатов объективных измерений или экспертных оценок. Для этого применяется нормативный подход. Этот подход основан на понятии нормы. В качестве нормы обычно выбирается среднее. Но вот о чего брать это среднее - это вопрос. Или по исходным данным, или по вторичным данным, полученных путем обработки первичных данных. Я уверен, что 2-й вариант лучше. Есть программная система система персонального уровня (с нулевым порогом входа), позволяющая реализовать нормативный подход и выработать научно-обоснованные критерии для их дальнейшего применения в критериальном подходе.

The Eidos-X++ system differs from other artificial intelligence systems in the following parameters:

- was developed in a universal setting, independent of the subject area. Therefore, it is universal and can be applied in many subject areas (http://lc.kubagro.ru/aidos/index.htm);

- is in full open free access (http://lc.kubagro.ru/aidos/_Aidos-X.htm), and with the relevant source texts (http://lc.kubagro.ru/__AIDOS-X.txt);

- is one of the first domestic systems of artificial intelligence of the personal level, i.e. it does not take special training in the field of technologies of artificial intelligence from the user (there is an act of introduction of system "Eidos" of 1987) (http://lc.kubagro.ru/aidos/aidos02/PR-4.htm);

- provides stable identification in a comparable form of strengh and direction of cause-effect relationships in incomplete noisy interdependent (nonlinear) data of very large dimension of numerical and non-numerical nature, measured in different types of scales (nominal, ordinal and numerical) and in different units of measurement (i.e. does not impose strict requirements to the data that can not be performed, and processes the data that is);

- contains a large number of local (supplied with the installation) and cloud educational and scientific applications (currently 31 and 196, respectively) (http://lc.kubagro.ru/aidos/Presentation_Aidos-online.pdf);

- provides multilingual interface support in 44 languages. Language databases are included in the installation and can be replenished automatically;

- supports on-line environment of knowledge accumulation and is widely used all over the world (http://aidos.byethost5.com/map5.php);

- the most time-consuming computationally, the operations of the synthesis models and implements recognition by using graphic processing unit (GPU) that some tasks can only support up to the solution of these tasks is several thousand times that really provides intelligent processing of big data, big information and big knowledge;

- provides transformation of the initial empirical data into information, and its knowledge and solution using this knowledge of classification problems, decision support and research of the subject area by studying its system-cognitive model, generating a very large number of tabular and graphical output forms (development of cognitive graphics), many of which have no analogues in other systems (examples of forms can be found in: http://lc.kubagro.ru/aidos/aidos18_LLS/aidos18_LLS.pdf);

- well imitates the human style of thinking: gives the results of the analysis, understandable to experts on the basis of their experience, intuition and professional competence.

Dear Desikan Ramesh

The criteria are really dependent on the researcher him-/herself based on the objective.

Many parameters can be considered during the selection of microalgae:

Lipid content

Carbohydrate content

CO2 conversion rate

Specific growth rate

Biomass productivity

Pigment content etc

There are lots of review papers.

Thank you