Functional porous carbons from waste cotton fabrics for dyeing wastewater purification

A new functional porous carbons (PC-WF) is prepared by activation-pyrolysis method use waste cotton fabrics (WF) as an abundant, cheap and available precursor for removal of Brilliant Crocein (BC-GR) and Cationic Red 2GL (CR-GL) from aqueous phase. The PC-WF was characterized by BET, FTIR, SEM, and XRD techniques, the surface area, total pore volume, average pore diameter was found as 1463.5 m² g^-1, 0.783 cm³ g^-1 and 2.14 nm, respectively. The influences on BC-GR and CR-GL adsorption of various experimental factors such as initial concentration and temperature were investigated. Adsorption kinetics was found to be best represented by the pseudo-second order model. The adsorption capacity was 319.8 mg g^-1 for BC-GR and 842.5 mg g^-1 for CR-GL at 30 °C, respectively. The results indicate that for waste cotton fabrics in particular, the practical application of this process to the production of porous carbon would be possible.     

Establishment techniques affect productivity,nutritive value and atmospheric N2 fixation of two sunn hemp cultivars

Nitrogen fertilization is a common practice for sustaining forage production in forage systems in southeastern United States. Warm-season annual legumes may be an alternative forage to warm-season perennial grasses that do not require N fertilization. Sunn hemp (Crotalaria juncea L.) is a fast-growing, warm-season annual legume native to India and Pakistan. The objective of this 2-year study was to assess the herbage accumulation (HA), atmospheric N₂ fixation (ANF) and nutritive value of sunn hemp. Treatments were the factorial arrangement of two sunn hemp cultivars (“Crescent Sun” and “Blue Leaf”), three seeding rates (17, 28 and 39 kg seed/ha) and seed inoculation (inoculated or non-inoculated seeds), distributed in a randomized complete block design with four replicates. Crescent sun had greater HA (3,218 vs. 1764 kg DM/ha) and ANF (41 vs. 25 kg N/ha). Blue leaf had greater crude protein (CP) (188 vs. 176 g/kg) and in vitro digestible organic matter (IVDOM) concentrations (564 vs. 531 g/kg) than crescent sun. Non-inoculated seed had greater CP than inoculated seed, 188 and 177 g/kg, respectively, and inoculation did not affect HA. Intermediate seeding rate (28 kg/ha) decreased HA (2002 kg DM/ha), while HA from high and low seeding rates (17 and 39 kg/ha, respectively) did not differ (2,863 and 2,615 kg DM/ha respectively). Planting non-inoculated crescent sun at 17 kg/ha seeding rate is a feasible management practice to produce sunn hemp in subtropical regions; however, inoculation should always be recommended for proper establishment.     

Determination of Energy Use Efficiency of some Apple (<Emphasis Type="Italic">Malus x domestica</Emphasis>) Production in Turkey: a Case Study of Eğirdir Region

This research aims to make an analysis of energy use efficiency of apple (‘Starkrimson Delicious’ and ‘Golden Delicious’) production in E?irdir region of Turkey, during the production season of 2012. Production data this research was collected in 2013. In order to determine the energy use efficiency of apple, various surveys have been conducted in 71 apple farms, selected through Simple Random Sampling method, located in E?irdir region of Turkey. The data have been collected through face to face questionnaires and first hand observations. The energy input and output values in apple production have been calculated as 34,703.63 MJ ha^?1 and 95,034 MJ ha^?1, respectively. Energy inputs consist of diesel fuel energy by 29.04?%, chemical fertilizers energy by 24.28?%, machinery energy by 15.70?%, chemical energy by 9.84?%, human labor energy by 8.54?%, electricity energy by 5.63?%, irrigation energy by 3.97?%, farmyard manure energy by 2.88?% and lime energy by 0.12?%. Energy use efficiency, energy productivity, specific energy and net energy in apple production have been calculated as 2.74, 1.16 kg MJ^?1, 0.86 MJ kg^?1 and 60,330.36 MJ ha^?1, respectively. The total energy input consumed has been classified as direct, by 47.17?%, indirect, by 52.83?%, renewable, by 15.38?% and non-renewable, by 74.62?%.     

