Browsing by Subject "Grain yield"

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Einfluss von Anbauverfahren und Umweltfaktoren auf Ertrag, Qualität und agronomische Eigenschaften von Soja (Glycine max L. Merrill)
(2021) Sobko, Olena; Gruber, Sabine
With a crude protein content of approximately 40% and a crude fat content of approximately 20% in the seeds, soybean (Glycine max L. Merril) is one of the worlds most important crops with a wide range of uses. The high-quality soybean protein is an important component of animal feed in dairy and meat production. Soybean oil is often used in human nutrition, and with increasing vegetarian or vegan diets, protein-rich foods made from soybean are in high demand. In practical farming, soybean is a beneficial crop in crop rotations because it can fix atmospheric nitrogen through symbiosis with rhizobia, making the plant self-sufficient in nitrogen supply. Since soybean cultivation has no tradition in Germany, optimization of the cultivation technique is required. The present work is about the elaboration of efficient cultivation techniques for soybean in Germany. In three publications, based on three multi-year as well as multi-location and orthogonal field trials, the effects of sowing density and sowing system on yield, protein, and oil content as well as on agronomic properties of soybean are investigated in several varieties from different maturity groups. In addition, the effects of temperature, precipitation and solar radiation on yield, oil content, and protein content have been investigated to identify potential locations for specific production priorities. In the first publication (published in Agronomy Journal MDPI), the results from trials over two years and two locations in southern Germany with four soybean varieties of different maturity groups (00, 000) and growth types with either drill seeding (row spacing 14 cm) or precision seeding (row spacing 28 cm) are presented. To answer the question of which seeding method is more efficient, the following characteristics have been investigated, namely seed yield and yield structure, protein and oil content, LAI, plant height, height of the first pod set, lodging, and nodule numbers. The sowing system did not significantly affect the tested traits, and there was little difference in yield and qualities (seed yield: 3.6 t ha-1 DM, protein content: 40.9 % DM, oil content: 18.8 % DM for drill seeding; seed yield: 3.8 t ha-1 DM, protein content: 40.1 % DM, oil content: 19.1 % DM for precision seeding). These results are very helpful for soybean producers, because they do not need to invest in new sowing technique but can sow with sowing machines which are already available on the farm. The second publication (published in Plant, Soil and Environment) is about the effects of sowing density of soybean with four varieties of maturity groups 00 and 000. Four sowing densities (30, 50, 70, and 90 seeds m-2) were tested over two years and two locations in southern Germany. The lowest seed yield (3.2 t ha-1 DM was obtained at a sowing density of 30 seeds m-2 and the highest at 90 seeds m-2 (4.4 t ha-1 DM). The 00 varieties (3.6 t ha-1 DM) were higher yielding than the 000 varieties (3.4 t ha-1 DM). Sowing density did not affect seed quality characteristics. Plants were more susceptible to lodging with increasing sowing density. The lowest pod set was 4 cm higher at a sowing density of 90 seeds m-2 (13.4 cm) than at 30 seeds m-2 (9.4 cm). Increasing sowing density could reduce yield losses due to threshing because the height of the first pod set was increased at high sowing densities. Consequently, the optimum soybean seed rate would be between 50 and 70 seeds m-2 for 00 and 000 varieties at the tested locations and similar regions in Germany. In the third publication (published in Agronomy Journal MDPI), the influences of environmental factors on yield, protein and oil content, and protein and oil yield of soybean in Germany have been investigated. In the two-year field trials, 13 soybean varieties from maturity groups 00 and 000 were tested at several locations across Germany (four in 2016 and five in 2017). The 000 varieties were less sensitive to environmental factors compared to the 00 varieties. Regardless of maturity group, high solar radiation and appropriate precipitation tended to increase seed yields (r seed yield / solar radiation = 0.32 and r seed yield / solar radiation = 0.33). High temperatures at maturity reduced the productivity but provided slightly higher protein contents in 000 varieties (r protein content / CHU at maturity = 0.23). The locations that are not at risk for water stress would be suitable for soybean production if protein or oil yield is the primary concern. Overall, this study indicates that a sowing density of 50-70 seeds m-2 in combination with varieties of appropriate maturity groups could promote soybean cultivation in Germany. In dry locations, a lower sowing density is advisable in contrast to locations with more precipitation. Additional costs for the adaptation of technical equipment would not be incurred, because both drill seeding and precision seeding can be applied. By matching the direction of use (protein and/or oil production) of soybean to the climatic conditions of specific regions, soybeans for food and feed can be produced in Germany with sufficient traceability for quality and food safety. Climate warming offers opportunities to extend soybean production in Germany. This thesis provides results from which recommendations can be derived that are immediately applicable in agricultural practice.
