Speaker
Description
Introduction
We investigated whether varying soybean seeding density and cultivar can tackle within-field variability by conducting a field experiment in Southern Brazil. We tested two hypotheses: that optimal seed density is higher in low yielding environment (HP1) and that high-yielding cultivars perform better than stable ones in high yielding environment and vice-versa (HP2). Three studies have been recently published suggesting that the optimal agronomic seeding rate of soybean is higher in low yielding zones than in high ones: Corassa et al. (2018) for Brazil, and Gaspar et al. (2020) and Carciochi et al. (2019) for North America. These three recent studies on the interaction of zone x sowing density used large datasets coming from various different fields within large ecological regions, however no study — to the best of our knowledge — investigated the effect of the interaction variable rate x zone at within-field level. We further formulated and tested the following three non-mutually-exclusive hypotheses to explain why agronomic optimal seeding rate is higher in low yielding environment: higher seeding rate in low environment increase leaf area index in early stages (HP1.1), plants in low yielding environment have a lower plastic response to density (HP1.2), and lastly that plants in low yielding zones have a lower emergence rate (HP1.3).
Materials and methods
We tested the hypotheses in a two seasons factorial experiment where 3 cultivars x 4 density x 3 environments were tested in 50x50 m plots on a 124 ha field in Southern Brazil, that has been cultivated with precision agricultural techniques over the past 20 years. During the two seasons we measured yield both using a harvest monitor and destructively by analyzing yield components (pods/plant, beans/pod, bean weight), leaf area index using a linear light ceptomer, soil moisture.
Results
Our results support the hypothesis that low yield environment have a higher optimal seeding rate (HP1). Despite the bias in the measurement between destructive and harvester the relation between seeding rate and yield was similar (Figure 1). Based on yield measured using the destructive approach, a seeding rate of 320k seeds/ha instead of 180 produced an increment of 11.4 % (SE. 7.9) in low, a decrement of -3.1 % (SE. 7.1) in medium, and an increment of 1.0 % (SE. 7.3) in high. We further observed that in low environment higher seeding rate induce a stronger initial canopy growth than in medium and high zones (HP1.1). We also observed a stronger correlation between the number of pods in high and medium zones than in low ones, suggesting that the yielding environment where a plant is grown influence its plasticity (HP1.2). We did not find evidence supporting neither HP 1.3 (lower emergence in low yielding environment), nor hypothesis 2 (interaction genotype x zone).
Figure 1: Effect of increased sowing density on yield by zone, measured either destructively. The predicted values are marginalized over year and cultivar, the shaded area is the standard error of the prediction.
Discussion
Our results on low yield zones having a higher agronomic seeding rate (HP1) extends at within-field scale similar observations developed at regional scale by Carciochi et al. (2019; Corassa et al. 2019). The existence of an interaction zone x density both at regional and within-field level induces us to think that in both case low zones are water limited. However at regional scale the major driver of water limitation is the amount of precipitation, and the soil-type , whereas at field scale topography and soil texture — that are often correlated — are a major driving factor. We observed that stable cultivars outperformed the high-yielding cultivar in all zones, the lack of interaction management zone x cultivar could be due to the fact that the 2 experimental years were extremely dry.
References
Carciochi et al. 2019. “Soybean Seed Yield Response to Plant Density by Yield Environment in North America.” Agronomy Journal 111 (July): 1923–32. https://doi.org/10.2134/agronj2018.10.0635.
Corassa et al. 2018. “Optimum Soybean Seeding Rates by Yield Environment in Southern Brazil.” Agronomy Journal 110 (6): 2430–38. https://doi.org/https://doi.org/10.2134/agronj2018.04.0239.
Gaspar et al. 2020. “Defining Optimal Soybean Seeding Rates and Associated Risk Across North America.” Agronomy Journal 112 (May): 2103–14. https://doi.org/10.1002/agj2.20203.
| Keywords | soybean; seeding variable rate; cultivars; Brazil; precision agriculture |
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