Breeding maize as biogas substrate in Central Europe: I. Quantitative-genetic parameters for testcross performance

Biofuels have gained importance recently and the use of maize biomass as substrate in biogas plants for production of methane has increased tremendously in Germany. The objectives of our research were to (1) estimate variance components and heritability for different traits relevant to biogas production in testcrosses (TCs) of maize, (2) study correlations among traits, and (3) discuss strategies to breed maize as a substrate for biogas fermenters. We evaluated 570 TCs of 285 diverse dent maize lines crossed with two flint single-cross testers in six environments. Data were recorded on agronomic and quality traits, including dry matter yield (DMY), methane fermentation yield (MFY), and methane yield (MY), the product of DMY and MFY, as the main target trait. Estimates of variance components showed general combining ability (GCA) to be the major source of variation. Estimates of heritability exceeded 0.67 for all traits and were even much greater in most instances. Methane yield was perfectly correlated with DMY but not with MFY, indicating that variation in MY is primarily determined by DMY. Further, DMY had a larger heritability and coefficient of genetic variation than MFY. Hence, for improving MY, selection should primarily focus on DMY rather than MFY. Further, maize breeding for biogas production may diverge from that for forage production because in the former case, quality traits seem to be of much lower importance.     

Identification of combining ability loci for five yield-related traits in maize using a set of testcrosses with introgression lines

Combining ability is essential for hybrid breeding in crops. However, the genetic basis of combining ability remains unclear and has been seldom investigated. Identifying molecular markers associated with this complex trait would help to understand its genetic basis and provide useful information for hybrid breeding in maize. In this study, we identified genetic loci of general combining ability (GCA) and specific combining ability (SCA) for five yield-related traits under three environments using a set of testcrosses with introgression lines (ILs). GCA or SCA of the five yield-related traits of the ILs was estimated by the performance of testcrosses with four testers from different heterotic groups. Genetic correlations between GCA of the traits and the corresponding traits per se were not significant or not strong, suggesting that the genetic basis between them is different. A total of 56 significant loci for GCA and 21 loci for SCA were commonly identified in at least two environments, and only 5 loci were simultaneously controlling GCA and SCA, indicating that the genetic basis of GCA and SCA is different. For all of the traits investigated, positive and significant correlations between the number of GCA loci in the ILs and the performance of the corresponding GCA of the ILs were detected, implying that pyramiding GCA loci would have positive effect on the performance of GCA. Results in this study would be useful for maize hybrid breeding.     

Assessing the impact of rumen microbial communities on methane emissions and production traits in Holstein cows in a tropical climate

The evaluation of how the gut microbiota affects both methane emissions and animal production is necessary in order to achieve methane mitigation without production losses. Toward this goal, the aim of this study was to correlate the rumen microbial communities (bacteria, archaea, and fungi) of high (HP), medium (MP), and low milk producing (LP), as well as dry (DC), Holstein dairy cows in an actual tropical production system with methane emissions and animal production traits. Overall, DC cows emitted more methane, followed by MP, HP and LP cows, although HP and LP cow emissions were similar. Using next-generation sequencing, it was found that bacteria affiliated with Christensenellaceae, Mogibacteriaceae, S24-7, Butyrivibrio, Schwartzia, and Treponema were negatively correlated with methane emissions and showed positive correlations with digestible dry matter intake (dDMI) and digestible organic matter intake (dOMI). Similar findings were observed for archaea in the genus Methanosphaera. The bacterial groups Coriobacteriaceae, RFP12, and Clostridium were negatively correlated with methane, but did not correlate with dDMI and dOMI. For anaerobic fungal communities, no significant correlations with methane or animal production traits were found. Based on these findings, it is suggested that manipulation of the abundances of these microbial taxa may be useful for modulating methane emissions without negatively affecting animal production.     

