Assessing the ecological soundness of organic and conventional agriculture by means of life cycle assessment (LCA) - a case study of leek production

Purpose – Sustainable agriculture implies the ability of agro-ecosystems to remain productive in the long-term. It is not easy to point out unambiguously whether or not current production systems meet this sustainability demand. A priori thinking would suggest that organic crops are environmentally favourable, but may ignore the effect of reduced productivity, which shifts the potential impact to other parts of the food provision system. The purpose of this paper is to assess the ecological sustainability of conventional and organic leek production by means of life cycle assessment (LCA). Design/methodology/approach – A cradle-to-farm gate LCA is applied, based on real farm data from two research centres. For a consistent comparison, two functional units (FU) were defined: 1ha and 1?kg of leek production. Findings – Assessed on an area basis, organic farming shows a more favourable environmental profile. These overall benefits are strongly reduced when the lower yields are taken into account. Related to organic farming it is therefore important that solutions are found to substantially increase the yields without increasing the environmental burden. Related to conventional farming, important potential for environmental improvements are in optimising the farm nutrient flows, reducing pesticide use and increasing its self-supporting capacity. Research limitations/implications – The research is a cradle-to-farm gate LCA, future research can be expanded to comprise all phases from cradle-to-grave to get an idea of the total sustainability of our present food consumption patterns. The research is also limited to the case of leek production. Future research can apply the methodology to other crops. Originality/value – To date, there is still lack of clear evidence of the added value of organic farming compared to conventional farming on environmental basis. Few studies have compared organic and conventional food production by means of LCA. This paper addresses these issues

Boschi di neoformazione in Italia: approfondimenti conoscitivi e orientamenti gestionali

Nelle regioni meridionali, e in Sicilia in particolare, la fisionomia della vegetazione forestale post-abbandono è quella della macchia o arbusteto che difficilmente evolve verso un bosco propriamente detto. Il processo evolutivo della vegetazione spesso non raggiunge lo stadio di bosco non perché le condizioni ambientali non lo consentano ma per due ragioni fondamentali: i disturbi, in particolare gli incendi e il pascolo, e le limitazioni nell’arrivo di propaguli, causate dalla mancanza di piante madri, dei dispersori dei semi o entrambi. Infatti, in contesti favorevoli (assenza di disturbi e arrivo dei propaguli) la vegetazione evolve sino al bosco. Le formazioni preforestali frutto dei processi di successione secondaria occupano superfici significative e sono conseguenza del fenomeno dell’abbandono dell’agricoltura iniziato alla seconda metà del secolo scorso e che ha interessato tutta l’Europa. Alcune azioni per ridurre i fattori negativi ed esaltare invece i vantaggi ambientali sono possibili per i boschi degli ambienti mediterranei. Tra queste, la trasformazione dei boschi di neoformazione in sistemi agroforestali, e più propriamente silvopastorali, utilizzando la parte aerea delle specie arboree e arbustive e mantenendo piccoli nuclei di specie spontanee utili alla fauna selvatica (a esempio, specie con frutti carnosi) senza lasciare che esse dominino la vegetazione erbacea. Ciò consentirebbe una valorizzazione delle superfici innanzitutto come pascoli, ma non si esclude l’utilizzazione come legna da ardere della componente arborea e, in certi casi, dei prodotti ottenibili (a esempio, manna, mandorle, carrube, nocciole). Altra possibilità per non disperdere i vantaggi consisterebbe nel mettere a coltura gli ex coltivi adottando tecniche alternative che non disperdano il carbonio accumulato. Su questo aspetto esistono già esperienze: ciò potrebbe inoltre ridurre la conflittualità tra gli enti gestori delle aree protette, restii a consentire un ritorno alla coltivazione, e gli agricoltori nonché i sostenitori della necessità di tutelare i paesaggi agrari

Produção e valor nutritivo da forragem de capim-elefante em dois sistemas de produção.

Esta pesquisa foi realizada com o objetivo de avaliar a produção e o valor nutritivo da forragem de capimelefante cultivado em sistemas convencional e agroecológico. No sistema convencional, o capim-elefante foi estabelecido em cultivo exclusivo, em linhas com espaçamento de 1,4 m e, no sistema agroecológico, em linhas afastadas 3 m. Nas entrelinhas, estabeleceu-se azevém no período hibernal para desenvolvimento de espécies de crescimento espontâneo no período estival. Avaliaram-se a massa, a produção e a composição botânica e estrutural da forragem e a carga animal. Amostras de simulação de pastejo foram coletadas para determinação dos teores de proteína bruta e fibra em detergente neutro e da digestibilidade in vitro da matéria seca e matéria orgânica. O delineamento experimental foi o inteiramente casualizado com dois tratamentos (sistemas convencional e agroecológico) e duas repetições (piquetes). Valores mais elevados para massa de forragem, produção de forragem, taxa de acúmulo diário e carga animal foram observados no sistema convencional. A relação folha:colmo foi similar entre os sistemas. Valor mais elevado de proteína bruta foi observado no sistema agroecológico. O capim-elefante sob manejo convencional apresenta maior produção de forragem, com menores teores de proteína bruta. O sistema agroecológico apresenta melhor distribuição da produção de forragem no decorrer do ano

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment