Informacja

Drogi użytkowniku, aplikacja do prawidłowego działania wymaga obsługi JavaScript. Proszę włącz obsługę JavaScript w Twojej przeglądarce.

Wyszukujesz frazę "Ma, Y." wg kryterium: Autor


Wyświetlanie 1-3 z 3
Tytuł:
Case study of developing an integrated water and nitrogen scheme for agricultural system on the North China Plain
Autorzy:
Liu, Y.
Tao, F.
Lao, Y.
Ma, J.
Powiązania:
https://bibliotekanauki.pl/articles/25700.pdf
Data publikacji:
2013
Wydawca:
Polska Akademia Nauk. Instytut Agrofizyki PAN
Opis:
Appropriate irrigation and nitrogen fertilization, along with suitable crop management strategies, are essential prerequisites for optimum yields in agricultural systems. This research attempts to provide a scientific basis for sustainable agricultural production management for the North China Plain and other semi-arid regions. Based on a series of 72 treatments over 2003-2008, an optimized water and nitrogen scheme for winter wheat/summer maize cropping system was developed. Integrated systems incorporating 120 mm of water with 80 kg N ha-1 N fertilizer were used to simulate winter wheat yields in Hebei and 120 mm of water with 120 kg N ha-1 were used to simulate winter wheat yields in Shandong and Henan provinces in 2000-2007. Similarly, integrated treatments of 40 kg N ha-1 N fertilizer were used to simulate summer maize yields in Hebei, and 80 kg N ha-1 was used to simulate summer maize yields in Shandong and Henan provinces in 2000-2007. Under the optimized scheme, 341.74 107 mm ha-1 of water and 575.79 104 Mg of urea fertilizer could be saved per year under the wheat/maize rotation system. Despite slight drops in the yields of wheat and maize in some areas, water and fertilizer saving has tremendous long-term eco-environmental benefits.
Źródło:
International Agrophysics; 2013, 27, 4
0236-8722
Pojawia się w:
International Agrophysics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Physical properties of unproductive soils of Northern China
Autorzy:
Malik, Z.
Malik, M.A.
Zong, Y.-T.
Lu, S.-G.
Powiązania:
https://bibliotekanauki.pl/articles/24211.pdf
Data publikacji:
2014
Wydawca:
Polska Akademia Nauk. Instytut Agrofizyki PAN
Tematy:
unproductive soil
soil property
pH
organic matter content
surface area
tensile strength
shear strength
cracking
physical property
Northern China
China
Opis:
The general characteristics: particle size distribution, pH, cation exchange capacity, organic matter content, total NPK, surface area; and physical properties: coefficient of linear extensibility, tensile strength, shear strength and cracking, were investigated in unproductive soils of Northern China. Principle component analysis showed that tensile strength, cohesion, cracking characteristics, clay content, cation exchange capacity and coefficient of linear extensibility were positively correlated with each other, whereas negatively correlated with angle of friction, indicating that these properties were subjected to clay % and smectite content. These correlations might be mainly responsible for low productivity (low yields) in Northern China.
Źródło:
International Agrophysics; 2014, 28, 4
0236-8722
Pojawia się w:
International Agrophysics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Prediction of soil physical properties by optimized support vector machines
Autorzy:
Besalatpour, A.
Hajabbasi, M.A.
Ayoubi, S.
Gharipour, A.
Jazi, A.Y.
Powiązania:
https://bibliotekanauki.pl/articles/24338.pdf
Data publikacji:
2012
Wydawca:
Polska Akademia Nauk. Instytut Agrofizyki PAN
Opis:
The potential use of optimized support vector machines with simulated annealing algorithm in developing prediction functions for estimating soil aggregate stability and soil shear strength was evaluated. The predictive capabilities of support vector machines in comparison with traditional regression prediction functions were also studied. In results, the support vector machines achieved greater accuracy in predicting both soil shear strength and soil aggregate stability properties comparing to traditional multiple-linear regression. The coefficient of correlation (R) between the measured and predicted soil shear strength values using the support vector machine model was 0.98 while it was 0.52 using the multiple-linear regression model. Furthermore, a lower mean square error value of 0.06 obtained using the support vector machine model in prediction of soil shear strength as compared to the multiple-linear regression model. The ERROR% value for soil aggregate stability prediction using the multiple-linear regression model was 14.59% while a lower ERROR% value of 4.29% was observed for the support vector machine model. The mean square error values for soil aggregate stability prediction using the multiplelinear regression and support vector machine models were 0.001 and 0.012, respectively. It appears that utilization of optimized support vector machine approach with simulated annealing algorithm in developing soil property prediction functions could be a suitable alternative to commonly used regression methods.
Źródło:
International Agrophysics; 2012, 26, 2
0236-8722
Pojawia się w:
International Agrophysics
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-3 z 3

    Ta witryna wykorzystuje pliki cookies do przechowywania informacji na Twoim komputerze. Pliki cookies stosujemy w celu świadczenia usług na najwyższym poziomie, w tym w sposób dostosowany do indywidualnych potrzeb. Korzystanie z witryny bez zmiany ustawień dotyczących cookies oznacza, że będą one zamieszczane w Twoim komputerze. W każdym momencie możesz dokonać zmiany ustawień dotyczących cookies