Biogas Production from Maize: Current State, Challenges, and Prospects. 1. Methane Yield Potential

Growing interest in converting biomass to renewable energies has led to a considerable expansion of maize cultivation in Germany to provide substrate for anaerobic digestion, producing methane for heat and electricity generation. For decades, maize has been bred for human and livestock nutrition as well as industrial purposes, but not for biomethanization. This review addresses the optimization potential for enhancing maize methane yield, especially open issues pertaining to biogas maize breeding objectives. A great challenge to be faced is the precise quantification of maize-specific methane yield (SMY), i.e., the methane yield per unit biomass. Methodological aspects covered in this review include the impact of the fermentation test procedure as well as of substrate conservation and pretreatment. The contribution of genotypic variation to methane hectare yield (MHY) and SMY are discussed and changes in SMY and MHY during maturation are assessed with respect to harvest timing. The review concludes with a systematic overview of research findings on the relation between SMY and chemical composition, approaches to SMY estimation, and their validation. There is still considerable controversy concerning a biogas maize ideotype; recent research, however, suggests that it differs from the forage maize ideotype, and that a high methane yield can be achieved by different breeding strategies.     

General combining ability of most yield-related traits had a genetic basis different from their corresponding traits per se in a set of maize introgression lines

Evaluation of combining ability is a crucial process in hybrid breeding, and dissection of the genetic basis of combining ability will facilitate hybrid breeding. In this study, molecular markers significantly associated with general combining ability (GCA) of seven yield-related traits and the traits per se were detected in a set of maize introgression lines (ILs) under three environments. Totally 25 and 31 significant loci for GCA and the traits per se were commonly detected under multiple environments, respectively. Correlation analysis and comparison among these significant loci revealed that the genetic basis of GCA of these yield-related traits was generally different from that of the traits per se except for the trait of ear row number. In addition, GCA of the ILs was positively and significantly correlated to the total relative effects of significant GCA loci in the ILs in general, implying that the GCA loci identified in this study would be useful in molecular breeding. Correlation analysis also showed that the GCA of yield per plant was strongly correlated to the GCA of kernel number per row, ear length and 100-kernel-weight, thus these traits were more important in genetic improvement for GCA. Results in this study would provide useful information for hybrid breeding in maize.     

Genome‐wide association analyses reveal the genetic basis of combining ability in rice

Combining ability is a measure for selecting elite parents and predicting hybrid performance in plant breeding. However, the genetic basis of combining ability remains unclear and a global view of combining ability from diverse mating designs is lacking. We developed a North Carolina II (NCII) population of 96 Oryza sativa and four male sterile lines to identify parents of greatest value for hybrid rice production. Statistical analyses indicated that general combining ability (GCA) and specific combining ability (SCA) contributed variously to different agronomic traits. In a genome‐wide association study (GWAS) of agronomic traits, GCA and SCA, we identified 34 significant associations (P < 2.39 × 10^?7). The superior alleles of GCA loci (Ghd8, GS3 and qSSR4) accumulated in parental lines with high GCA and explained 30.03% of GCA variance in grain yield, indicating that molecular breeding of high GCA parental lines is feasible. The distinct distributions of these QTLs contributed to the differentiation of parental GCA in subpopulations. GWAS of SCA identified 12 more loci that showed dominance on corresponding agronomic traits. We conclude that the accumulation of superior GCA and SCA alleles is an important contributor to heterosis and QTLs that greatly contributed to combining ability in our study would accelerate the identification of elite inbred lines and breeding of super hybrids.     

Genetic analysis of several traits in potatoes by means of a diallel cross

Genetic variation for nine traits of importance in potatoes was analysed in a half-diallel set of crosses with six parents. General combining ability (GCA) effects were responsible for differences in maturity. For the other traits (yield, number of tubers, mean tuber weight, percentages of cracked and diseased tubers, texture and blackening following cooking and specific gravity) special combining ability (SCA) was important. The correlations between the traits were calculated. The implication for breeding is that trial crossing would be necessary to identify progenies with good potential. The analyses revealed associations between traits which are potentially useful to the breeder.     

Changes in root size and distribution in relation to nitrogen accumulation during maize breeding in China

Background and aims

Modern maize breeding has increased maize yields worldwide. The changes in above-ground traits accompanying yield improvement are well-known, but less information is available as to the effect of modern plant breeding on changes in maize root traits.

Methods

Root growth, nitrogen uptake, dry matter accumulation and yield formation of six maize hybrids released from 1973 to 2000 in China were compared. Experiments were conducted under low and high nitrogen supply in a black soil in Northeast China in 2010 and 2011.

Results

While nitrogen accumulation, dry matter production and yield formation have been increased, modern maize breeding in China since 1990 has reduced root length density in the topsoil without much effect on root growth in the deeper soil. The efficiency of roots in acquiring N has increased so as to match the requirement of N accumulation for plant growth and yield formation. The responses of root growth, nitrogen and dry matter accumulation, and grain yield to low-N stress were similar in the more modern hybrids as in the older ones.

Conclusions

Modern maize breeding has constitutively changed root and shoot growth and plant productivity without producing any specific enhancement in root responsiveness to soil N availability.     

Large-Scale Evaluation of Maize Germplasm for Low-Phosphorus Tolerance

Low-phosphorus (LP) stress is a global problem for maize production and has been exacerbated by breeding activities that have reduced the genetic diversity of maize. Although LP tolerance in maize has been previously evaluated, the evaluations were generally performed with only a small number of accessions or with samples collected from a limited area. In this research, 826 maize accessions (including 580 tropical/subtropical accessions and 246 temperate accessions) were evaluated for LP tolerance under field conditions in 2011 and 2012. Plant height (PH) and leaf number were measured at three growth stages. The normalized difference vegetation index (NDVI) and fresh ear weight (FEW) were also measured. Genetic correlation analysis revealed that FEW and NDVI were strongly correlated with PH, especially at later stages. LP-tolerant and -sensitive accessions were selected based on the relative trait values of all traits using principal component analysis, and all the 14 traits of the tolerant maize accessions showed less reduction than the sensitive accessions under LP conditions. LP tolerance was strongly correlated with agronomic performance under LP stress conditions, and both criteria could be used for genetic analysis and breeding of LP tolerance. Temperate accessions showed slightly better LP tolerance than tropical/subtropical ones, although more tolerant accessions were identified from tropical/subtropical accessions, which could be contributed by their larger sample size. This large-scale evaluation provides useful information, LP-tolerant germplasm resources and evaluation protocol for genetic analysis and developing maize varieties for LP tolerance.     

Genetic correlations derived from Full-sib relationships in soybean (Glycine max Merr.)

Summary Spaced plants of a segregating soybean hybrid population in the F₆ generation were scored for fourteen quantitative traits related to yield, foliage development and growth duration. Full-sib relationships were used to estimate the genetic additive components of variation and covariation. All genetic correlations between traits, as well as phenotypic and environmental correlations, were estimated separately. A principal component analysis was further performed in all three cases. Genetic correlations identified four different groups of traits comprised of: (I) seed number per pod; (II) mean seed weight; (III) dry weight and chlorophyll content per unit leaf area; (IV) all the other characters, including seed yield and total plant weight at maturity. Among these traits, stem diameter at ground level appeared to be a good indicator of yield. This distribution remained about the same for the environmental correlations, except that growth duration traits and foliage development traits became independent of yield. The implications of these results are discussed in relation to soybean breeding for climatic adaptation.     

A Study on Genotype-by-Environment Interaction Analysis for Agronomic Traits of Maize Genotypes Across Huang-Huai-Hai Region in China

Facing the trend of increasing population, how to increase maize grain yield is a very important issue to ensure food security. In this study, 28 nationally approved maize hybrids were evaluated across 24 different climatic conditions for two consecutive years (2018–2019). The purpose of this study was to select high-yield with stable genotypes and identify important agronomic traits for maize breeding program improvement. The results of this study showed that the genotype ╳ environment interaction effects of the 12 evaluated agronomic traits was highly significant (P < 0.001). We introduced a novel multi-trait genotype-ideotype distance index (MGIDI) to select genotypes based on multiple agronomic traits. The selection process exhibited by this method is unique and easy to understand, so the MGIDI index will have more and more important applications in future multi-environment trials (METs) research. The genotypes selected by the MGIDI index were G22, G10, G12 and G1 as the high yielding and stable genotypes. The parents of these selected genotypes have the ability to play a greater role as the basic germplasm in the breeding process. A new form of genotype (G) main effects and genotype (G) -by-environment (E) interaction (GGE) technician, genotype*yield*trait (GYT) biplot, based on multiple traits for genotypes selection was also applied in this study. The GYT biplot ranked genotypes by combining grain yield with other evaluated agronomic traits, and displayed the distribution of their traits, namely strengths and weaknesses.     

