The maize root system is crucial for plant establishment as well as water and nutrient uptake. There is substantial genetic and phenotypic variation for root architecture, which gives opportunity for selection. Root traits, however, have not been used as selection criterion mainly due to the difficulty in measuring them, as well as their quantitative mode of inheritance. Seedling root traits offer an opportunity to study multiple individuals and to enable repeated measurements per year as compared to adult root phenotyping. We developed a new software framework to capture various traits from a single image of seedling roots. This framework is based on the mathematical notion of converting images of roots into an equivalent graph. This allows automated querying of multiple traits simply as graph operations. This framework is furthermore extendable to 3D tomography image data. In order to evaluate this tool, a subset of the 384 inbred lines from the Ames panel, for which extensive genotype by sequencing data are available, was investigated. A genome wide association study was applied to this panel for two traits, Total Root Length and Total Surface Area, captured from seedling root images from WinRhizo Pro 9.0 and the current framework (called ARIA) for comparison using 135,311 single nucleotide polymorphism markers. The trait Total Root Length was found to have significant SNPs in similar regions of the genome when analyzed by both programs. This high-throughput trait capture software system allows for large phenotyping experiments and can help to establish relationships between developmental stages between seedling and adult traits in the future.
The occurrence of seven trace elements and forty three antibiotics was investigated in manure-based fertilizers from the Zhejiang province of China. These trace elements included copper, zinc, arsenic, chromium, mercury, lead and cadmium. The targeted antibiotics included four groups: sulfonamides, tetracyclines, fluoroquinolones and chloramphenicols. The median amounts of copper, zinc, arsenic, chromium, mercury, lead and cadmium in the analyzed samples were 160, 465, 7.9, 21.2, 0.3, 8.1 and 0.6 mg·kg , respectively. Seventeen antibiotics were detected. Enrofloxacin was the most frequently detected compound, with a detection rate of 39.3% and concentrations ranging from 6.7 μg·kg to 4091 μg·kg . Based on the referred loading rates in agricultural soil, 10% of the collected manure-based fertilizer samples might pose a high potential ecological risk due to the presence of antibiotics. Occurrence of seven trace elements and forty three antibiotics was investigated in manure-based fertilizers in Zhejiang province of China. The trace elements included copper, zinc, arsenic, chromium, mercury, lead and cadmium; the targeted antibiotics included four groups: sulfonamides, tetracyclines, fluoroquinolones and chloramphenicols. The medium values of copper, zinc, arsenic, chromium, mercury, lead and cadmium in the analyzed samples were 160, 465, 7.9, 21.2, 0.3, 8.1 and 0.6 mg·kg , respectively. Seventeen antibiotics were detected. Enrofloxacin was the most frequently detected compound with the detection rate of 39.3% and the concentrations ranged from 6.7 μg·kg to 4091 μg·kg . Based on the referred loading rates, 10% of the collected manure-based fertilizers might pose a high potential ecological risk after their application onto agriculture soil due to the presence of antibiotics.
Background Peach is a typical perennial fruit crop that can be categorized both as an ornamental and edible crop. Double flower is an important appearance trait, in which breeders are pursuing in high-quality ornamental peach breeding. The single/double flower character in peach is controlled by one gene, Dl, and the underlying genetic mechanism is unknown. Objective In this study, we explored the genetic basis of single/double flower trait in peach in a genome-wide association study using 1 042 687 SNPs characterized in 201 accessions. Methodology Four loci were identified to be significantly associated with the trait on chromosomes (Chr.) 1, 2 and 6. Besides, the bulked segregant analysis (BSA) was performed with two DNA bulks (single and double flower pool) from the F-1 population plants of a cross 'Juhuatao' x 'Honggengansutao'. Results We found a genomic region on Chr. 2 by the BSA, which overlapped the association peak on Chr. 2 in the GWAS-denoted as a region harbouring Dl. Finally, a candidate gene was identified by expression analysis of different plant tissues. Conclusion Our results provide insights into the genetic basis of flower shape and might facilitate marker-assisted selection breeding for ornamental peach.
