Core bacteria and fungi in response to residue retention and their contribution to soil multifunctionality in maize agroecosystem.

Core microbiome has been proven to play crucial roles in soil function. However, we still lack knowledge on how core microbiome responds to crop residue retention, and whether they contribute to this process. Consequently, we examined the effect of residue retention on soil core and non-core microbial communities in maize seedling, mature stage and freezing period based on a multi-site field experiment in Sanjiang Plain, Northeast China. Totally, 247 bacterial amplicon sequence variants (ASVs) and 109 fungal ASVs were identified as core microbiota. Both core and non-core bacterial/fungal community composition were significantly influenced by residue retention across all study sites. Especially, the core fungal community shifted towards a saprotroph-dominated community. Normalized stochastic ratio pattern revealed that that deterministic process dominated both core and non-core microbial community assembly processes. Residue retention enhanced the deterministic process of core microbial community assembly, while exhibited opposite effect on non-core microbial community. This study also revealed that soil fungi were more sensitive to residue retention than bacteria, with a larger proportion of core fungi were enriched or depleted by residue retention. In addition, residue retention complicated core bacterial co-occurrence network, while simplified fungal network. Our results pointed out both no reduction in microbial diversity or collapse in microbial network structure after repeated freezing-thawing cycles. The potential function of core microbiome was evaluated through random forest analysis and structural equation model, the results indicated core microbiome contributed more to multifunctionality than non-core microbiome. Overall, this study strengthened our understanding of soil core microbiome in response to residue retention, and highlighted their importance in maintaining soil multifunctionality.

Data-driven approaches can harness crop diversity to address heterogeneous needs for breeding products.

This perspective describes the opportunities and challenges of data-driven approaches for crop diversity management (genebanks and breeding) in the context of agricultural research for sustainable development in the Global South. Data-driven approaches build on larger volumes of data and flexible analyses that link different datasets across domains and disciplines. This can lead to more information-rich management of crop diversity, which can address the complex interactions between crop diversity, production environments, and socioeconomic heterogeneity and help to deliver more suitable portfolios of crop diversity to users with highly diverse demands. We describe recent efforts that illustrate the potential of data-driven approaches for crop diversity management. A continued investment in this area should fill remaining gaps and seize opportunities, including i) supporting genebanks to play a more active role in linking with farmers using data-driven approaches; ii) designing low-cost, appropriate technologies for phenotyping; iii) generating more and better gender and socioeconomic data; iv) designing information products to facilitate decision-making; and v) building more capacity in data science. Broad, well-coordinated policies and investments are needed to avoid fragmentation of such capacities and achieve coherence between domains and disciplines so that crop diversity management systems can become more effective in delivering benefits to farmers, consumers, and other users of crop diversity.

Genomics-driven breeding for local adaptation of durum wheat is enhanced by farmers' traditional knowledge.

In the smallholder, low-input farming systems widespread in sub-Saharan Africa, farmers select and propagate crop varieties based on their traditional knowledge and experience. A data-driven integration of their knowledge into breeding pipelines may support the sustainable intensification of local farming. Here, we combine genomics with participatory research to tap into traditional knowledge in smallholder farming systems, using durum wheat (Triticum durum Desf.) in Ethiopia as a case study. We developed and genotyped a large multiparental population, called the Ethiopian NAM (EtNAM), that recombines an elite international breeding line with Ethiopian traditional varieties maintained by local farmers. A total of 1,200 EtNAM lines were evaluated for agronomic performance and farmers' appreciation in three locations in Ethiopia, finding that women and men farmers could skillfully identify the worth of wheat genotypes and their potential for local adaptation. We then trained a genomic selection (GS) model using farmer appreciation scores and found that its prediction accuracy over grain yield (GY) was higher than that of a benchmark GS model trained on GY. Finally, we used forward genetics approaches to identify marker-trait associations for agronomic traits and farmer appreciation scores. We produced genetic maps for individual EtNAM families and used them to support the characterization of genomic loci of breeding relevance with pleiotropic effects on phenology, yield, and farmer preference. Our data show that farmers' traditional knowledge can be integrated in genomics-driven breeding to support the selection of best allelic combinations for local adaptation.

The genomic and bioclimatic characterization of Ethiopian barley (Hordeum vulgare L.) unveils challenges and opportunities to adapt to a changing climate.

