Long-term analysis from a cropping system perspective: Yield stability, environmental adaptability, and production risk of winter barley
Introduction
Yield vulnerability can be defined as the susceptibility of a crop to extreme environmental change that negatively impacts yield or the resilience of crops (Urruty et al., 2016; Reidsma et al., 2010). More specifically, yield vulnerability can be used as a measure of (1) yield stability, expressed as the annual variability in crop yield, (2) environmental adaptability, indicating how well a crop responds to improved environmental conditions, and (3) production risk, which can be described as the probability of yield losses resulting from detrimental environmental change. These parameters include the effects of several environmental conditions, such as annual weather and soil conditions or pressure from pathogens (Manns and Martin, 2018; Dijkman et al., 2017; Wiebe et al., 2015; Cook, 2001) as well as agronomic factors, such as the cropping sequence or fertilization (Nielsen and Vigil, 2018; Sieling et al., 2015; Brisson et al., 2010; Helmers et al., 2001). For example, Peltonen-Sainio et al. (2010) reported that a higher frequency of early summer droughts resulted in yield instabilities, especially in cereal-dominated cropping sequences with limited crop diversity. Other studies reported positive effects on the yield stability of cereal crops and a reduced production risk when these crops were grown with favorable cropping sequences that included greater crop diversity and organic matter inputs compared to those of cereal-dominated cropping sequences without organic matter inputs (Babulicova and Dyulgerova, 2019; Gaudin et al., 2015; Hejcman et al., 2012; Buraczyňska et al., 2011; Stanger et al., 2008; Christen, 2001; Berzesenyi et al., 2000). A recent French study focused on the impact of climate change on the vulnerability of winter barley yields (Schauberger et al., 2019). This report and others have indicated that the vulnerability of cropping systems (CS) has increased in recent decades due to the presence of environmental stress caused by climate change (Ray et al., 2015; IPCC, 2014; Rosenzweig et al., 2014; Peltonen-Sainio et al., 2010). Climate change models predict that the risk of crop losses will continue to increase due to the higher frequency of extreme weather events (Wiebe et al., 2015).
An evaluation of crop performance as a function of CS and agronomic practices is important to ensure sustainable agricultural production in the future (Dijkman et al., 2017; Ishag, 2015; Olesen et al., 2011). In particular, an analysis of crop yield stability requires data from long-term experiments (LTE) that take into consideration variable weather conditions to evaluate the effects of cropping sequences, growing seasons, and management practices on crop production over a sufficiently long period (Piepho, 1998). Several approaches are available for estimating yield stability, such as Taylor’s power law regression with the related power law residuals stability measure (Döring et al., 2015), the adjusted coefficient of variation method (Döring and Reckling, 2019), the coefficient of variation method (Knapp and van der Heijden, 2018), and the use of classic parameters like ecovalence (Wricke, 1962).
The use of mixed models and residual maximum likelihood (REML) estimation are recommended in LTE stability analysis because they can accommodate LTE-specific factors, including the autocorrelation of residuals over time, non-orthogonal designs, and appropriate variance-covariance structures (Onofri et al., 2016). In most LTEs, the variance is not constant over multiple years and compound symmetry correlation structures with variance heterogeneity between years must be considered in models to ensure statistical accuracy (Onofri et al., 2016; Littell et al., 2006).
The Shukla stability model, which is used for estimating yield stability (Shukla, 1972), and the Finlay-Wilkinson regression approach, which gives information about environmental adaptability (Finlay and Wilkinson, 1963), are both appropriate ways of using mixed models for yield vulnerability analysis. For both, the REML estimates of the variance parameters serve as measures of stability (van Eeuwijk et al., 2016; Raman et al., 2011; Piepho, 1998). A useful addition to the evaluation of stability is a risk analysis that takes into consideration both absolute yield performance and stability (Piepho, 2000). The production risk provides further information regarding treatment resilience in response to environmental limitations and can be defined as the probability that the crop yield falls a given percentage below a critical pre-determined yield level (Eskridge, 1990). As such, the calculation of risk should be based on a mixed model approach that includes REML estimations so that the trial design and all LTE characteristics can be taken into account and thus provide valid results.
To date, only a few LTEs analysis have focused on the vulnerability of winter barley with regard to CS diversity or agronomic practices. For example, a cropping sequence study was carried out in Syria by Singh and Jones (2002), and a soil cultivation study was performed in Mexico by Fuhrer and Chervet (2015). However, few studies are relevant for temperate climate conditions (e.g., St-Martin et al., 2017; Christen, 2001). In view of the current challenging agronomic conditions that are expected to persist in the future, improved knowledge regarding how winter barley yields may be maintained and improved is needed. In particular, little evidence regarding the long-term impact of CS diversity or agricultural practices is available. The aim of this study was to investigate the impact of CS diversity on the yield vulnerability of winter barley in relation to the following three properties: (a) yield stability, (b) environmental adaptability, and (c) production risk. This study was based on data from an LTE covering a period of 27 years (1993–2019), which included different cropping sequences, organic matter inputs (straw and green manure), and three nitrogen (N) fertilization treatments. The data were used to test the following hypotheses: (H 1) CS with higher crop diversity and organic matter inputs help maintain winter barley yields and decrease yield vulnerability; (H 2) in cereal CS, organic matter inputs decrease the yield vulnerability of winter barley; and (H 3) mineral N fertilization reduces the yield vulnerability of winter barley.
Section snippets
Experimental design
The LTE used in this study was established in 1982 at Justus Liebig University Giessen in the Rauischholzhausen field station, Germany (Table 1). During the early phase of the trial (1982–1992), no control plots without mineral N fertilization were included, and variable N fertilization amounts were employed in the various plots. For this reason, this trial phase of the LTE was excluded and only data from 1993 to 2019 were analyzed in this study, during which constant mineral N levels were used
Mean yield
The CS 4–6, with sugar beets or field beans in the cropping sequences, showed the highest mean yields, followed by CS 2–3 with oilseed rape or winter rye with an organic matter supply (Table 4). Yields in cereal-CS 1 without organic inputs were significantly lower than in the other CS. In all CS, the yield levels increased with a higher supply of mineral N (N 0 < N 1 < N 2). The difference between the treatments N 0 and N 1 was larger (2.52 t ha−1) than between the treatments N 1 and N 2
Discussion
It has been shown that CS with higher crop diversity that used straw and green manure and mineral N fertilizer had less yield vulnerability for winter barley. This was indicated by increased yield stability, relatively better environmental adaptability, and lower production risk compared to less diverse or cereal-dominated CS without organic matter inputs.
Winter barley yields were more stable in systems with sugar beets (CS 4) and field beans (CS 5 and CS 6). Broad-leaved crops, particularly
Conclusion
In this LTE, the yield vulnerability of winter barley was influenced by N fertilizer inputs, cropping sequence, and organic matter additions. It can be concluded that winter barley grown in CS with higher crop diversity that include organic matter inputs led to lower winter barley yield vulnerability (hypothesis H 1 accepted). In cereal-dominated CS, additional organic matter inputs also reduced the yield vulnerability of winter barley, as indicated by higher yield stability, better
Funding
The first author acknowledges support by DFG grantMA 7094/1-1. The third author was supported by the UK Biotechnology and Biological Sciences Research Council under the National Capabilities program grant (BBS/E/C/000J0300). The fourth author acknowledges support by DFG grant PI 377/20-1.
CRediT authorship contribution statement
Janna Macholdt: Conceptualization, Methodology, Formal analysis, Writing - original draft, Writing - review & editing. Merete Elisabeth Styczen: Writing - review & editing. Andy Macdonald: Writing - review & editing. Hans-Peter Piepho: Methodology, Formal analysis, Writing - review & editing. Bernd Honermeier: Data curation, Writing - review & editing.
Declarations of Competing Interest
None.
Acknowledgements
The study was supported by Justus Liebig University Giessen. The authors would like to thank the staff of the Justus Liebig University Giessen agricultural research station, especially Dr. Lothar Behle-Schalk as the station head and Sabine Phillipzik as the technical assistant for the implementation of the LTE. Further thanks go to Dr. Jens Hartung (Biostatistics Unit, University Hohenheim) and to the two anonymous reviewers for helpful comments.
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2022, European Journal of AgronomyCitation Excerpt :At all three application dates, the barley crop fertilized with 80 or 120 kg N ha−1 was able to realize more of the annual yield potential (as indicated by the average annual yield) (slope > 1) in combination with the smallest variation (higher r2 values) than the unfertilized control or the 40 kg N ha−1 treatment (Table 2). Also Macholdt et al. (2020), who analyzed the yield stability of different cropping systems with winter barley fertilized with N amounts of 0, 70 and 140 kg N ha−1, observed less stable yields and a poorer environmental adaptability in the unfertilized plots. Our experiment revealed a clear breeding progress in winter barley yields of the last decades mainly due to an increase in the number of grains m−2 rather than to heavier grains.