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ADAPTABILITY OF MAIZE (Zea mays L.) TO CULTIVATION ON CLOSED LANDFILL WITH REDUCED TILLAGE INPUTS

Published online by Cambridge University Press:  16 December 2013

FRANCO TESIO*
Affiliation:
ValOryza s.a.s. 55, Corso Gastaldi, 13100 Vercelli (VC), Italy
FRANCESCA FOLLIS
Affiliation:
ValOryza s.a.s. 55, Corso Gastaldi, 13100 Vercelli (VC), Italy
ANDRÉ ANDRES
Affiliation:
Embrapa Temperate Agriculture, BR 392 Km 78, 96.001-970 Pelotas, Brazil
*
‡Corresponding author. Email: franco.tesio@valoryza.it
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Summary

Cultivation of less productive soils such as closed landfills has become convenient because European subsidies covered part of the risk to obtain production. Aim of the research was to evaluate grain yields of maize hybrids belonging to different maturity classes (FAO 200, 300 and 400) (Gretzmacher, R. (1979). Die Bodenkultur 30:256--280) grown on closed landfills by the adoption of two minimum tillage methods (chisel plowing at 0.35 m plus disk harrowing at 0.20 m, or only disk harrowing at 0.20 m). Maize cultivation inserted in a winter cereal rotation had a grain production ranging from 4.6 t ha−1 (FAO 200, disk harrowing only) to 8.3 t ha−1 (FAO class 400, chisel plowing plus disk harrowing) in the two considered years (2011 and 2012). The adoption of chisel plowing coupled with disk harrowing reduced yield fluctuation between years, and furnished higher yield performance if compared with the single disk harrowing passage. The best growing hybrid cycles were those belonging to FAO class 300 with production similar to that of the longest maturity class, and with moisture content equal to the shortest maturity class.

Information

Type
Research Article
Copyright
Copyright © Cambridge University Press 2013 
Figure 0

Table 1. Analysis of variance carried out on crop density, yield and moisture content response presenting the main effects and the interactions.

Figure 1

Table 2. Crop density assessed in the two growing seasons and comparison with the seed density of each class and tillage input.

Figure 2

Table 3. Analysis of variance carried out on weed density response presenting the main effects and the interactions.

Figure 3

Figure 1. Weed density assessed before herbicide treatment. Bars represent the standard mean error (n = 12).

Figure 4

Figure 2. Maize grain yield at 13% of moisture content in 2011. Bars represent the standard mean error (n = 6). Values sharing the same letters were not significantly different with the Wallet post-hoc test (p = 0.05). **Significant differences between tillage input with p ≤ 0.01.

Figure 5

Figure 3. Maize grain yield at 13% of moisture content in 2012. Bars represent the standard mean error (n = 6). *Significant differences between tillage input with p ≤ 0.05, or **p ≤ 0.01.

Figure 6

Figure 4. Maize grain moisture at harvest in 2011. Bars represent the standard mean error (n = 6).

Figure 7

Figure 5. Maize grain moisture at harvest in 2012. Bars represent the standard mean error (n = 6). Values sharing the same letters were not significantly different with the Wallet post-hoc test (p ≤ 0.05). **Significant differences between tillage inputs with p ≤ 0.01.