High resolution melting curve analysis (HRM) has been used as an efficient, accurate and cost-effective tool to detect single nucleotide polymorphisms (SNPs) or insertions or deletions (INDELs). However, its efficiency, accuracy and applicability to discriminate microsatellite polymorphism have not been extensively assessed. The traditional protocols used for SSR genotyping include PCR amplification of the DNA fragment and the separation of the fragments on electrophoresis-based platform. However, post-PCR handling processes are laborious and costly. Furthermore, SNPs present in the sequences flanking repeat motif cannot be detected by polyacrylamide-gel-electrophoresis based methods. In the present study, we compared the discriminating power of HRM with the traditional electrophoresis-based methods and provided a panel of primers for HRM genotyping in Citrus. The results showed that sixteen SSR markers produced distinct polymorphic melting curves among the Citrus spp investigated through HRM analysis. Among those, 10 showed more genotypes by HRM analysis than capillary electrophoresis owing to the presence of SNPs in the amplicons. For the SSR markers without SNPs present in the flanking region, HRM also gave distinct melting curves which detected same genotypes as were shown in capillary electrophoresis (CE) analysis. Moreover, HRM analysis allowed the discrimination of most of the 15 citrus genotypes and the resulting genetic distance analysis clustered them into three main branches. In conclusion, it has been approved that HRM is not only an efficient and cost-effective alternative of electrophoresis-based method for SSR markers, but also a method to uncover more polymorphisms contributed by SNPs present in SSRs. It was therefore suggested that the panel of SSR markers could be used in a variety of applications in the citrus biodiversity and breeding programs using HRM analysis. Furthermore, we speculate that the HRM analysis can be employed to analyse SSR markers in a wide range of applications in all other species.
1. The development of ecological networks could enhance the ability of species to disperse across fragmented landscapes and could mitigate against the negative impacts of climate change. The development of such networks will require widespread ecological restoration at the landscape scale, which is likely to be costly. However, little information is available regarding the cost-effectiveness of restoration approaches. 2. We address this knowledge gap by examining the potential impact of landscape-scale habitat restoration on the value of multiple ecosystem services across the catchment of the River Frome in Dorset, England. This was achieved by mapping the market value of four ecosystem services (carbon storage, crops, livestock and timber) under three different restoration scenarios, estimating restoration costs, and calculating net benefits. 3. The non-market value of additional services (cultural, aesthetic and recreational value) was elicited from local stakeholders using an online survey tool. Flood risk was assessed using a scoring approach. Spatial Multi-Criteria Analysis (MCA) was conducted, incorporating both market and non-market values, to evaluate the relative benefits of restoration scenarios. These were compared with impacts of restoration on biodiversity value. 4. Multi-Criteria Analysis results consistently ranked restoration scenarios above a non-restoration comparator, reflecting the increased provision of multiple ecosystem services. Restoration scenarios also provided benefits to biodiversity, in terms of increased species richness and habitat connectivity. However, restoration costs consistently exceeded the market value of ecosystem services. 5. Synthesis and applications. Establishment of ecological networks through ecological restoration is unlikely to deliver net economic benefits in landscapes dominated by agricultural land use. This reflects the high costs of ecological restoration in such landscapes. The cost-effectiveness of ecological networks will depend on how the benefits provided to people are valued, and on how the value of non-market benefits are weighted against the costs of reduced agricultural and timber production. Future plans for ecological restoration should incorporate local stakeholder values, to ensure that benefits to people are maximised.
► We define the concepts relevant for yield gap analysis. ► We review different methods for local and global yield gap analyses. ► Global methods are coarse and local studies use different methods. ► A number of methods is compared using data sets from three regions. ► Components of a protocol for global yield gap analysis with local relevance are proposed. Yields of crops must increase substantially over the coming decades to keep pace with global food demand driven by population and income growth. Ultimately global food production capacity will be limited by the amount of land and water resources available and suitable for crop production, and by biophysical limits on crop growth. Quantifying food production capacity on every hectare of current farmland in a consistent and transparent manner is needed to inform decisions on policy, research, development and investment that aim to affect future crop yield and land use, and to inform on-ground action by local farmers through their knowledge networks. Crop production capacity can be evaluated by estimating potential yield and water-limited yield levels as benchmarks for crop production under, respectively, irrigated and rainfed conditions. The differences between these theoretical yield levels and actual farmers’ yields define the yield gaps, and precise spatially explicit knowledge about these yield gaps is essential to guide sustainable intensification of agriculture. This paper reviews methods to estimate yield gaps, with a focus on the local-to-global relevance of outcomes. Empirical methods estimate yield potential from 90 to 95th percentiles of farmers’ yields, maximum yields from experiment stations, growers’ yield contests or boundary functions; these are compared with crop simulation of potential or water-limited yields. Comparisons utilize detailed data sets from western Kenya, Nebraska (USA) and Victoria (Australia). We then review global studies, often performed by non-agricultural scientists, aimed at yield and sometimes yield gap assessment and compare several studies in terms of outcomes for regions in Nebraska, Kenya and The Netherlands. Based on our review we recommend key components for a yield gap assessment that can be applied at local to global scales. Given lack of data for some regions, the protocol recommends use of a tiered approach with preferred use of crop growth simulation models applied to relatively homogenous climate zones for which measured weather data are available. Within such zones simulations are performed for the dominant soils and cropping systems considering current spatial distribution of crops. Need for accurate agronomic and current yield data together with calibrated and validated crop models and upscaling methods is emphasized. The bottom-up application of this global protocol allows verification of estimated yield gaps with on-farm data and experiments.
