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Rehman,Abdul; Qamar,Rafi; E. Safdar,Muhammad; ,Atique-ur-Rehman; M.R. Javeed,Hafiz; Maqbool,Rizwan; Farooq,Naila; Shahzad,Muhammad; Ali,Mazhar; H. Tarar,Zahid. |
Abstract Background: Parthenium hysterophorus L., commonly known as parthenium weed, poses severe economic and environmental hazards to the agro-ecosystems of Pakistan. Objective: To estimate the yield loss and critical competition period of this weed in the spring sown maize crop. Method: Field studies were conducted at an agronomic research area in the College of Agriculture at the University of Sargodha in Punjab-Pakistan during two consecutive year spring seasons (2014 and 2015). Treatments were comprised of viz., control plots (weed free), and parthenium competition durations of 2, 3, 4, 5 and 6 weeks after crop emergence (WAE), as well as weedy check for the full growing season of the crop. Results: Study results showed that the prolongation... |
Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Competition duration; Parthenium; Spring maize; Yield loss; Logistic model. |
Ano: 2020 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-83582020000100327 |
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Liu,Yi; Yang,Shenjiao; Li,Shiqing; Chen,Fang. |
Effects of meteorological variables on crop production can be evaluated using various models. We have evaluated the ability of the Hybrid-Maize model to simulate growth, development and grain yield of maize (Zea mays L.) cultivated on the Loess Plateau, China, and applied it to assess effects of meteorological variations on the performance of maize under rain-fed and irrigated conditions. The model was calibrated and evaluated with data obtained from field experiments performed in 2007 and 2008, then applied to yield determinants using daily weather data for 2005-2009, in simulations under both rain-fed and irrigated conditions. The model accurately simulated Leaf Area Index , biomass, and soil water data from the field experiments in both years, with... |
Tipo: Info:eu-repo/semantics/article |
Palavras-chave: Crop simulation; Maize model; Potential productivity; Water stress; Spring maize. |
Ano: 2012 |
URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0103-90162012000500003 |
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