Environmental drivers of community diversity in a neotropical urban landscape: a multi-scale analysis

Context

Many aquatic communities are linked by the aerial dispersal of multiple, interacting species and are thus structured by processes occurring in both the aquatic and terrestrial compartments of the ecosystem.

Objectives

To evaluate the environmental factors shaping the aquatic macroinvertebrate communities associated with tank bromeliads in an urban landscape.

Methods

Thirty-two bromeliads were georeferenced to assess the spatial distribution of the aquatic meta-habitat in one city. The relative influence of the aquatic and terrestrial habitats on the structure of macroinvertebrate communities was analyzed at four spatial scales (radius = 10, 30, 50, and 70 m) using redundancy analyses.

Results

We sorted 18,352 aquatic macroinvertebrates into 29 taxa. Water volume and the amount of organic matter explained a significant part of the taxa variance, regardless of spatial scale. The remaining variance was explained by the meta-habitat size (i.e., the water volume for all of the bromeliads within a given surface area), the distance to the nearest building at small scales, and the surface area of buildings plus ground cover at larger scales. At small scales, the meta-habitat size influenced the two most frequent mosquito species in opposite ways, suggesting spatial competition and coexistence. Greater vegetation cover favored the presence of a top predator.

Conclusions

The size of the meta-habitat and urban landscape characteristics influence the structure of aquatic communities in tank bromeliads, including mosquito larval abundance. Modifications to this landscape will affect both the terrestrial and aquatic compartments of the urban ecosystem, offering prospects for mosquito management during urban planning.

     

Use of geoinformation and neurotechnology to assess and to forecast the humus content variations in the steppe soils

This paper reports the results obtained using the systemic basin approach, geoinformation, and neurotechnology for modeling and forecasting of the humus spatial inhomogeneity and content variations in the steppe and dry steppe zones (Kherson oblast, Ukraine). The general trend of such variations has been determined in the 0–40 cm layer for 42 years. The intensive use of irrigation and drainage activities in 1970–1989 resulted in a significant humus depletion by 0.36% on average (from 2.56% to 2.2%). The analysis in 4450 observation points has yielded a decrease in the variability, the rising polynomial dependence of the humus enrichment from the west to the east, and the logarithmic dependence from the south to the north. The neurotechnological modeling has made it possible to develop the artificial neural network for the spatiotemporal modeling of the humus content in the soils. The humus is predicted to be subject to the irreversible process of gradual depletion in the 0–40 layer until 2025 upon the use of the existing agrotechnologies: rainfed land by 0.01%/year and irrigated land by 0.03%/year. This result defines the territorial priorities of the regional policy and suggests the differentiated efficiency evaluation of the soil-protective unit of the farming systems.     

Identification and validation of root length QTLs for water stress resistance in hexaploid wheat (<Emphasis Type="Italic">Titicum aestivum</Emphasis> L.)

