Long-term effects of four tillage systems and weather conditions on soybean yield and agronomic characteristics in Brazil

Australian Journal of Crop Science(2015)

Cited 0|Views2
No score
Abstract
Intensive mechanized tillage systems, which are widely adopted by farmers, can cause soil disturbances and compromise the agricultural production sustainability. Despite some divergences, the no-tillage system (NT) has been shown to be more environmental and economically sustainable for farming in southern Brazil. The aim of this study was to assess the long-term effects of four soil management systems on soybean yield and agronomic characteristics, in a 14-cropping-season experiment that was established on an Oxisol in the Rio Grande do Sul state, southern region of Brazil. The experiment was carried out in randomized complete block design with three replications. The treatments consisted of four soil management systems: two conservation systems (no-tillage (NT) and reduced-tillage (RT)) and two conventional tillage (disk plowing + disking (DPD) and moldboard plowing + disking (MPD)). The parameters of grain yield, thousand-grain weight, plant height, first pod insertion height, plant stand, and soybean yield components (the number of pods per plant, the number of grains per plant, and the grain yield per plant) were evaluated at crop maturity. During the 14 successive crops, conservation systems provided grain yield and plant agronomic characteristics that were similar or significantly better than to those of conventional tillage in the majority of the cropping seasons. These findings demonstrate that NT and RT are suitable methods in environmental and economic terms, particularly NT, because it has lower production costs by reducing some mechanized operations. The main variations in soybean yield were due to changes in weather conditions that occurred during the study period (172 months), particularly with respect to the impact of water stress on plant development.
More
Translated text
Key words
soybean yield,tillage systems,agronomic characteristics,weather conditions,long-term
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined