The effect of manuring with undersown catch crop, and production system on the potato tuber content of microelements
The potato tuber content of microelements is lower than that of macroelements but they are equally important. With this respect, there has been noticed a favourable effect of natural and organic manuring. The objective of the study reported here was to determine the effect of manuring with an undersown catch crop, either autumn-incorporated or left on the soil surface as mulch for spring incorporation, and production system on the potato tuber content of microelements. The study involved a field experiment, which was conducted in 2009-2012. The following two factors were examined: I − manuring with undersown catch crop: control, farmyard manure, Persian clover, Persian clover + westerwolds ryegrass, westerwolds ryegrass, Persian clover − mulch, Persian clover + westerwolds ryegrass − mulch, westerwolds ryegrass − mulch; II − production system: integrated and organic. Potato tubers were sampled to determine microelement contents. The highest iron and zinc contents were recorded in the tubers of potato manured with autumn-incorporated Persian clover whereas boron content was the highest in the tubers of potato manured with Persian clover, regardless of when it had been incorporated, as well as an autumn-incorporated Persian clover + westerwolds ryegrass mixture. Organic potatoes contained more iron and boron whereas tubers grown in the integrated production system were higher in zinc, manganese and copper. Potato manuring with undersown catch crops and farmyard manure in both the production systems studied increased the potato tuber content of microelements, excluding copper and manganese.
PlumX Metrics provide insights into the ways people interact with individual pieces of research output (articles, conference proceedings, book chapters, and many more) in the online environment. Examples include, when research is mentioned in the news or is tweeted about. Collectively known as PlumX Metrics, these metrics are divided into five categories to help make sense of the huge amounts of data involved and to enable analysis by comparing like with like.
Copyright (c) 2019 Anna Płaza, Barbara Gąsiorowska, Emilia Rzążewska, Anna Cybulska, Rafał Górski
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.