Effects of ensiling, silage additives and storage period on methane formation of biogas crops

Effects of the ensiling process, storage periods of up to 1 year and several chemical and biological silage additives on biomethanation were assessed for maize, sorghum, forage rye and triticale with the aim to identify optimised conditions for silage production of crops used as feedstock in biogas plants. Ensiling, prolonged storage and biological silage additives showed positive effects on methane yield of up to 11%. These could be attributed to increases in organic acids and alcohols during ensiling. A regression model including acetic acid, butyric acid and ethanol accounts for 75-96% of the variation in methane yield. Storage periods of up to 1 year for properly ensiled crops could be possible without losses in methane production, considering the increase in methane yield and the losses of dry matter during this period. However, taking storage losses into account silage additives showed little effect on methane production.     

Analysis of Covariation of Grain Yield and Dry Matter Yield for Breeding Dual Use Hybrid Rye

Winter rye (Secale cereale L.) is becoming increasingly important as substrate for biogas production in Central Europe. Dry matter yield has evolved as a breeding goal comparably important to the traditional grain yield. We analyzed the covariation between both traits and tested other agronomic traits for their correlation to dry matter yield that could be used for prediction of biomass yield. A set of 258 experimental hybrids were tested for dry matter yield harvested at late milk stage and grain yield harvested at full ripening at three to four locations in Germany in 2011 and 2012. We observed a wide range of dry matter yield (10–24 Mg ha^?1) and grain yield (6–15 Mg ha^?1) among testcross progenies. Genetic variances were significantly (P?<?0.01) different from zero for all traits. High entry-mean heritabilities (0.92–0.94) were found for plant height measurements and moderate heritabilities for grain and dry matter yield (0.52 and 0.49, respectively). Relative efficiencies for selection of dry matter yield estimated by second (EC 51–55) and third (EC 73) measurements of plant height were 1.24 and 0.98 respectively, compared to 0.52 for grain yield. Indirect selection for high dry matter yield using late plant height measurements should be successful. Using grain yield for indirect selection was less effective. The observed broad genetic variation for biomass yield in elite hybrid rye gives good prospects for the use as a resource of renewable energy. Plant height is a good predictor of dry matter yield but should be selected together with improved lodging resistance.     

Parental Selection of Hybrid Breeding Based On Maternal and Paternal Inheritance of Traits in Rapeseed (Brassica napus L.)

Parental selection is crucial for hybrid breeding, but the methods available for such a selection are not very effective. In this study, a 6×6 incomplete diallel cross was designed using 12 rapeseed germplasms, and a total of 36 hybrids together with their parental lines were planted in 4 environments. Four yield-related traits and seed oil content (OC) were evaluated. Genetic distance (GD) was estimated with 359 simple sequence repeats (SSRs) markers. Heterosis levels, general combining ability (GCA) and specific combining ability (SCA) were evaluated. GD was found to have a significant correlation with better-parent heterosis (BPH) of thousand seed weight (TSW), SCA of seeds per silique (SS), TSW, and seed yield per plant (SY), while SCA showed a statistically significant correlation with heterosis levels of all traits at 1% significance level. Statistically significant correlations were also observed between GCA of maternal or paternal parents and heterosis levels of different traits except for SS. Interestingly, maternal (TSW, SS, and OC) and paternal (siliques per plant (SP) and SY) inheritance of traits was detected using contribution ratio of maternal and paternal GCA variance as well as correlations between GCA and heterosis levels. Phenotype and heterosis levels of all the traits except TSW of hybrids were significantly correlated with the average performance of parents. The correlations between SS and SP, SP and OC, and SY and OC were statistically significant in hybrids but not in parents. Potential applications of parental selection in hybrid breeding were discussed.     

Biogas Production from Maize: Current State, Challenges and Prospects. 2. Agronomic and Environmental Aspects

Several European countries have expanded the traditional use of anaerobic digestion, i.e. waste treatment, to energy generation through attractive incentives. In some countries, it is further promoted by additional payments to generate biogas from biomass. This review aims to summarise agronomic aspects of methane production from maize, to address resulting abiotic environmental effects and to highlight challenges and prospects. The opportunities of biogas production are manifold, including the mitigation of climate change, decreasing reliance on fossil fuels and diversification of farm income. Although the anaerobic digestion of animal manure is regarded as the most beneficial for reducing greenhouse gas (GHG) emission from manure storage, the energy output can be substantially enhanced by co-digesting manure and maize, which is the most efficient crop for substrate provision in many regions. Although first regarded as beneficial, the rush into biogas production strongly based on maize (Zea mays ssp. mays) is being questioned in view of its environmental soundness. Main areas of concern comprise the spatial concentration of biogas plant together with the high amount of digestate and resulting pollution of surface and ground water, emission of climate-relevant gases and detrimental effects of maize cultivation on soil organic matter degradation. Key challenges that have been identified to enhance the sustainability of maize-based biogas production include (1) the design of regionally adapted maize rotations, (2) an improved management of biogas residues (BR), (3) the establishment of a more comprehensive data base for evaluating soil C fluxes in maize production as well as GHG emissions at the biogas plant and during BR storage and (4) the consideration of direct and indirect land use change impact of maize-based biogas production.     

