| Title |
Empiric mathematical model for predicting the content of alpha-acids in hop (Humulus lupulus L.) cv. Aurora
|
|---|---|
| Published in |
SpringerPlus, February 2013
|
| DOI | 10.1186/2193-1801-2-59 |
| Pubmed ID | |
| Authors |
Siniša Srečec, Barbara Čeh, Tanja Savić Ciler, Alenka Ferlež Rus |
| Abstract |
The aim of this research is to find a simple mathematical model due to sum of effective temperatures and rainfalls from second germination after spring pruning till the technological maturity of hop cones, in order to achieve reliable prognosis of alpha-acids content in hop cv. Aurora. After mathematical analyses of experimental data by Eurequa Formulize 0.96 Beta software 17 equations were offered, and after substituting the values of dependent and independent variables in all equations only one equation was chosen with p = 0.034 (p<0.05). This equation is not reliable in extremely drought year if crop evapotranspiration ET0 in July is higher than 4.5, primarily because of negative influence on formation and development of hop glandular trichomes. Considering achieved results it is possible to suggest following general equation for alpha-acids accumulation in hop: y = [(k 1 w) - k 2 - (k 3 w (2))/x] ÷ (-10) ↔ ET 0 July ≤ 4.5. Where y is alpha acids content in dry matter (%), x = sum of effective temperatures and w = sum of rainfals, both from second germination after spring pruning till technological maturity of hop cones. Coefficients k 1 , k 2 and k 3 are determined for cultivar Aurora (53.8, 453 and 1.33, respectively). |
Mendeley readers
The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 14 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 4 | 29% |
| Other | 2 | 14% |
| Student > Doctoral Student | 2 | 14% |
| Professor | 2 | 14% |
| Student > Master | 2 | 14% |
| Other | 2 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 7 | 50% |
| Engineering | 3 | 21% |
| Biochemistry, Genetics and Molecular Biology | 2 | 14% |
| Earth and Planetary Sciences | 1 | 7% |
| Unknown | 1 | 7% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 03 July 2018.
All research outputs
#7,180,770
of 22,696,971 outputs
Outputs from SpringerPlus
#455
of 1,852 outputs
Outputs of similar age
#61,517
of 193,023 outputs
Outputs of similar age from SpringerPlus
#18
of 113 outputs
Altmetric has tracked 22,696,971 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 1,852 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.7. This one has gotten more attention than average, scoring higher than 73% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 193,023 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 67% of its contemporaries.
We're also able to compare this research output to 113 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.