Phenotypic and genotypic evaluation of yield components and nitrogen use efficiency of triticale (× Triticosecale Wittmack)
(2024) Neuweiler, Jan Eric; Würschum, Tobias
Modern agricultural systems require the use of mineral or organic fertilization to keep up with the growing demand for food, feed and recently also to replace fossil energy sources. One of the most important macronutrients to increase yields is nitrogen, mostly applied in its mineral form nitrate and ammonium. However, the biggest disadvantage of mineral fertilization is the good water solubility of these ions, leading to a high rate of fertilizers being leached out by strong rain falls. This results in the eutrophication of aquatic ecosystems and thus the destruction of these habitats. Further critical points are the entry of nitrates into the groundwater, evaporation of gaseous nitrogen compounds from agricultural soils and canopies as well as high energy consumption for the production of mineral nitrogen fertilizers and in result an increased emission of greenhouse gases. This has led to an increasingly restrictive legislation regulating nitrogen fertilization. The solution to resolve this contradiction, where yields should be as high as possible and fertilizer inputs as low as possible is not trivial. A big part of the solution will be the breeding of new, resource efficient cultivars producing high yields under limited nitrogen availability as well as special purpose cultivars, having a chemical grain composition and grain shape characteristics as demanded by the market. Triticale (× Triticosecale Wittmack), is a man-made small-grain cereal created by the hybridization of wheat (Triticum spp.) as female parent and rye (Secale spp.) as male parent. Triticale can be considered as a multi-purpose crop as its grain is used as animal feed and for the production of bioethanol as well as the whole plant is used as substrate for the production of biogas. Therefore, triticale can be regarded as an ideal crop to develop breeding strategies to tackle future challenges and to study the genetic basis of traits related to resource efficiency, as these results might also be transferred to other crops. In order to contribute to the solution of these challenges, the objectives of this thesis were to: (i) evaluate the genetic architecture of grain yield and grain quality related traits as well as of traits related to nitrogen use efficiency (NUE), (ii) evaluate long-term genetic trends resulting from breeding progress for traits of agronomic importance, (iii) assess the potential of index-selection to simultaneously improve negatively correlated grain yield and grain protein content, (iv) develop strategies for the identification of nitrogen efficient triticale genotypes and (v) assess the usefulness of marker-based selection techniques to improve grain yield and grain quality related traits as well as traits related to NUE in triticale by breeding. For this purpose, we used two panels of diverse genotypes representing the variation present in the European winter triticale germplasm pool. The PredBreed panel, comprising 1,218 genotypes tested in 2014 and 2015 at five locations and the SENSELGO panel, comprising 450 genotypes tested in 2018 and 2019 at four locations. Grain yield and protein content were evaluated in all field trials. In addition, grain shape characteristics were evaluated in the PredBreed panel. The SENSELGO panel was tested under four different nitrogen fertilization levels representing 40%, 70% 100% and 130% of the legal, site-specific maximum amount of nitrogen to be applied according to the latest fertilizer regulation of Germany to test their reaction on different nitrogen fertilization rates and to assess their NUE. Additionally starch content was measured. Our results show, that there is a continuous annual increase of 0.5 dt/ha for grain yield over the last decades. Moreover, we found that modern cultivars were able to make better use of the available nitrogen. This indicates, that modern cultivars have a better NUE compared to old cultivars due to their higher overall grain yield potential. Besides grain yield, quality and grain shape related traits are of great importance for the subsequent use of the harvested grain. For these traits it was found that modern cultivars tend to have bigger and more spherical grains with the potential to produce higher protein contents from the available nitrogen. To simultaneously select for negatively correlated grain yield and the most important quality related trait protein content, we evaluated different indices accounting for both traits, revealing that the sum of the standardized grain yield and protein content (IndexEW) led to the most balanced selection, whereas the index grain protein deviation (GPD) led to the selection of mostly low-yielding genotypes with a high protein content. The genetic architecture of all traits under investigation was found to be complex with many small- and medium-effect quantitative trait loci (QTL) and a high level of