The climate crisis is impacting agroecosystems and threatening food security of millions of smallholder farmers. Understanding the potential for current and future climatic adaptation of local crop agrobiodiversity may guide breeding efforts and support resilience of agriculture. Here, we combine a genomic and climatic characterization of a large collection of traditional barley varieties from Ethiopia, a staple for local smallholder farmers cropping in challenging environments. We find that the genomic diversity of barley landraces can be partially traced back to geographic and environmental diversity of the landscape. We employ a machine learning approach to model Ethiopian barley adaptation to current climate and to identify areas where its existing diversity may not be well adapted in future climate scenarios. We use this information to identify optimal trajectories of assisted migration compensating to detrimental effects of climate change, finding that Ethiopian barley diversity bears opportunities for adaptation to the climate crisis. We then characterize phenology traits in the collection in two common garden experiments in Ethiopia, using genome-wide association approaches to identify genomic loci associated with timing of flowering and maturity of the spike. We combine this information with genotype-environment associations finding that loci involved in flowering time may also explain environmental adaptation. Our data show that integrated genomic, climatic, and phenotypic characterizations of agrobiodiversity may provide breeding with actionable information to improve local adaptation in smallholder farming systems.

Data-driven, participatory characterization of farmer varieties discloses teff breeding potential under current and future climates.

In smallholder farming systems, traditional farmer varieties of neglected and underutilized species (NUS) support the livelihoods of millions of growers and consumers. NUS combine cultural and agronomic value with local adaptation, and transdisciplinary methods are needed to fully evaluate their breeding potential. Here, we assembled and characterized the genetic diversity of a representative collection of 366 Ethiopian teff (Eragrostis tef) farmer varieties and breeding materials, describing their phylogenetic relations and local adaptation on the Ethiopian landscape. We phenotyped the collection for its agronomic performance, involving local teff farmers in a participatory variety evaluation. Our analyses revealed environmental patterns of teff genetic diversity and allowed us to identify 10 genetic clusters associated with climate variation and with uneven spatial distribution. A genome-wide association study was used to identify loci and candidate genes related to phenology, yield, local adaptation, and farmers' appreciation. The estimated teff genomic offset under climate change scenarios highlighted an area around lake Tana where teff cropping may be most vulnerable to climate change. Our results show that transdisciplinary approaches may efficiently propel untapped NUS farmer varieties into modern breeding to foster more resilient and sustainable cropping systems.

Small farms support the livelihoods of about two billion people worldwide. Smallholder farmers often rely on local varieties of crops and use less irrigation and fertilizer than large producers. But smallholdings can be vulnerable to weather events and climate change. Data-driven research approaches may help to identify the needs of farmers, taking into account traditional knowledge and cultural practices to enhance the sustainability of certain crops. Teff is a cereal crop that plays a critical role in the culture and diets of Ethiopian communities. It is also a super food appreciated on international markets for its nutritional value. Rural smallholder farmers in Ethiopia rely on the crop for subsistence and income and make up the bulk of the country's agricultural system. Many grow local varieties with tremendous genetic diversity. Scientists, in collaboration with farmers, could tap that diversity to produce more productive or climate-resilient types of teff, both for national and international markets. Woldeyohannes, Iohannes et al. produced the first large-scale genetic, agronomic and climatic study of traditional teff varieties. In the experiments, Woldeyohannes and Iohannes et al. sequenced the genomes of 366 Ethiopian teff varieties and evaluated their agronomic value in common gardens. The team collaborated with 35 local farmers to understand their preference of varieties and traits. They then conducted a genome-wide association study to assess the crops' productivity and their adaptations to local growing conditions and farmer preferences. Genetic changes that speed up teff maturation and flowering time could meet small farmers' needs to secure teff harvest. Woldeyohannes, Iohannes et al. also identified a region in Ethiopia, where local teff varieties may struggle to adapt to climate change. Genetic modifications may help the crop to adapt to frequent droughts that may be a common characteristic of future climates. The experiments reveal the importance of incorporating traditional knowledge from smallholder farmers into data-driven crop improvement efforts considering genetics and climate science. This multidisciplinary approach may help to improve food security and protect local genetic diversity on small farms. It may also help to ensure that agricultural advances fairly and equitably benefit small farmers.

Spontaneous grassland recovery on abandoned croplands in northern China: Different vegetation patterns in desert and typical steppe.

Passive restoration (without any intervention) has been proposed as an effective strategy for grassland restoration in abandoned croplands. However, whether the vegetation in abandoned croplands can change towards the desired state and the time needed to reach a relative stable state are context-dependent. We investigated three abandoned croplands with different recovery times (5, 15 and 20 years) and one natural grassland in each of two different types of steppe (desert steppe and typical steppe) in the agro-pastoral ecotone of northern China to assess the restoration potential of grassland on abandoned croplands. Above- and below-ground biomass as well as species biodiversity increased gradually with increasing recovery time. After 20 years of restoration there was no significant difference between abandoned cropland and natural steppe in the typical steppe site, but above- and below-ground biomass and species biodiversity were still lower in abandoned cropland in the desert steppe site. At the beginning of restoration, the communities were dominated mainly by annual species, especially in the desert steppe. As recovery time increased, the biomass and richness of perennial graminoids and forbs increased significantly and replaced annual species as the dominant species. In both desert steppe and typical steppes, species similarity between restored and natural steppe increased over time, suggesting that previously cultivated grassland recovered towards the desired state. Our results indicate that 20 years was sufficient time for the restoration of croplands in the typical steppe, but more time may be needed in the desert steppe.

Data-driven decentralized breeding increases prediction accuracy in a challenging crop production environment.

Crop breeding must embrace the broad diversity of smallholder agricultural systems to ensure food security to the hundreds of millions of people living in challenging production environments. This need can be addressed by combining genomics, farmers' knowledge, and environmental analysis into a data-driven decentralized approach (3D-breeding). We tested this idea as a proof-of-concept by comparing a durum wheat (Triticum durum Desf.) decentralized trial distributed as incomplete blocks in 1,165 farmer-managed fields across the Ethiopian highlands with a benchmark representing genomic prediction applied to conventional breeding. We found that 3D-breeding could double the prediction accuracy of the benchmark. 3D-breeding could identify genotypes with enhanced local adaptation providing superior productive performance across seasons. We propose this decentralized approach to leverage the diversity in farmer fields and complement conventional plant breeding to enhance local adaptation in challenging crop production environments.

Integrating Conventional and Participatory Crop Improvement for Smallholder Agriculture Using the Seeds for Needs Approach: A Review.

In response to the climate change, it is essential to provide smallholder farmers with improved field crop genotypes that may increase the resilience of their farming system. This requires a fast turnover of varieties in a system capable of injecting significant amounts of genetic diversity into productive landscapes. Crop improvement is a pivotal strategy to cope with and adapt to climate change. Modern breeding may rely on the genomics revolution to speed up the development of new varieties with adaptive potential. However, centralized breeding may not adequately address smallholder farmers' needs for more locally acclimatized varieties or groups of varieties. This, in turn, constrains adoption of new varieties that reduces the effectiveness of a resource-intensive breeding process, an issue that may be overcome with participatory, decentralized approaches. Whether high-tech centralized breeding or decentralized participatory approaches are better suited for smallholder farmers in the global South is hotly debated. Sidestepping any false dichotomies and ideological issues in these debates, this review provides a perspective on relevant advances in a breeding approach that combines the two approaches and uses genomics for trait mining from ex situ collections of genetic materials, participatory multilocation trials and crowdsourced citizen science. It argues that this new combination of high-tech centralized and participatory decentralized methods can provide a coherent and effective approach to breeding for climate adaptation and the present review advocates on a different way forward for the future research.

Crop variety management for climate adaptation supported by citizen science.

Crop adaptation to climate change requires accelerated crop variety introduction accompanied by recommendations to help farmers match the best variety with their field contexts. Existing approaches to generate these recommendations lack scalability and predictivity in marginal production environments. We tested if crowdsourced citizen science can address this challenge, producing empirical data across geographic space that, in aggregate, can characterize varietal climatic responses. We present the results of 12,409 farmer-managed experimental plots of common bean (Phaseolus vulgaris L.) in Nicaragua, durum wheat (Triticum durum Desf.) in Ethiopia, and bread wheat (Triticum aestivum L.) in India. Farmers collaborated as citizen scientists, each ranking the performance of three varieties randomly assigned from a larger set. We show that the approach can register known specific effects of climate variation on varietal performance. The prediction of variety performance from seasonal climatic variables was generalizable across growing seasons. We show that these analyses can improve variety recommendations in four aspects: reduction of climate bias, incorporation of seasonal climate forecasts, risk analysis, and geographic extrapolation. Variety recommendations derived from the citizen science trials led to important differences with previous recommendations.

