Results 171 to 180 of about 735,768 (237)

Comparing time‐lapse photography and traditional human observation in collecting crop pollinator visitation data Ajastetun valokuvauksen ja perinteisen suoran havainnoinnin vertailu kerättäessä tietoa pölyttäjien kukkakäynneistä viljelykasveilla

open access: yesAgricultural and Forest Entomology, EarlyView.
Time‐lapse photography with commercially available trail cameras provides a competitive alternative to direct human observations for documenting pollinator flower visits, but its performance varies between crops. In apple, the cameras recorded more diverse pollinator assemblages than the human observer due to larger temporal coverage of the camera ...
Marjaana Toivonen, Paula Humberg
wiley   +1 more source

Comparing verbenone‐based repellents for ambrosia beetle management in eastern apple orchards

open access: yesAgricultural and Forest Entomology, EarlyView.
Non‐native ambrosia beetles (Xylosandrus germanus, X. crassiusculus, Anisandrus maiche) damage high‐density apple orchards across the eastern United States, motivating the search for selective, semiochemical‐based repellent strategies. Across Ohio, New York and Pennsylvania, three verbenone formulations, sachets, SPLAT® VERB and a test SPLAT ...
Kelsey N. Tobin   +5 more
wiley   +1 more source

The Influence of Microbial Fertilizers on the Rhizospheric and Epiphytic Microbiota, as Well as the Foliar Feeding Impact on Apple Leaf Mineral Contents. [PDF]

open access: yesPlants (Basel)
Kuzin AI   +10 more
europepmc   +1 more source

What political theory can learn from conceptual engineering: The case of “corruption”

open access: yesAmerican Journal of Political Science, EarlyView.
Abstract Conceptual change is commonplace in political theory. Recent scholarship argues that improving a concept, or “engineering” it, can sharpen its normative and explanatory power. This article illustrates what political theory can learn from conceptual engineering (CE) by examining the evolution of “corruption” as a case study.
Emanuela Ceva, Patrizia Pedrini
wiley   +1 more source

Predicting adolescent conduct problems: A machine learning approach using early family and child predictors

open access: yesBritish Journal of Developmental Psychology, EarlyView.
Abstract Early recognition of predictors of adolescents' conduct problems is crucial for timely intervention. The use of traditional regression models, however, is limited in the ability to identify non‐linear relationships between predictor variables. This study employed multiple machine learning algorithms to predict adolescent conduct problems from ...
Reyhaneh S. Razavi   +2 more
wiley   +1 more source

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