pleiotropy. Moreover, the analysis of the SENSELGO panel revealed a nitrogen dependent effect for some quantitative trait loci and the use of indices does not lead to a reduction in the complexity of the genetic architecture. These findings suggest that marker-assisted selection (MAS) methods only have a limited potential for the improvement of traits related to resource efficiency and grain characteristics and we therefore suggest phenotypic selection as the method of choice. By calculating the genotype-by-nitrogen interaction variance of every single genotype, it is possible to identify genotypes deviating from normal behavior. These genotypes can be selected and used as parental components to start a new breeding cycle with the aim of breeding more nitrogen-efficient cultivars. However, our results show that the overall genotype-by-nitrogen interaction variance is rather low, with highest estimates under conventional nitrogen conditions, whereas the highest yielding genotype was always different for every nitrogen fertilization level. From these results we concluded that the selection under conventional nitrogen conditions in early generations followed by trials under the nitrogen condition of the target environment is the best approach to select the highest yielding and nitrogen efficient cultivars for all environments and markets. In conclusion, the breeding of resource efficient and special purpose triticale cultivars is of utmost importance to maintain our yields on a high level and take responsibility for the environment and future generations at the same time. It is a challenging but feasible task. The genetic architecture of these traits is too complex to make successful use of MAS but phenotypic selection methods offer sufficient tools as index selection and multi-stage selection under varying nitrogen fertilization levels, to improve these traits in order to fulfill the task of using the available resources responsibly and at the same time ensuring the supply for a growing world population under more and more extreme climatic conditions.
Phenotypic and molecular analyses of grain and biomass productivity under irrigated and rainfed conditions in hybrid rye
(2014) Gottwald, Marlen; Miedaner, Thomas
Rye (Secale cereale L.) is a small grain cereal used for bread making, livestock feeding and as renewable energy source. These types of usages are leading to different breeding goals. Rye growing regions are affected by climate change and consequently by drought. Germany is touched by rainless periods in spring and early summer in the last years. Again, in spring 2012 farmers in Brandenburg and Lower Saxony were affected by drought periods. Yield losses in those regions, especially in combination with sandy soils are expected. Therefore much attention is paid for breeding of drought resistant germplasm. Briefly, our objectives of this study were to (1) estimate the biomass and biogas potential of different plant materials, their quantitative genetic parameters and biogas-related traits, (2) analyze two recombinant inbred lines and differences in their yield potential between irrigated and rainfed regime, as well as the relative efficiency for indirect selection for drought resistance in irrigated regime, and (3) investigate the phenotypic performance for ten agronomic and quality traits across multiple environments and estimated the number and effects underlying QTL. For the biomass-/ biogas analyses a wide range of plant material was analysed. Germplasm resources, full-sib families selected for grain and forage use were tested for their per se and testcross performance and experimental hybrids selected for grain use and population cultivars selected for grain and forage use were analyzed. Dry matter yields varying across environments from 106 to 177 dt/ha for per se and testcross performance, respectively. For testcross performance, germplasm resources showed similar values to forage rye. The later the maturity stage, the more dry matter yield on the whole plant level was achieved. Estimates of genotypic variances for biomass yield were significant for all rye materials, whereas the variances per se and for testcrosses were for germplasm resources exorbitant higher than for forage and grain rye. Typical cumulative methane production curves were obtained for the whole plant material from the Hohenheim biogas yield test. Methane yield showed large differences between second and third harvest date for individual plant fractions. Differences between genotypes were not substantial for methane yield although significant in some instances. At EC77/83 hybrids and forage rye reached similar methane yield of about 5000 m3/ha. A high correlation between dry matter yield and methane yield was observed (r=0.95). Concerning high cost and time consuming analysis of biogas tests, for breeders the main breeding goal should be maximum dry matter yield. Direct selection on dry matter yield should indirect improve methane yield. Two biparental populations were used for the analysis of drought