Influences of nitrogen fertilization and harvest time on combustion quality of four perennial grasses in a semi-arid Mediterranean climate

2019 ◽  
Vol 128 ◽  
pp. 239-247 ◽  
Author(s):  
Recep Irfan Nazli ◽  
Veyis Tansi
2009 ◽  
Vol 70 (1) ◽  
pp. 135-144 ◽  
Author(s):  
Marek Gajewski ◽  
Zenon Węglarz ◽  
Anna Sereda ◽  
Marta Bajer ◽  
Agnieszka Kuczkowska ◽  
...  

Quality of Carrots Grown for Processing as Affected by Nitrogen Fertilization and Harvest TermIn 2007-2008 the effect of nitrogen fertilization and harvest term on quality of two carrot cultivars was investigated. The field experiment was carried out in Żelazna Experimental Station of Warsaw University of Life Sciences. Karotan F1and Trafford F1cultivars, commonly grown for juice industry, were the objects of the experiment. Carrot seeds were sown at the beginning of May. Nitrogen fertilization was applied in five rates, ranged from 0 to 120 kg·ha-1and in two terms — before sowing and in the middle of growing season. Roots were harvested in three terms: mid-September, mid-October and the first decade of November. After harvest there were determined: nitrates (NO3) content in carrot roots and juice, soluble solids, colour parameters of juice in CIE L*a*b*system. The dose and the term of nitrogen fertilization influenced nitrates content in carrots, and the highest NO3concentration was found in carrots fertilized with 120 kg·ha-1of N before sowing. Karotan showed higher nitrates accumulation than Trafford. The content of nitrates in the roots was markedly higher than in carrot juice. Nitrates content in carrots decreased with delaying of harvest time, in opposite to soluble solids content. Soluble solids content and colour parameters of carrot juice were not affected by nitrogen fertilization, but the lowest L*, a*and b*values were observed at the last term of harvest.


2020 ◽  
Vol 51 (1) ◽  
pp. 90-98
Author(s):  
Blazquez Francisco Rubén ◽  
Daniel Valerio Peláez ◽  
Romina Jessica Andrioli ◽  
Omar Raúl Elia

Author(s):  
I.G.C. Kerr ◽  
J.M. Williams ◽  
W.D. Ross ◽  
J.M. Pollard

The European rabbit (Oryctolagus cuniculus) introduced into New Zealand in the 183Os, has consistently flourished in Central Otago, the upper Waitaki, and inland Marlborough, all areas of mediterranean climate. It has proved difficult to manage in these habitats. The 'rabbit problem' is largely confined to 105,000 ha of low producing land mostly in semi arid areas of Central Otago. No field scale modifications of the natural habitat have been successful in limiting rabbit numbers. The costs of control exceed the revenue from the land and continued public funding for control operations appears necessary. A system for classifying land according to the degree of rabbit proneness is described. Soil survey and land classification information for Central Otago is related to the distribution and density of rabbits. This intormation can be used as a basis for defining rabbit carrying capacity and consequent land use constraints and management needs. It is concluded that the natural rabbit carrying capacity of land can be defined by reference to soil survey information and cultural modification to the natural vegetation. Classification of land according to rabbit proneness is proposed as a means of identifying the need for, and allocation of, public funding tor rabbit management. Keywords: Rabbit habitat, rabbit proneness, use of rabbit prone land.


Sensors ◽  
2021 ◽  
Vol 21 (9) ◽  
pp. 2940
Author(s):  
Luciano Ortenzi ◽  
Simone Figorilli ◽  
Corrado Costa ◽  
Federico Pallottino ◽  
Simona Violino ◽  
...  

The degree of olive maturation is a very important factor to consider at harvest time, as it influences the organoleptic quality of the final product, for both oil and table use. The Jaén index, evaluated by measuring the average coloring of olive fruits (peel and pulp), is currently considered to be one of the most indicative methods to determine the olive ripening stage, but it is a slow assay and its results are not objective. The aim of this work is to identify the ripeness degree of olive lots through a real-time, repeatable, and objective machine vision method, which uses RGB image analysis based on a k-nearest neighbors classification algorithm. To overcome different lighting scenarios, pictures were subjected to an automatic colorimetric calibration method—an advanced 3D algorithm using known values. To check the performance of the automatic machine vision method, a comparison was made with two visual operator image evaluations. For 10 images, the number of black, green, and purple olives was also visually evaluated by these two operators. The accuracy of the method was 60%. The system could be easily implemented in a specific mobile app developed for the automatic assessment of olive ripeness directly in the field, for advanced georeferenced data analysis.


Hydrobiologia ◽  
2021 ◽  
Author(s):  
José Etham de Lucena Barbosa ◽  
Juliana dos Santos Severiano ◽  
Hérika Cavalcante ◽  
Daniely de Lucena-Silva ◽  
Camila Ferreira Mendes ◽  
...  

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