A large nested association mapping population for breeding and quantitative trait locus mapping in Ethiopian durum wheat.

The Ethiopian plateau hosts thousands of durum wheat (Triticum turgidum subsp. durum) farmer varieties (FV) with high adaptability and breeding potential. To harness their unique allelic diversity, we produced a large nested association mapping (NAM) population intercrossing fifty Ethiopian FVs with an international elite durum wheat variety (Asassa). The Ethiopian NAM population (EtNAM) is composed of fifty interconnected bi-parental families, totalling 6280 recombinant inbred lines (RILs) that represent both a powerful quantitative trait loci (QTL) mapping tool, and a large pre-breeding panel. Here, we discuss the molecular and phenotypic diversity of the EtNAM founder lines, then we use an array featuring 13 000 single nucleotide polymorphisms (SNPs) to characterize a subset of 1200 EtNAM RILs from 12 families. Finally, we test the usefulness of the population by mapping phenology traits and plant height using a genome wide association (GWA) approach. EtNAM RILs showed high allelic variation and a genetic makeup combining genetic diversity from Ethiopian FVs with the international durum wheat allele pool. EtNAM SNP data were projected on the fully sequenced AB genome of wild emmer wheat, and were used to estimate pairwise linkage disequilibrium (LD) measures that reported an LD decay distance of 7.4 Mb on average, and balanced founder contributions across EtNAM families. GWA analyses identified 11 genomic loci individually affecting up to 3 days in flowering time and more than 1.6 cm in height. We argue that the EtNAM is a powerful tool to support the production of new durum wheat varieties targeting local and global agriculture.

Association Between Exposure to Heavy Metals and Systemic Sclerosis: the Levels of Al, Cd, Hg, and Pb in Blood and Urine of Patients.

Systemic sclerosis (SSc) is a multisystem connective tissue disease; exogenous factors-including heavy metals-may have a role in the disease pathogenesis. In this context, a study on the quantification of Al, Cd, Hg, and Pb in blood and urine of 27 SSc patients and 30 controls was carried out. Main findings were that Al was significantly depleted in blood and increased in urine of SSc patients respect to controls; and Pb was found slightly increased in blood and significantly decreased in SSc group. In addition, higher Hg levels in urine were found in SSc subjects with the higher severity of the disease. Females showed the most marked differences in the levels of blood Al, blood Pb, and urine Cd between patients and controls. Smoking, hobby, ingestion of contaminated food, job exposure may contribute to the bodily levels of Al, Hg, Pb in SSc patients. The results indicated that low, chronic, and multiple exposures to heavy metals-also through habits, diet, and environment-may influence the risk for SSc.

Erratum: Joining smallholder farmers' traditional knowledge with metric traits to select better varieties of Ethiopian wheat.

A correction to this article has been published and is linked from the HTML version of this paper. The error has been fixed in the paper.

Genome-Wide Association Study of Septoria tritici Blotch Resistance in Ethiopian Durum Wheat Landraces.

Septoria tritici blotch (STB) is a devastating fungal disease affecting durum and bread wheat cultivation worldwide. The identification, development, and employment of resistant wheat genetic material is the key to overcoming costs and limitations of fungicide treatments. The search for resistance sources in untapped genetic material may speed up the deployment of STB genetic resistance in the field. Ethiopian durum wheat landraces represent a valuable source of such diversity. In this study, 318 Ethiopian durum wheat genotypes, for the most part traditional landraces, were phenotyped for resistance to different aspects of STB infection. Phenology, yield and yield component traits were concurrently measured the collection. Here we describe the distribution of STB resistance traits in modern varieties and in landraces, and the relation existing between STB resistance and other agronomic traits. STB resistance sources were found in landraces as well as in modern varieties tested, suggesting the presence of alleles of breeding relevance. The genetic material was genotyped with more than 16 thousand genome-wide polymorphic markers to describe the linkage disequilibrium and genetic structure existing within the panel of genotypes, and a genome-wide association (GWA) study was run to allow the identification of genomic loci involved in STB resistance. High diversity and low genetic structure in the panel allowed high efficiency GWA. The GWA scan detected five major putative QTL for STB resistance, only partially overlapping those already reported in the wheat literature. We report four putative loci for Septoria resistance with no match in previous literature: two highly significant ones on Chr 3A and 5A, and two suggestive ones on Chr 4B and 5B. Markers underlying these QTL explained as much as 10% of the phenotypic variance for disease resistance. We found three cases in which putative QTL for agronomic traits overlapped marker trait association deriving from STB GWA. Our results show that the Ethiopian untapped allelic diversity bears a great value in studying the molecular basis of STB resistance and in breeding for resistance in local and international material.

