One of the primary challenges of our time is to enhance global food production and security. Most assessments in agricultural systems focus on plant yield. Yet, these analyses neglect temporal yield stability, or the variability and reliability of production across years. Here we perform a meta-analysis to assess temporal yield stability of three major cropping systems: organic agriculture and conservation agriculture (no-tillage) vs. conventional agriculture, comparing 193 studies based on 2896 comparisons. Organic agriculture has, per unit yield, a significantly lower temporal stability (−15%) compared to conventional agriculture. Thus, although organic farming promotes biodiversity and is generally more environmentally friendly, future efforts should focus on reducing its yield variability. Our analysis further indicates that the use of green manure and enhanced fertilisation can reduce the yield stability gap between organic and conventional agriculture. The temporal stability (−3%) of no-tillage does not differ significantly from those of conventional tillage indicating that a transition to no-tillage does not affect yield stability.

Abstract:In evolutionary plant breeding, crop populations with a high level of genetic diversity are subjected to the forces of natural selection. In a cycle of sowing and re-sowing seed from the plant population year after year, those plants favored under prevailing growing conditions are expected to contribute more seed to the next generation than plants with lower fitness. Thus, evolving crop populations have the capability of adapting to the conditions under which they are grown. Here we review the current state of research in evolutionary plant breeding and concentrate on the ability of evolving plant populations to deal with stressful, variable, and unpredictable environments. This resilience of evolving plant populations is seen as a major advantage under the predicted threats faced by agriculture such as global climate change. We have conducted an analysis of the strengths, weaknesses, opportunities and threats of this breeding approach and suggest how its concept can be broadened and expanded. Given the current legal restrictions for realizing the potential of evolutionary plant breeding, we call for a change in legislation to allow evolving crop populations to enter agricultural practice on a larger scale.

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In the face of a changing climate, yield stability is becoming increasingly important for farmers and breeders. Long-term field experiments (LTEs) generate data sets that allow the quantification of stability for different agronomic treatments. However, there are no commonly accepted guidelines for assessing yield stability in LTEs. The large diversity of options impedes comparability of results and reduces confidence in conclusions. Here, we review and provide guidance for the most commonly encountered methodological issues when analysing yield stability in LTEs. The major points we recommend and discuss in individual sections are the following: researchers should (1) make data quality and methodological approaches in the analysis of yield stability from LTEs as transparent as possible; (2) test for and deal with outliers; (3) investigate and include, if present, potentially confounding factors in the statistical model; (4) explore the need for detrending of yield data; (5) account for temporal autocorrelation if necessary; (6) make explicit choice for the stability measures and consider the correlation between some of the measures; (7) consider and account for dependence of stability measures on the mean yield; (8) explore temporal trends of stability; and (9) report standard errors and statistical inference of stability measures where possible. For these issues, we discuss the pros and cons of the various methodological approaches and provide solutions and examples for illustration. We conclude to make ample use of linking up data sets, and to publish data, so that different approaches can be compared by other authors and, finally, consider the impacts of the choice of methods on the results when interpreting results of yield stability analyses. Consistent use of the suggested guidelines and recommendations may provide a basis for robust analyses of yield stability in LTEs and to subsequently design stable cropping systems that are better adapted to a changing climate.

The processing quality of 37 wheat varieties grown in Hungary and Austria (2011-2013) were assessed under organic and conventional low input management. The varieties studied were developed using three breeding strategies (conventional, organic and their combination: BFOA). The aim was to evaluate the effect of the field management and to assess the performance of varieties developed using different breeding methods, based on their quality traits under different managements. Furthermore, properties were identified that could characterize wheat quality and be used effectively for selection under both types of growing conditions. Strong year and genotype effects were found for all the quality traits (protein, starch, gluten, GI, Zeleny, Farinograph water absorption, development time, stability and quality number, falling number, flour yield, hardness index) of the studied varieties, while the effect of the management was significant for the physical properties (test weight, thousand-kernel weight, hardness) and gluten quality characters (gluten spread, GI, dough stability) of the grain. The standard deviation of the gluten quality traits characterized the differences between the breeding 3 strategies. It proved possible to pre select organic varieties for quality traits with high broad-sense heritability under conventional growing conditions, but direct selection in organic fields is suggested for gluten quality characters. Abbreviations:BFOA 'Breeding For Organic Agriculture': method used for selection, involving conventional selection up to F5 and organic selection

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Enhancing plant breeding to ensure global food security requires new technologies. For wheat phenotyping, only limited seeds and resources are available in early selection cycles. This forces breeders to use small plots with single or multiple row plots in order to include the maximum number of genotypes/lines for their assessment. High-throughput phenotyping through remote sensing may meet the requirements for the phenotyping of thousands of genotypes grown in small plots in early selection cycles. Therefore, the aim of this study was to compare the performance of an unmanned aerial vehicle (UAV) for assessing the grain yield of wheat genotypes in different row numbers per plot in the early selection cycles with ground-based spectral sensing. A field experiment consisting of 32 wheat genotypes with four plot designs (1, 2, 3, and 12 rows per plot) was conducted. Near infrared (NIR)-based spectral indices showed significant correlations (p < 0.01) with the grain yield at flowering to grain filling, regardless of row numbers, indicating the potential of spectral indices as indirect selection traits for the wheat grain yield. Compared with terrestrial sensing, aerial-based sensing from UAV showed consistently higher levels of association with the grain yield, indicating that an increased precision may be obtained and is expected to increase the efficiency of high-throughput phenotyping in large-scale plant breeding programs. Our results suggest that high-throughput sensing from UAV may become a convenient and efficient tool for breeders to promote a more efficient selection of improved genotypes in early selection cycles. Such new information may support the calibration of genomic information by providing additional information on other complex traits, which can be ascertained by spectral sensing.

Most of our crops are grown in monoculture with single genotypes grown over wide acreage. An alternative approach, where segregating populations are used as crops, is an exciting possibility, but outcomes of natural selection upon this type of crop are not well understood. We tracked allelic frequency changes in evolving composite cross populations of wheat grown over 10 generations under organic and conventional farming. At three generations, each population was genotyped with 19 SSR and 8 SNP markers. The latter were diagnostic for major functional genes. Gene diversity was constant at SSR markers but decreased over time for SNP markers. Population differentiation between the four locations could not be detected, suggesting that organic vs. non-organic crop management did not drive allele frequency changes. However, we did see changes for genes controlling plant height and phenology in all populations independently and consistently. We interpret these changes as the result of a consistent natural selection towards wild-type. Independent selection for alleles that are associated with plant height suggests that competition for light was central, resulting in the predominance of stronger intraspecific competitors, and highlighting a potential trade-off between individual and population performance.