Thoughts on Breeding for Increased Forage Yield

Most forage crops have not experienced yield gains as impressive as those observed in annual grains crops such as maize (Zea mays L); in fact, yield improvement in lucerne appears to have stopped in the Midwestern USA (Riday and Brummer, 2002). I contend that much of this disparity can be explained by a failure of breeders to pursue long term recurrent selection programs within populations to capitalize on small, incremental improvements in yield over time. Many selection programs last only two or three cycles, resulting in a germplasm or cultivar release. Either no further selection is attempted or the new population is mixed with a larger germplasm pool in the belief that genetic variation is running low, a belief with little empirical support

Prospects for Improving Alfalfa Yield Using Genomic- and Phenomic-Based Breeding

Alfalfa (Medicago sativa L.) is a perennial outcrossing legume that is cultivated as an important forage crop in many parts of the world. Yield is the most important trait for profitable alfalfa production, yet over the last 30 years yield improvement in California has stagnated. Current breeding methods focus on recurrent phenotypic selection; however, alternatives incorporating genomic- and phenomic-based information may enhance genetic gain and help to address the lack of yield improvement. Here we attempt to increase the yield potential of alfalfa using genomic selection (GS) in combination with high throughput phenotyping (HTP). A total of 193 families from two closely related elite populations were sown in the greenhouse and transplanted into mini sward plots at two locations near Davis, CA in May 2020. The trial was managed as a high-input system under full irrigation. Families were genotyped and phenotyped for biomass yield by mechanical harvest and a combination of drone and tower-based remote sensors across 12 harvests, 3 in the establishment year (2020), 7 in the first full year of production (2021) and 2 in 2022. Alfalfa yields ranged from 13-27 tonnes DM/hectare/year with a number of half-sib families outperforming popular cultivars in the first 2 years of production. Biomass volume predicted from the drone-based cameras had a moderate prediction accuracy with an overall R2 of 0.55. Some individual harvests reached accuracies as high as 0.85. Genotyping resulted in a dataset with 6,838 SNPs. Allele frequencies were used to generate a relationship matrix for GS. Narrow-sense heritability for dry matter yield was 0.31 and the predictive ability of the GS model was 0.15

Genetic Mapping in Tetraploid Alfalfa: Results and Prospects

Among the difficulties of improving forages is their perennial nature, which necessarily requires long selection cycles to fully evaluate genotypes. Further, traits of particular importance—yield and winter hardiness—are difficult to assess on single plants, necessitating evaluation of progeny, which is both time consuming and expensive. Because of this, yield of many forages, and particularly alfalfa, has not improved substantially over the past 25 years (Riday and Brummer, 2002). Winter hardiness often has a negative correlation with autumn growth, although some evidence suggests this is not always true (Brummer et al., 2000). One way to overcome some of these limitations may be through the use of genetic markers to help select desirable genotypes. The objective of this experiment was to test the hypothesis that quantitative trait loci (QTL) for complex agronomic traits could be identified in a segregating tetraploid alfalfa population

Distribution of Legumes along Gradients of Slope and Soil Electrical Conductivity in Pastures

Legumes establish and persist on backslope landscape positions but fail on summits and toeslopes in southeastern Iowa pastures, suggesting that these pastures be managed site specifically. Visual delineation of landscape positions, however, can be difficult, and char- acterization of spatial variability through soil sampling is expensive. Creation of digital elevation models (DEM) and apparent soil electrical conductivity (ECa) mapping are inexpensive alternatives to de- scribing field conditions. Our objective was to examine the relationships of DEM-derived slope, soil ECa, and legume distribution in pastures.We examined these relationships across four 1.4-ha pastures. Each pasture was divided into 0.46-ha plots that were assigned one of three stocking treatments: continuous, rotational, and nongrazed. We found that legumes, as a percentage of pasture cover,were greatest at 15 to 20% slopes and intermediate values of soil ECa. The absolute ECa value at which legumes were maximized varied by plot within each stocking system and year ECa was measured. When ECa was standardized by pasture and year, however, a nonlinear response curve explained 23 to 42% of the variation of legume cover across the plots. Grazing reduced competition from smooth brome (Bromus inermis Leyss.) and reed canarygrass (Phalaris arundinacea L). These grasses dominated at 0 to 8% slopes and where ECa was either low or high in value. We concluded that slope and soil ECa data are useful in identifying sites where legumes are successful in pastures and showed potential for use in site-specific management of pastures

