Multi-experiment assessment of soil nitrous oxide emissions in sugarcane

Soil nitrous oxide (N 2O) fluxes comprise a significant part of the greenhouse gas emissions of agricultural products but are spatially and tempo-rally variable, due to complex interactions between climate, soil and management variables. This study aimed to identify the main factors that affect N2Oemissions under sugarcane, using a multi-site data-base from field experiments. Greenhouse gas fluxes, soil, climate, and management data were obtained from 13 field trials spanning the 2011–2017 period. We conducted exploratory, descriptive and inferential data analyses in experiments with varying fertiliser and stillage (vinasse) type and rate, and crop residue rates. The most relevant period of high N2O fluxes was the first 46 days after fertiliser application. The results indicate a strong positive correlation of cumulative N2O with nitrogen (N) fertiliser rate, soil fungi community (18S rRNA gene), soil ammonium(NH 4+ ) and nitrate (NO3−); and a moderate negative correlation with amoA genes of ammonia-oxidising archaea (AOA) and soil organic matter content. The regression analysis revealed that easily routinely measured climate and management-related variables explained over 50% of the variation in cumulativeN2O emissions, and that additional soil chemical and physical parameters improved the regression fit within R2 = 0.65. Cross-wavelet analysis indicated significant correlations of N2O fluxes with rainfall and air temperature up to 64 days, associated with temporal lags of 2 to 4 days in some experiments, and presenting a good environmental control over fluxes in general. The nitrogen fertiliser mean emission factors ranged from 0.03 to 1.17% of N applied, with urea and ammonium nitrate plus vinasse producing high emissions, while ammonium sulphate, ammonium nitrate without vinasse, calcium nitrate, and mitigation alternatives (nitrification inhibitors and timing of vinasse application) producing low N2O-EFs. Measurements from multiple sites spanning several crop-ping seasons were useful for exploring the influence of environmental and management-related variables on soil N 2O emissions in sugarcane production, providing support for global warming mitigation strategies, nitrogen management policies, and increased agricultural input efficiency

Dissolved organic matter cycling in eastern Mediterranean rivers experiencing multiple pressures. The case of the trans-boundary Evros River

The objective of our study was to provide a comprehensive evaluation on C, N, P cycling in medium sized Mediterranean rivers, such as the Evros, experiencing multiple pressures (intensive agriculture, industrial activities, population density). Our work aims also to contribute to the development of integrated management policies. Dissolved organic matter (DOM) cycling were investigated, during a one-year study. It was shown that the organic component of N and P was comparable to those of large Mediterranean rivers (Rhone, Po). In the lower parts of the river where all point and non-point inputs converge, the high inorganic N input favour elevated assimilation rates by phytoplankton and result in increased chl-a concentrations and autochthonous dissolved organic matter (DOM) production during the dry season with limited water flow. Moreover, carbohydrate distribution revealed that there is a constant background of soil derived mono-saccharides on top of which are superimposed impulses of poly-saccharides during blooms. During the dry season, inorganic nutrients and DOM are trapped in the lower parts of the river, whereas during high flow conditions DOM is flushed towards the sea and organic nitrogen forms can become an important TDN constituent (at least 40%) transported to shelf waters. The co-existence of terrigenous material with autochthonous and some anthropogenic is supported by the relatively low DOC:DON and DOC:DOP ratios, the positive correlation of DOC vs chl-a and the decoupling between DOC and DON. Overall, this study showed that in medium size Mediterranean rivers, such as the Evros, intensive agriculture and pollution sources in combination with water management practices and climatic variability are important factors determining C, N, P dynamics and export to coastal seas. Also, it highlights the importance of the organic fraction of N and P when considering management practices

PENGEMBANGAN MEDIA MONOPOLI DENGAN TEMA INDAHNYA KERAGAMAN DI NEGERIKU PADA MATA PELAJARAN IPS KELAS IV

Tujuan dari penelitian ini ialah untuk mengetahui kelayakan, mendapatkan nilai dari para ahli, serta respon peserta didik dari media yang peneliti coba kembangkan, yaitu Monopoli SETAPARULA (Senjata, Tari, Pakaian, Rumah, Lagu) dengan tema Indahnya Keragaman di Negeriku. Penelitian dilakukan di SDN Panunggangan 1 dengan subjek penelitian kelas IV dan 10 peserta didik untuk diuji coba terbatas. Jenis penelitian yang digunakan pada metode penelitian pengembangan (Research and Development) ialah dari Borg dan Gall yang dimodifikasi dari Sugiyono, hal tersebut terdiri dari 6 tahapan yaitu: tahap analisis masalah, tahap pengumpulan data, tahap pengembangan desain produk, tahap validasi desain produk, tahap uji perbaikan (revisi) desain produk, dan tahap uji coba produk. Instrumen yang digunakan berupa lembar angket untuk validasi ahli dan respon peserta didik. Hasil uji validasi oleh para ahli (ahli media, ahli materi, ahli bahasa, dan ahli pendidikan) terhadap kualitas media monopoli yang dikembangkan termasuk dalam kriteria layak dengan presentase penilaian sebesar 78,21%. Hasil uji coba terbatas pada peserta didik terhadap media monopoli mendapatkan kriteria sangat layak dengan presentase penilaian sebesar 100%. Berdasarkan hasil penelitian dapat disimpulkan bahwa media monopoli yang dikembangkan sangat layak digunakan dalam proses pembelajaran Ilmu Pengetahuan Sosial (IPS)

Weak proactive cognitive/motor brain control accounts for poor children's behavioral performance in speeded discrimination tasks

Background: Motor and inhibitory control rely on frontal cortex activity, which is known to reach full maturation only in late adolescence. The development of inhibitory control has been studied using event-related potentials (ERP), focusing on reactive processing (i.e. the N2 and the P3 components). Scarce information exists concerning pre-stimulus activity as that represented by the Bereinshafstpotential (BP) and by the prefrontal negativity (pN). Further, no literature exists concerning the post-stimulus components originating within the anterior insula (pN1, pP1, pP2). This study aims at associating children performance with these motor-cognitive processing in frontal brain areas. Methods: High-resolution EEG recordings were employed to measure ERPs from 18 children (12 years old) and 18 adults (28 years old) during a visuo-motor discriminative response task. Response time (RT), commission (CE) and omission errors, and RT variability were compared between groups. At brain level, two pre-stimulus (BP and pN) and seven post-stimulus (P1; pN1; N1; pP1; N2; pP2; P3) ERP components were compared between groups. Results: Children showed slower and more variable RTs and poorer inhibition (higher CEs) than adults. At electrophysiological level, children presented smaller BP and pN. After stimulus onset, children showed lower amplitude of N1, pP1, P3, and pP2 components. The P1, pP1, N2 and P3 were delayed compared to adults. Conclusions: Our results demonstrate that children are characterized by less intense task-related proactive activities in frontal cortex, which may account for subsequent poor and delayed reactive processing and, thus, for inaccurate and slow performance

A 1H-NMR-based metabolomic analysis of propolis from Santa Catarina state

16th IUFoST World Congress of Food Science and Technology: Addressing Global Food Security and Wellness through Food Science and TechnologyPropolis is a resinous biomass produced by honeybees from exudates of local flora. It has been used since ancient times in folk medicine and in recent years has been added to foods and beverages to improve health and prevent diseases. The chemical composition of propolis is highly variable and depends on the climate, season, specie of bee, and mainly the local flora visited by bees to collect resin. In order to identify groups of chemical similarity among samples (n=20 autumn, n=16 winter, n=19 spring, n=17 summer) of propolis produced in Santa Catarina (SC) state (southern Brazil - 2010), lyophilized ethanolic extracts (200 mg/ml, EtOH 70%, v/v) were solubilized in MeOD3 (700l) and analyzed by NMR spectroscopy. One-dimensional 1HNMR spectra were acquired at a magnetic field strength of 500,13/125,03 MHz using a Varian Inova 500 MHz equipment and standard conditions of data acquisition. The 1H-NMR peak list data set was processed under MetaboAnalyst 2.0. suite, computing the resonances at 0.80- 12ppm spectral window. Principal Components Analysis (PCA) score scatter plots (PC1 88.2% x PC2 2.2%) clearly demonstrated samples discriminated mainly according to the season of production. These results suggest that not only geographical origin is important for the classification of propolis, but the seasonal effects as well. Since seasons directly influence the flora available from where bees collect resin, the propolis chemical profile can be significantly modified over the seasons even from a same geographical origin.info:eu-repo/semantics/publishedVersio

A machine learning and chemometrics assisted interpretation of spectroscopic data: a NMR-based metabolomics platform for the assessment of Brazilian propolis

In this work, a metabolomics dataset from 1H nuclear magnetic resonance spectroscopy of Brazilian propolis was analyzed using machine learning algorithms, including feature selection and classification methods. Partial least square-discriminant analysis (PLS-DA), random forest (RF), and wrapper methods combining decision trees and rules with evolutionary algorithms (EA) showed to be complementary approaches, allowing to obtain relevant information as to the importance of a given set of features, mostly related to the structural fingerprint of aliphatic and aromatic compounds typically found in propolis, e.g., fatty acids and phenolic compounds. The feature selection and decision tree-based algorithms used appear to be suitable tools for building classification models for the Brazilian propolis metabolomics regarding its geographic origin, with consistency, high accuracy, and avoiding redundant information as to the metabolic signature of relevant compounds.The work is partially funded by ERDF -European Regional Development Fund through the COMPETE Programme (operational programme for competitiveness) and by National Funds through the FCT (Portuguese Foundation for Science and Technology) within projects ref. COMPETE FCOMP-01-0124-FEDER-015079 and PEstOE/ EEI/UI0752/2011. RC's work is funded by a PhD grant from the Portuguese FCT ( ref. SFRH/BD/66201/2009)

Impact of soil moisture on crop yields over Brazilian semiarid

The objective of this work was to investigate the relationship between soil water content and rainfall with rice, beans, cassava and corn yields in the semiarid region of Northeast Brazil. Precipitation and modeled soil water content were compared to yields recorded at the county levels in this region. The results were also integrated over the area of the nine States that lie within the officially recognized region of semiarid climate in Brazil. The influence of water balance components was quantified by calculating their correlation coefficient with yields of the different crop species over the municipalities of the region. It was found that rainfall had higher correlation to crop yields over most of the region, while soil water content had lower values of correlation. This result is consistent with the fact that average root depth is 40 cm, lower than the layer of soil used in the model used to estimate soil water content (100 cm). Plants respond better to the precipitation in the top layers of soil, while the water storage in the deep layer of soil might be important only in other temporal and spatial scales of the hydrological cycle.Peer ReviewedPostprint (published version

Importance of including soil moisture in drought monitoring over the Brazilian semiarid region: An evaluation using the JULES model, in situ observations, and remote sensing