Thorough understanding of the genetic mechanisms governing drought adaptive traits can facilitate drought resistance improvement. This study was conducted to identify chromosome regions harbouring QTLs contributing for water stress resistance in wheat. A RIL mapping population derived from a cross between W7984 (Synthetic) and Opata 85 was phenotyped for root length and root dry weight under water stress and non-stress growing conditions. ANOVA showed highly significant (p ≤ 0.01) variation among the RILs for both traits. Root length and root dry weight showed positive and significant (p ≤ 0.01) phenotypic correlation. Broad sense heritability was 86% for root length under stress and 65% for root dry weight under non-stress conditions. A total of eight root length and five root dry weight QTLs were identified under both water conditions. Root length QTLs Qrln.uwa.1BL, Qrln.uwa.2DS, Qrln.uwa.5AL and Qrln.uwa.6AL combined explained 43% of phenotypic variation under non-stress condition. Opata was the source of favourable alleles for root length QTLs under non-stress condition except for Qrln.uwa.6AL. Four stress specific root length QTLs, Qrls.uwa.1AS, Qrls.uwa.3AL, Qrls.uwa.7BL.1 and Qrls.uwa.7BL.2 jointly explained 47% of phenotypic variation. Synthetic wheat contributed favourable alleles for Qrls.uwa.1AS and Qrls.uwa.3AL. Two stable root dry weight QTLs on chromosomes 4AL and 5AL were consistently found in both water conditions. Three validation populations were developed by crossing cultivars Lang, Yitpi, and Chara with Synthetic W7984 to transfer two of the QTLs identified under stress condition. The F_2.3 and F_3.4 validation lines were phenotyped under the same level of water stress as RILs to examine the effect of these QTLs. There were 13.5 and 14.5% increases in average root length due to the inheritance of Qrls.uwa.1AS and Qrls.uwa.3AL, respectively. The result indicated that closely linked SSR markers Xbarc148 (Qrls.uwa.1AS) and Xgwm391 (Qrls.uwa.3AL) can be incorporated into MAS for water stress improvement in wheat.     

Effects of cover crop growth and decomposition on the distribution of aggregate size fractions and soil microbial carbon dynamics

Although the effects of cover crops (CC) on various soil parameters have been fully investigated, less is known about the impacts at different stages in CC cultivation. The objective of this study was to quantify the influence of CC cultivation stages and residue placement on aggregates and microbial carbon (C_mic). Additionally, the influence of residue location and crop species on CO₂ emissions and leached mineralized nitrogen (N_min) during the plant degradation period was also investigated. Within an incubation experiment, four CC species were sown in soil columns, with additional columns being kept plant‐free. After plant growth, the columns were frozen (as occurs in winter under field conditions) and then incubated with the plant material either incorporated or surface‐applied. With CC, concentrations of large and medium macroaggregates were twice that of the fallow, confirming positive effects of root growth. Freezing led to a decrease in these aggregate size classes. In the subsequent incubation, the large macroaggregates decreased far more in the samples with CC than in the fallow, leading to similar aggregate size distributions. No difference in C_mic concentration was found among the CC cultivation stages. CO₂ emissions were roughly equivalent to the carbon amounts added as plant residues. Comparison of columns with incorporated or surface‐applied residues indicated no consistent pattern of aggregate distribution, CO₂ emission or C_mic and N_min concentrations. Our results suggest that positive effects of CC cultivation are only short term and that a large amount of organic material in the soil could have a greater influence than CC cultivation.     

Determination of Energy Input-Output Analysis in Plum (<Emphasis Type="Italic">Prunus domestica</Emphasis> L.) Production

The aim of this research is to compose the energy input-output analysis of plum in Nevsehir province in Turkey. This research was conducted at the plum cultivating facilities during the 2015–2016 production seasons in Nevsehir province of Central Anatolian Region in Turkey. The agricultural input energies and output energies used in plum cultivation were calculated to determine the energy input-output analysis. According to the research findings, the energy inputs in plum cultivation were calculated respectively 3920?MJ ha^?1 (44.99%) chemical fertilizers energy, 1618.91?MJ ha^?1 (18.58%) diesel fuel energy, 1125.85?MJ ha^?1 (12.92%) chemicals energy, 1069.20?MJ ha^?1 (12.27%) machinery energy, 723.24?MJ ha^?1 (8.30%) human labour energy and 255?MJ ha^?1 (2.93%) irrigation water energy. Production output plum yield were calculated as 12,112.50?MJ ha^?1. The energy output/input ratio, specific energy, energy usage efficiency and net energy calculations were calculated respectively as 1.39, 1.37?MJ kg^?1, 0.73?kg MJ^?1 and 3400.30?MJ ha^?1.