tolerance. The analysis was performed in duplicate. Both populations were grown under irrigated and rainfed regimes. Striking less rainfall compared to long-term precipitation occurred between April and July, during critical phases of plant development. Grain yield reduction between irrigated and non-irrigated regime ranged from 2% to 29.6% for population A and 2% to 40% for population B, whereas differences between both regimes were significant (P<0.05) for five and four environments, respectively. Genotypic variances of grain yield were significant in all instances, whereas genotype by irrigation interaction variance between both regimes being significant only in three and four environments for population A and B, respectively. Analysis across those environments revealed significant difference for genotype by irrigation interaction variance and the three-way interaction variance in both populations. Heritability estimates were higher for the irrigated than for the rainfed regime. High interaction variance with environment and no clustering of the two regimes in a multi-dimensional analysis were found. This illustrates the different soil and whether conditions between locations and additionally every location suffered from a different drought stress. The correlation between both regimes was significant but moderate, but genotypic coefficients considerably higher (Pop-A: 0.86, Pop-B: 0.84), which could be substantiated that testcrosses differed not substantially in drought-resistance. Indirect selection for drought in the irrigated regime was predicted to be equally or more efficient than direct selection in the non-irrigated regime. Phenotypic and genotypic analysis was done across ten environments for both biparental populations for the general improvement of agronomic and quality traits in rye. Population A were genotyped with a Rye5K SNP array and for population B DArT genotyping was done with a 3K rye array. Additionally both populations were genotyped with about 150 SSRs. The genetic linkage maps comprised 1,819 and 1,265 markers for population A and B, respectively and were used for the QTL analysis for ten agronomic and quality traits. Phenotyping revealed large genetic variation for ten agronomic and quality traits. Intensive phenotyping at up to ten environments led to moderate to high heritabilities. Across environments explained genotypic variance of the individual QTL ranged from 5 to 55%. For 1000-kernel weight, test weight, falling number, and starch content, several QTL with high effects and a frequency of recovery of about 90% were identified in both population. Rye suffered from drought stress in the last decade. Focusing on general improvement of rye regarding yield and quality, as well as improving rye regarding drought-resistance is important. Future research should be done in fine mapping and validation of the detected QTLs, for exploiting their potential in marker assisted breeding.
Regionalising a soil-plant model ensemble to simulate future yields under changing climatic conditions
(2023) Bendel, Daniela Silke; Streck, Thilo
Models are supportive in depicting complex processes and in predicting their effects. Climate models are applied in many areas to assess the possible consequences of climate change. Even though Global Climate Models (GCM) have now been regionalised to the national level, their resolution of down to 5x5 km2 is still rather coarse from the perspective of a plant modeller. Plant models were developed for the field scale and work spatially explicitly. This requires to make adjustments if they are applied at coarser scales. The regionalisation of plant models is reasonable and advantageous against the background of climate change and policy advice, both gaining in importance. The higher the spatial and temporal heterogeneity of a region, the greater the computational need. The (dis)aggregation of data, frequently available in differing resolutions or quality, is often unavoidable and fraught with high uncertainties. In this dissertation, we regionalised a spatially-explicit crop model ensemble to improve yield projections for winter wheat under a changing climate. This involved upscaling a crop model ensemble consisting of three crop models to the Stuttgart region, which has an area of 3,654 km2. After a thorough parameter estimation performed with a varying number of Agricultural Response Units on a high-performance computing cluster, yield projections up to the year 2100 were computed. The representative concentration pathways of the Intergovernmental Panel on Climate Change (IPCC) RCP2.6 (large reduction of CO2 emissions) and RCP8.5 (worst case scenario) served as a framework for this effort. Under both IPCC scenarios, the model ensemble predicts stable winter wheat yields up to 2100, with a moderate decrease of 5 dt/ha for RCP2.6 and a small increase of 1 dt/ha for RCP8.5. The variability within the model ensemble is particularly high for RCP8.5. Results were obtained without accounting for a potential progress in wheat breeding.