In Europe, agri-environmental schemes (AES) have been introduced in response to concerns about farmland biodiversity declines. Yet, as AES have delivered variable results, a better understanding of what determines their success or failure is urgently needed. Focusing on pollinating insects, we quantitatively reviewed how environmental factors affect the effectiveness of AES. Our results suggest that the ecological contrast in floral resources created by schemes drives the response of pollinators to AES but that this response is moderated by landscape context and farmland type, with more positive responses in croplands (vs. grasslands) located in simple (vs. cleared or complex) landscapes. These findings inform us how to promote pollinators and associated pollination services in species-poor landscapes. They do not, however, present viable strategies to mitigate loss of threatened or endangered species. This indicates that the objectives and design of AES should distinguish more clearly between biodiversity conservation and delivery of ecosystem services. Keywords: Agri-environmental schemes, ecological contrast, ecosystem services, landscape context, land-use intensity, pollinators.
The effect of the composition of twelve varieties of extra virgin olive oils (EVOOs) on their differentiation based in agronomic criteria and on the antioxidant capacity was studied. Principal component analysis permitted an overview of the samples and their compositions, showing evidence of grouping and correlation between antioxidant capacity, oleuropein and ligstroside derivatives (OLD) and specific extinction at 270. Oleic and linoleic acids, 3,4-DHPEA-EA and p-HPEA-EDA (OLD), unsaturated/saturated ratio and induction time (IT) allowed the correct classification of samples according to year of harvest, ripening stage and variety. The antioxidant capacity of EVOOs was satisfactory predicted through a partial least square model based on ΔK, hydroxytyrosol, pinoresinol, oleuropein derivate and IT. Validation of the model gave a correlation R > 0.83 and an error of 7% for independent samples. This model could be a useful tool for the olive industry to highlight the nutritional quality of EVOOs and improve their marketing.
Organic farming practices have been promoted as, , reducing the environmental impacts of agriculture. This meta-analysis systematically analyses published studies that compare environmental impacts of organic and conventional farming in Europe. The results show that organic farming practices generally have positive impacts on the environment per unit of area, but not necessarily per product unit. Organic farms tend to have higher soil organic matter content and lower nutrient losses (nitrogen leaching, nitrous oxide emissions and ammonia emissions) per unit of field area. However, ammonia emissions, nitrogen leaching and nitrous oxide emissions per product unit were higher from organic systems. Organic systems had lower energy requirements, but higher land use, eutrophication potential and acidification potential per product unit. The variation within the results across different studies was wide due to differences in the systems compared and research methods used. The only impacts that were found to differ significantly between the systems were soil organic matter content, nitrogen leaching, nitrous oxide emissions per unit of field area, energy use and land use. Most of the studies that compared biodiversity in organic and conventional farming demonstrated lower environmental impacts from organic farming. The key challenges in conventional farming are to improve soil quality (by versatile crop rotations and additions of organic material), recycle nutrients and enhance and protect biodiversity. In organic farming, the main challenges are to improve the nutrient management and increase yields. In order to reduce the environmental impacts of farming in Europe, research efforts and policies should be targeted to developing farming systems that produce high yields with low negative environmental impacts drawing on techniques from both organic and conventional systems. ► On a per area basis organic farming, generally, has low environmental impacts. ► The benefits of organic farming are reduced when using product unit comparison. ► High levels of variation exist within both organic and conventional systems. ► Modelling studies tend to overestimate the benefits of organic farming. ► The relative impacts of the systems vary between different product groups.
In this work the content of seven heavy metals (Cd, Cr, Cu, Hg, Ni, Pb and Zn) and other parameters (the pH, organic matter, carbonates and granulometric fraction) in agricultural topsoil in the Ebro basin are quantified, based on 624 samples collected according to an 8 by 8 km square mesh. The average concentrations (mg/kg) obtained were: Cd 0.415 ± 0.163, Cr 20.27 ± 13.21, Cu 17.33 ± 14.97, Ni 20.50 ± 22.71, Pb 17.54 ± 10.41, Zn 17.53 ± 24.19 and Hg 35.6 ± 42.05 μg/kg. The concentration levels are relatively low in areas of high pH and low organic matter content concentration. The results of factor analysis group Cd, Cu, Hg, Pb and Zn in F1 and Cr y Ni in F2. The spatial heavy metals component maps based on geostatistical analysis, show definite association of these factors with the soil parent material. The local anomalies (found in Cu, Zn and Pb) are attributed to anthropogenic influence. Geostatistical analyses showed definite association of metals with soil parent materials.