Plant species richness in relation to pasture position, management, and scale

The objective of this research was to describe how landscape position, grazing management, and scale affected overall plant species richness and species richness per functional group in temperate pastures located in the central United States. The effects and interactions of summit, backslope, and toeslope positions and continuous, rotational, and nongrazed stocking systems on species richness were examined at sample scales of 0.18 m2 and 4.5 m2. Landscape position explained 40–63% of species richness variation at 0.18 m2 compared to 3–26% at 4.5 m2 for overall, perennial, perennial grass, vegetative-spreading grass, perennial herb, and perennial N2-fixing herb (legume) functional groups. Grazing management, in contrast, explained 22–35% of species richness variation for overall, perennial, annual–biennial, perennial grass, and perennial bunchgrass functional groups at 0.18 m2 compared to 30–43% of their variation at 4.5 m2. Landscape position and stocking system mostly did not interact. Overall species richness averaged 11.7, 14.3, and 10.3 on summits, backslopes, and toeslopes, respectively, and 14.8, 12.9, and 8.7 within the continuous, rotational, and nongrazed systems, respectively, at the 4.5 m2-scale. Backslope positions supported more species than summits and toeslopes regardless of scale, with differences that appeared related to total vegetation production and aboveground competition. Continuously and rotationally stocked pastures also supported more species than nongrazed pastures, effects that were consistent across functional types and scales. Increased scale enabled detection of a greater number of species per unit area but reduced the percentage of species richness variation explained by pasture position and management

Effects of Nitrogen Fertilization on Biomass Yield and Quality in Large Fields of Established Switchgrass in Southern Iowa, USA

Switchgrass (Panicum virgatum L.) is a potential biofuel crop in the midwestern United States. The objective of this experiment was to test the effect of nitrogen application on biomass dry matter yield and fiber and mineral concentrations in large field plots in Lucas and Wayne counties in southern Iowa. Two established switchgrass fields with a previous history of limited management were evaluated from 1998 through 2002. Nitrogen was applied in the spring at rates of 0, 56, 112, and 224 kg N ha−1, and a single biomass harvest was made in autumn. Biomass production averaged across locations and N levels increased by 3.6 mg ha−1 between 1998 and 2002 to 6.5 mg ha−1. Nitrogen improved yields, with the response declining as N levels increased. The highest yield throughout the experiment was 8.5 mg ha−1 at the Lucas location in 2002. Changes in fiber and mineral concentrations did not follow any trend over years but were likely due to differences in harvest date among years. Nitrogen fertilization had no meaningful effect on the quality of the biofuel produced. This study clearly shows that nitrogen application and proper agronomic management can substantially increase the yield of established switchgrass fields over time without affecting the quality of the feedstock. As this experiment was conducted in large plots using commercial farm machinery, the results should be broadly applicable to real world situations

Quantitative Trait Locus Mapping of Winter Hardiness Metabolites in Autotetraploid Alfalfa (M. sativa)

In winter hardy alfalfa cultivars, cold acclimation occurs prior to the onset of freezing temperatures and normally is accompanied with a series of metabolic and morphological adjustments. We are studying the accumulation pattern of metabolites throughout the autumn previous to freezing and relating them to winter survival in an Fl segregating population between the cross of M. sativa subsp. sativa and subsp. falcata. Morphological components and soluble carbohydrates, protein, amino-N groups, and free fatty acids were measured in 2001 and 2002 in the field. Broad sense heritability was intermediate for shoot and root mass and height, and for metabolites, ranged from low (TNC=0.04) to high (starch=0.80). The genetic correlation between winter injury was not significant for most of the metabolites, except for soluble protein and amino-N group concentrations. The presence of allele al of MSAIC B, a cold-related gene, was positively associated with autumn plant height but negatively associated with root mass in the WISFAL-6 parent. Numerous QTL were detected for concentrations of metabolites. Our results suggest that winter injury and autumn biomass are controlled by different loci in this population

Plant Breeding Perspectives for Alfalfa (\u3cem\u3eMedicago sativa\u3c/em\u3e L.) Success in Warm Climates

Climate change can have major impacts on adaptation of forage species to agroecosystems around the world. The ability of breeders to select for traits that impart adaptability to climate resilience will be critical for the future of grasslands. Alfalfa (Medicago sativa L.) is the most important perennial forage legume in the world because of its relatively high yield and nutritional value. In Florida, nondormant cultivars were developed for improved adaptation to the state’s subtropical agroecosystem (‘Florida 66’, ‘Florida 77’, and ‘Florida 99’); however, these cultivars are not commercially available. Breeding efforts are underway to develop new nondormant alfalfa adapted to subtropical conditions. The main goal of the alfalfa breeding program at the University of Florida (UF) is to combine germplasm screening, genomics, enviromics, and phenomics to improve yield and persistence. The integration of multi-omics data can result in greater genetic gain by reducing the length of the breeding cycle and by increasing the size of breeding populations. The development of nondormant, persistent, and high yielding cultivars would be a big step towards establishing alfalfa systems in warmer climates

Establishment and persistence of legumes on sites varying in aspect, landscape position and soil type

Most Iowa pastures display only a small variety of plant species, resulting in large seasonal and annual variations in pasture productivity. This project evaluated the causes for these variations in cool-season grass pastures and considered ways to improve diversity of legume species used for grazing