Genome Wide Association Study to Identify the Genetic Base of Smallholder Farmer Preferences of Durum Wheat Traits.

Smallholder agriculture involves millions of farmers worldwide. A methodical utilization of their traditional knowledge in modern breeding efforts may help the production of locally adapted varieties better addressing their needs. In this study, a combination of participatory approaches, genomics, and quantitative genetics is used to trace the genetic basis of smallholder farmer preferences of durum wheat traits. Two smallholder communities evaluated 400 Ethiopian wheat varieties, mostly landraces, for traits of local interest in two locations in the Ethiopian highlands. For each wheat variety, farmers provided quantitative evaluations of their preference for flowering time, spike morphology, tillering capacity, and overall quality. Ten agronomic and phenology traits were simultaneously measured on the same varieties, providing the means to compare them with farmer traits. The analysis of farmer traits showed that they were partially influenced by gender and location but were repeatable and heritable, in some cases more than metric traits. The durum wheat varieties were genotyped for more than 80,000 SNP markers, and the resulting data was used in a genome wide association (GWA) study providing the molecular dissection of smallholder farmers' choice criteria. We found 124 putative quantitative trait loci (QTL) controlling farmer traits and 30 putative QTL controlling metric traits. Twenty of such QTL were jointly identified by farmer and metric traits. QTL derived from farmer traits were in some cases dependent on gender and location, but were consistent throughout. The results of the GWA study show that smallholder farmers' traditional knowledge can yield QTL eluding metric measurements of phenotypes. We discuss the potential of including farmer evaluations based on traditional knowledge in crop breeding, arguing for the utilization of this untapped resource to develop better adapted genetic materials for local agriculture.

Joining smallholder farmers' traditional knowledge with metric traits to select better varieties of Ethiopian wheat.

Smallholder farming communities face highly variable climatic conditions that threaten locally adapted, low-input agriculture. The benefits of modern crop breeding may fail to reach their fields when broadly adapted genetic materials do not address local requirements. To date, participatory methods only scratched the surface of the exploitability of farmers' traditional knowledge in breeding. In this study, 30 smallholder farmers in each of two locations in Ethiopia provided quantitative evaluations of earliness, spike morphology, tillering capacity and overall quality on 400 wheat genotypes, mostly traditional varieties, yielding altogether 192,000 data points. Metric measurements of ten agronomic traits were simultaneously collected, allowing to systematically break down farmers' preferences on quantitative phenotypes. Results showed that the relative importance of wheat traits differed by gender and location. Farmer traits were variously contributed by metric traits, and could only partially be explained by them. Eventually, farmer trait values were used to produce a ranking of the 400 wheat varieties identifying the trait combinations most desired by farmers. The study scale and methods lead to a better understanding of the quantitative basis of Ethiopian smallholder farmer preference in wheat, broadening the discussion for the future of local, sustainable breeding efforts accommodating farmers' knowledge.

What are the prospects for citizen science in agriculture? Evidence from three continents on motivation and mobile telephone use of resource-poor farmers.