Soil moisture information is essential to monitoring of the intensity of droughts, the start of the rainy season, planting dates and early warnings of yield losses. We assess spatial and temporal trends of drought over the Brazilian semiarid region by combining soil moisture observations from 360 stations, root zone soil moisture from a leading land surface model, and a vegetation health index from remote sensing. The soil moisture dataset was obtained from the network of stations maintained by the National Center of Monitoring and Early Warning of Natural Disasters (Cemaden), in Brazil. Soil water content at 10 to 35 cm depth, for the period 1979–2018, was obtained from running the JULES land surface model (the Joint UK Land Environment Simulator). The modelled soil moisture was correlated with measurements in the common period of 2015–2018, resulting in an average correlation coefficient of 0.48 across the domain. The standardized soil moisture anomaly (SMA) was calculated for the long-term modelled soil moisture and revealed strong negative values during well-known drought periods in the region, especially during El-Niño years. The performance of SMA in identifying droughts during the first 2 months of the raining and cropping season was similar to the Standardized Precipitation Index (SPI), commonly used for drought assessment: 12–14 events were identified by both indices. Finally, the temporal relationship between both SMA and SPI with the Vegetation Health Index (VHI) was assessed using the cross-wavelet transform. The results indicated lagged correlations of 1 to 1.5 months in the annual scale, suggesting that negative trends in SMA and SPI can be an early warning to yield losses during the growing season. Public policies on drought assessment should consider the combination of multiple drought indices, including soil moisture anomaly

Assessment of the environmental status in Hellenic coastal waters (Eastern Mediterranean): from the Water Framework Directive to the Marine Strategy Water Framework Directive.

A  methodology is presented to assess the environmental status sensu the Marine Strategy Water Framework Directive (MSFD) based on data obtained from the monitoring of water quality in the Hellenic coastal waters within the Water Framework Directive (WFD).   An adapted decision tree used for integrating the results of the WFD in the Basque country was applied. Modifications lie to the evaluation of the physicochemical status based on a eutrophication index developed for Eastern Mediterranean waters. Results on hydromorphological, physicochemical and biological elements are presented. The chemical status was evaluated based on measurements of heavy metals in water. The evaluation of the biological quality was based on the use of metrics developed for phytoplankton biomass, benthic macroinvertebrates and macroalgae updated to accommodate MSFD needs. Results on the integrative status of the water bodies were validated by correlating classification results with a pressure index and environmental indicators in water column and sediment. Following this decision tree the majority of stations expected to be at risk of achieving the good status were found in moderate status. Benthos was found to be the element with the closest agreement with the integrated final status having an increased weighting in the decision tree. The quality of benthos and in some  limited cases  the eutrophication index determined largely the final status. The highest disagreement with the integrative classification was produced by macroalgae. All indicators used correlated with water and sediment parameters but benthos correlated better with sediment factors while phytoplankton and eutrophication index with water column parameters

Metabolic profiling and classification of propolis samples from Southern Brazil: an NMR-based platform coupled with machine learning

The chemical composition of propolis is affected by environmental factors and harvest season, making it difficult to standardize its extracts for medicinal usage. By detecting a typical chemical profile associated with propolis from a specific production region or season, certain types of propolis may be used to obtain a specific pharmacological activity. In this study, propolis from three agroecological regions (plain, plateau, and highlands) from southern Brazil, collected over the four seasons of 2010, were investigated through a novel NMR-based metabolomics data analysis workflow. Chemometrics and machine learning algorithms (PLS-DA and RF), including methods to estimate variable importance in classification, were used in this study. The machine learning and feature selection methods permitted construction of models for propolis sample classification with high accuracy (>75%, reaching 90% in the best case), better discriminating samples regarding their collection seasons comparatively to the harvest regions. PLS-DA and RF allowed the identification of biomarkers for sample discrimination, expanding the set of discriminating features and adding relevant information for the identification of the class-determining metabolites. The NMR-based metabolomics analytical platform, coupled to bioinformatic tools, allowed characterization and classification of Brazilian propolis samples regarding the metabolite signature of important compounds, i.e., chemical fingerprint, harvest seasons, and production regions.Financial support for this investigation by National Council for Scientific and Technological Development (CNPq), Coordination for the Improvement of Higher Education Personnel (CAPES), Brazilian Biosciences National Laboratory (LNBioCNPEM/MCTI), Foundation for Support of Scientific and Technological Research in the State of Santa Catarina (FAPESC), and Portuguese Foundation for Science and Technology (FCT) is acknowledged. The research fellowship granted by CNPq to the first author is also acknowledged. The work was partially funded by a CNPq and FCT agreement through the PropMine grant