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Effect of soybean crop structure on large crabgrass (Digitaria sanguinalis) growth and seed dormancy

Published online by Cambridge University Press:  02 March 2021

Fernando H. Oreja*
Affiliation:
Postgraduate Student, Faculty of Agronomy, University of Buenos Aires, Buenos Aires, Argentina
Diego Batlla
Affiliation:
Assistant Professor, Faculty of Agronomy, University of Buenos Aires, Buenos Aires, Argentina
Elba B. de la Fuente
Affiliation:
Associate Professor, Faculty of Agronomy, University of Buenos Aires, Buenos Aires, Argentina
*
Author for correspondence: Fernando H. Oreja, Department of Vegetal Production, Faculty of Agronomy, University of Buenos Aires, Buenos Aires, San Martín Avenue 4453, C1417DSE, Argentina. (Email: orejaf@agro.uba.ar)
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Abstract

Crop–weed interactions are affected by environmental alterations resulting from a crop’s presence, such as modifications in temperature, light quality and quantity, and moisture conditions that could modify weed performance. The objectives of this work were to study (1) how soybean [Glycine max (L.) Merr.] crop structure modifies the environment under the canopy and large crabgrass [Digitaria sanguinalis (L.) Scop.] plant structure, biomass, and seed production and dormancy; and (2) the relative importance of these environmental changes on the weed’s characteristics. A field experiment in a completely randomized block design with five replicates was performed to evaluate narrow and wide interrow spacing and soybean maturity groups 3 and 4. Measured variables were intercepted solar radiation (RAD); red–far red (R-FR) ratio; humidity; minimum, maximum, and alternating temperatures; and weed biomass, tillers per plant, height, and seed dormancy. Crop canopy reduced solar radiation, R-FR ratio, and daily average maximum and alternating temperatures. Soybean presence reduced the weed biomass, tillers and seeds per plant, and seed dormancy. High solar radiation intercepted by the crop during the reproductive phase was the main environmental variable related to reductions in weed biomass, tillers per plant, and fecundity. The combination of low temperature and solar radiation received by developing seeds was more related to seed dormancy than the rest of the variables. Crop management decisions focused on the fact that keeping the crop canopy alive for a longer time at the end of the season would not only reduce the weed growth but also seed dormancy.

Information

Type
Research Article
Copyright
© The Author(s), 2021. Published by Cambridge University Press on behalf of the Weed Science Society of America
Figure 0

Figure 1. Percentage of radiation intercepted by the crop (A–C) during experiments for soybean maturity group (MG3, squares; MG4, circles) and row spacing (wide spacing, closed symbols; narrow spacing, open symbols) treatments of Digitaria sanguinalis for years 1 (A), 2 (B), and 3 (C). An asterisk (*) indicates significant differences among treatments on the same date.

Figure 1

Table 1. Average maximum, minimum, average, and alternating temperatures and average humidity measured for different treatments at 15 cm above the soil surface in years 2 (2009–2010) and 3 (2010–2011). Treatments were soybean crop presence at two maturity groups (MG), MG3 and MG4, with either narrow (0.175 m) or wide (0.52 m) interrow spacing, and a treatment without soybean crop presence.a

Figure 2

Figure 2. Red–far red (R-FR) ratio under the crop canopy (A–C) during experiments for maturity group (MG3, squares; MG4, circles) and row spacing (wide spacing, closed symbols; narrow spacing, open symbols) treatments of Digitaria sanguinalis for years 1 (A), 2 (B), and 3 (C). An asterisk (*) indicates significant differences among treatments on the same date.

Figure 3

Table 2. Digitaria sanguinalis height, tillers per plant, aboveground biomass and seeds per plant percentage reduction compared with plants growing without crop for different treatments. Treatments were 2 soybean maturity groups 3 and 4 (MG3 and MG4), 2 interrow spacing (wide and narrow) and without crop. Numbers in parenthesis are standard deviation of each value. For each year, rows with the same letter in the column are not significantly different according to Tukey’s (p < 0.05).

Figure 4

Figure 3. Principal component analysis plot between environmental variables measured for treatments. Symbols ● represent the treatments. Codes: first number is year (1, 2008–2009; 2, 2009–2010; 3, 2010–2011); last number is row spacing; MG: soybean maturity group; bold letters are environmental variables (RAD, Radiation on weed; R-FR, red–far-red ratio; Avg. Tem, average temperature; Min Temp, minimum temperature; Max Temp, maximum temperature; Alt. Tem., alternating temperature; crop stages: R3, R4, R5, R6; and R7; red vectors represent explanatory variables (tillers per plant, biomass, and germination). Dashed lines indicate the different crop structure treatments: wide and narrow interrow spacing. Eigenvalue given for each axis represents the variance in the data matrix attributed to that axis.