As the sustainability of agricultural citizen science projects depends on volunteer farmers who contribute their time, energy and skills, understanding their motivation is important to attract and retain participants in citizen science projects. The objectives of this study were to assess 1) farmers' motivations to participate as citizen scientists and 2) farmers' mobile telephone usage. Building on motivational factors identified from previous citizen science studies, a questionnaire based methodology was developed which allowed the analysis of motivational factors and their relation to farmers' characteristics. The questionnaire was applied in three communities of farmers, in countries from different continents, participating as citizen scientists. We used statistical tests to compare motivational factors within and among the three countries. In addition, the relations between motivational factors and farmers characteristics were assessed. Lastly, Principal Component Analysis (PCA) was used to group farmers based on their motivations. Although there was an overlap between the types of motivations, for Indian farmers a collectivistic type of motivation (i.e., contribute to scientific research) was more important than egoistic and altruistic motivations. For Ethiopian and Honduran farmers an egoistic intrinsic type of motivation (i.e., interest in sharing information) was most important. While fun has appeared to be an important egoistic intrinsic factor to participate in other citizen science projects, the smallholder farmers involved in this research valued 'passing free time' the lowest. Two major groups of farmers were distinguished: one motivated by sharing information (egoistic intrinsic), helping (altruism) and contribute to scientific research (collectivistic) and one motivated by egoistic extrinsic factors (expectation, expert interaction and community interaction). Country and education level were the two most important farmers' characteristics that explain around 20% of the variation in farmers motivations. For educated farmers, contributing to scientific research was a more important motivation to participate as citizen scientists compared to less educated farmers. We conclude that motivations to participate in citizen science are different for smallholders in agriculture compared to other sectors. Citizen science does have high potential, but easy to use mechanisms are needed. Moreover, gamification may increase the egoistic intrinsic motivation of farmers.

High-density molecular characterization and association mapping in Ethiopian durum wheat landraces reveals high diversity and potential for wheat breeding.

Durum wheat (Triticum turgidum subsp. durum) is a key crop worldwide, and yet, its improvement and adaptation to emerging environmental threats is made difficult by the limited amount of allelic variation included in its elite pool. New allelic diversity may provide novel loci to international crop breeding through quantitative trait loci (QTL) mapping in unexplored material. Here, we report the extensive molecular and phenotypic characterization of hundreds of Ethiopian durum wheat landraces and several Ethiopian improved lines. We test 81 587 markers scoring 30 155 single nucleotide polymorphisms and use them to survey the diversity, structure, and genome-specific variation in the panel. We show the uniqueness of Ethiopian germplasm using a siding collection of Mediterranean durum wheat accessions. We phenotype the Ethiopian panel for ten agronomic traits in two highly diversified Ethiopian environments for two consecutive years and use this information to conduct a genome-wide association study. We identify several loci underpinning agronomic traits of interest, both confirming loci already reported and describing new promising genomic regions. These loci may be efficiently targeted with molecular markers already available to conduct marker-assisted selection in Ethiopian and international wheat. We show that Ethiopian durum wheat represents an important and mostly unexplored source of durum wheat diversity. The panel analysed in this study allows the accumulation of QTL mapping experiments, providing the initial step for a quantitative, methodical exploitation of untapped diversity in producing a better wheat.

A global perspective of the richness and evenness of traditional crop-variety diversity maintained by farming communities.

Varietal data from 27 crop species from five continents were drawn together to determine overall trends in crop varietal diversity on farm. Measurements of richness, evenness, and divergence showed that considerable crop genetic diversity continues to be maintained on farm, in the form of traditional crop varieties. Major staples had higher richness and evenness than nonstaples. Variety richness for clonal species was much higher than that of other breeding systems. A close linear relationship between traditional variety richness and evenness (both transformed), empirically derived from data spanning a wide range of crops and countries, was found both at household and community levels. Fitting a neutral "function" to traditional variety diversity relationships, comparable to a species abundance distribution of "neutral ecology," provided a benchmark to assess the standing diversity on farm. In some cases, high dominance occurred, with much of the variety richness held at low frequencies. This suggested that diversity may be maintained as an insurance to meet future environmental changes or social and economic needs. In other cases, a more even frequency distribution of varieties was found, possibly implying that farmers are selecting varieties to service a diversity of current needs and purposes. Divergence estimates, measured as the proportion of community evenness displayed among farmers, underscore the importance of a large number of small farms adopting distinctly diverse varietal strategies as a major force that maintains crop genetic diversity on farm.

Focal nodular hyperplasia of the liver in infancy: a case report.

Focal nodular hyperplasia of the liver is a benign disorder usually affecting young women. Its treatment in children is traditionally conservative. Because of its rarity in childhood, its differential diagnosis with other hepatic tumors in children and infants is challenging. We present the case of a 7-month-old infant with large focal nodular hyperplasia affecting the whole left liver lobe. Because of progressive enlargement of the lesion and compression of the portal vein, the baby underwent successful surgical treatment. Different therapeutic options and relative indications are discussed.