Quantitative genetic parameters of agronomic and quality traits in a global germplasm collection reveal excellent breeding perspectives for Jatropha curcas L.

Jatropha curcas L. (jatropha) is an undomesticated plant, which has received great attention in recent years for its potential in biofuel production and in greening and rehabilitation of wastelands. Yet the absence of improved cultivars and the lack of agronomic knowledge are limiting factors for successful jatropha cultivation. The objectives of the present study were to investigate the perspectives of a worldwide jatropha breeding program and specifically to (i) estimate variance components and heritabilities for agronomic and quality traits in the early phase of cultivation; (ii) assess phenotypic and genetic correlations among those traits; and (iii) discuss strategies for breeding high yielding jatropha cultivars. Data on various traits was collected from 375 jatropha genotypes, which were tested at seven locations during the first 3 years of growth. The accumulated seed yields and the seed yields per harvest year differed significantly among the testing locations. The estimates of genetic and genotype‐by‐environment interaction variances were significant and estimates of heritabilities were high for all yield parameters. The estimates of genetic correlations indicated a strong association among yield parameters. Oil yield was strongly correlated with seed yield and only weakly with oil content in seeds. The perspectives of a jatropha breeding program are excellent. Improved cultivars, definition of favorable environmental factors and refinement of agronomic management practices are needed to secure sustainable jatropha cultivation.     

Prediction of single-cross hybrid performance for grain yield and grain dry matter content in maize using AFLP markers associated with QTL

Prediction methods to identify single-cross hybrids with superior yield performance have the potential to greatly improve the efficiency of commercial maize (Zea mays L.) hybrid breeding programs. Our objectives were to (1) identify marker loci associated with quantitative trait loci for hybrid performance or specific combining ability (SCA) in maize, (2) compare hybrid performance prediction by genotypic value estimates with that based on general combining ability (GCA) estimates, and (3) investigate a newly proposed combination of the GCA model with SCA predictions from genotypic value estimates. A total of 270 hybrids was evaluated for grain yield and grain dry matter content in four Dent × Flint factorial mating experiments, their parental inbred lines were genotyped with 20 AFLP primer-enzyme combinations. Markers associated significantly with hybrid performance and SCA were identified, genotypic values and SCA effects were estimated, and four hybrid performance prediction approaches were evaluated. For grain yield, between 38 and 98 significant markers were identified for hybrid performance and between zero and five for SCA. Estimates of prediction efficiency (R ²) ranged from 0.46 to 0.86 for grain yield and from 0.59 to 0.96 for grain dry matter content. Models enhancing the GCA approach with SCA estimates resulted in the highest prediction efficiency if the SCA to GCA ratio was high. We conclude that it is advantageous for prediction of single-cross hybrids to enhance a GCA-based model with SCA effects estimated from molecular marker data, if SCA variances are of similar or larger importance as GCA variances.     

Use of tuber progeny tests for genetical studies as part of a potato (Solanum tuberosum subsp. tuberosum) breeding programme

A diallel set of crosses, including selfs and some reciprocal crosses, was made between 15 parents, chosen for their fertility, from those included in a tetraploid potato (Solanum tuberosum subsp. tuberosum) breeding programme at the Scottish Crop Research Institute. The progenies were grown in randomised complete block trials with two replicates at a high-grade seed site from 1994 to 1996 inclusive and at a ware site in 1995 and 1996. The parents were included in the ware trials. Tubers were assessed for visual preference in all trials and for fry colour at both sites in 1996. Emergence and maturity were recorded in the ware trials and the tubers were assessed for yield, dry matter, size, appearance (regularity of shape), scab, uniformity, sprouting in store and keeping quality. There were very few growth cracks and very few internal defects. No reciprocal differences were found. Inbreeding depression was marked for emergence, yield, tuber size and appearance, and visual preference. In contrast, the selfs had a lighter fry colour than the parents and F₁s. Combining-ability analysis (selfs omitted) identified fry colour, emergence, maturity, yield, dry matter and sprouting resistance as traits for which the GCA (general combining ability) variance and narrow-sense heritability were high enough for good progress from full-sib family selection. Correlations between GCAs for pairs of traits were examined, including those from previously published seedling progeny tests. For fry colour, an unfavourable correlation with low yield (r = 0.596) was compensated by a favourable one with high dry matter content (r = 0.652), whereas unfavourable ones between foliage and tuber blight resistance and sprouting susceptibility (r = 0.578 and 0.596) were identified for monitoring. Clones with high GCAs were identified for use as parents in future breeding and the extent to which GCAs could be predicted from the parents, and the offspring means from the midparent means, was determined by regression and correlation analysis. The offspring-midparent regression was highest for fry colour, followed by dry matter, emergence and sprouting. Values were lower for scab due to environmental variation; for maturity, yield and tuber size due to SCA (specific combining ability); and for visual preference due to both factors. The implications for a breeding strategy are discussed. Received: 28 November 1998 / Accepted: 19 December 1998     

Determining the Most Important Physiological and Agronomic Traits Contributing to Maize Grain Yield through Machine Learning Algorithms: A New Avenue in Intelligent Agriculture

Prediction is an attempt to accurately forecast the outcome of a specific situation while using input information obtained from a set of variables that potentially describe the situation. They can be used to project physiological and agronomic processes; regarding this fact, agronomic traits such as yield can be affected by a large number of variables. In this study, we analyzed a large number of physiological and agronomic traits by screening, clustering, and decision tree models to select the most relevant factors for the prospect of accurately increasing maize grain yield. Decision tree models (with nearly the same performance evaluation) were the most useful tools in understanding the underlying relationships in physiological and agronomic features for selecting the most important and relevant traits (sowing date-location, kernel number per ear, maximum water content, kernel weight, and season duration) corresponding to the maize grain yield. In particular, decision tree generated by C&RT algorithm was the best model for yield prediction based on physiological and agronomical traits which can be extensively employed in future breeding programs. No significant differences in the decision tree models were found when feature selection filtering on data were used, but positive feature selection effect observed in clustering models. Finally, the results showed that the proposed model techniques are useful tools for crop physiologists to search through large datasets seeking patterns for the physiological and agronomic factors, and may assist the selection of the most important traits for the individual site and field. In particular, decision tree models are method of choice with the capability of illustrating different pathways of yield increase in breeding programs, governed by their hierarchy structure of feature ranking as well as pattern discovery via various combinations of features.     

Methane production through anaerobic digestion of various energy crops grown in sustainable crop rotations

Biogas production is of major importance for the sustainable use of agrarian biomass as renewable energy source. Economic biogas production depends on high biogas yields. The project aimed at optimising anaerobic digestion of energy crops. The following aspects were investigated: suitability of different crop species and varieties, optimum time of harvesting, specific methane yield and methane yield per hectare. The experiments covered 7 maize, 2 winter wheat, 2 triticale varieties, 1 winter rye, and 2 sunflower varieties and 6 variants with permanent grassland. In the course of the vegetation period, biomass yield and biomass composition were measured. Anaerobic digestion was carried out in eudiometer batch digesters. The highest methane yields of 7500-10200 m(N)(3)ha(-1) were achieved from maize varieties with FAO numbers (value for the maturity of the maize) of 300 to 600 harvested at "wax ripeness". Methane yields of cereals ranged from 3200 to 4500 m(N)(3)ha(-1). Cereals should be harvested at "grain in the milk stage" to "grain in the dough stage". With sunflowers, methane yields between 2600 and 4550 m(N)(3)ha(-1) were achieved. There were distinct differences between the investigated sunflower varieties. Alpine grassland can yield 2700-3500 m(N)(3)CH(4)ha(-1). The methane energy value model (MEVM) was developed for the different energy crops. It estimates the specific methane yield from the nutrient composition of the energy crops. Energy crops for biogas production need to be grown in sustainable crop rotations. The paper outlines possibilities for optimising methane yield from versatile crop rotations that integrate the production of food, feed, raw materials and energy. These integrated crop rotations are highly efficient and can provide up to 320 million t COE which is 96% of the total energy demand of the road traffic of the EU-25 (the 25 Member States of the European Union).