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AbstractBACKGROUND: Inappropriate utilisation of biosolids may adversely impact agrosystem productivity. Here, we address the response of wheat (Triticum durum) to different doses (0, 40, 100, 200 and 300 t ha−1) of either municipal solid waste (MSW) compost or sewage sludge in a greenhouse pot experiment. Plant growth, heavy metal uptake, and antioxidant activity were considered.RESULTS: Biomass production of treated plants was significantly enhanced at 40 t ha−1 and 100 t ha−1 of MSW compost (+48% and +78% relative to the control, respectively). At the same doses of sewage sludge, the increase was only 18%. Higher doses of both biosolids restricted significantly the plant growth, in concomitance with the significant accumulation of heavy metals (Ni2+, Pb2+, Cu2+ and Zn2+), especially in leaves. Leaf activities of antioxidant enzymes (ascorbate peroxidase, glutathione reductase, catalase and superoxide dismutase) were unchanged at 40 t ha−1 MSW compost or sewage sludge, but were significantly stimulated at higher doses (200–300 t ha−1), together with higher leaf concentration of reduced glutathione.CONCLUSION: This preliminary study suggests that a MSW supply at moderate doses (100 t ha−1) could be highly beneficial for wheat productivity. Copyright © 2010 Society of Chemical Industry

Life Cycle Assessment (the systematic analysis of the environmental impact of products during their entire life cycle), Carbon Footprint and Water Footprint assessments play an important role in decision-making processes. These assessments can help guide land management decisions and will likely play a larger role in the future, especially in natural areas with high biodiversity. Agriculture is a substantial consumer of fresh water, so it is important to identify causes and possible solutions to optimize agricultural water use. Water footprint assessments consider water consumption from several points of view and aid in reaching Sustainable Development Goals. Olive trees are a widespread agricultural crop growing in the Mediterranean Basin and are particularly important in the Umbria region in Italy. This paper estimates the water footprint impact related to the production of 1 kg of olives in a rainfed olive orchard managed using low environmental impact techniques. Eleven years of data collection (meteorological data, olives yield data, processes data) are analyzed for typical rural conditions. The results show that local management techniques have lower water requirements than standard international usages. These results can be used to improve and to further explore agricultural water use.

This study investigated the metabolizable energy (ME) intake, net energy of production (NEp), heat production (HP), efficiencies of ME use for energy, lipid and protein retention as well as the performance of broiler chickens fed diets based on cassava chips or pellets with or without supplementation with an enzyme product containing xylanase, amylase, protease and phytase. The two products, cassava chips and pellets, were analysed for nutrient composition prior to feed formulation. The cassava chips and pellets contained 2.2% and 2.1% crude protein; 1.2% and 1.5% crude fat; and 75.1% and 67.8% starch, respectively. Lysine and methionine were 0.077%, 0.075%, and 0.017%, 0.020% protein material, respectively, while calculated ME was 12.6 and 11.7 MJ/kg, respectively. Feed intake to day 21 was lower (p<0.01) on the diet containing cassava chips compared to diets with cassava pellets. Enzyme supplementation increased (p<0.01) feed intake on all diets. Live weight at day 21 was significantly (p<0.01) reduced on the diet based on cassava chips compared to pellets, but an improvement (p<0.01) was noticed with the enzyme supplementation. Metabolizable energy intake was reduced (p<0.01) by both cassava chips and pellets, but was increased (p<0.01) on all diets by enzyme supplementation. The NEp was higher (p<0.01) in the maize-based diets than the diets containing cassava. Enzyme supplementation improved (p<0.01) NEp in all the diets. Heat production was highest (p<0.01) on diets containing cassava pellets than on cassava chips. It is possible to use cassava pellets in diets for broiler chickens at a level close to 50% of the diet to reduce cost of production, and the nutritive value of such diets can be improved through supplementation of enzyme products containing carbohydrases, protease, and phytase.

Understanding the relationship between climate and crop productivity is a key component of projections of future food production, and hence assessments of food security. Climate models and crop yield datasets have errors, but the effects of these errors on regional scale crop models is not well categorized and understood. In this study we compare the effect of synthetic errors in temperature and precipitation observations on the hindcast skill of a process-based crop model and a statistical crop model. We find that errors in temperature data have a significantly stronger influence on both models than errors in precipitation. We also identify key differences in the responses of these models to different types of input data error. Statistical and process-based model responses differ depending on whether synthetic errors are overestimates or underestimates. We also investigate the impact of crop yield calibration data on model skill for both models, using datasets of yield at three different spatial scales. Whilst important for both models, the statistical model is more strongly influenced by crop yield scale than the process-based crop model. However, our results question the value of high resolution yield data for improving the skill of crop models; we find a focus on accuracy to be more likely to be valuable. For both crop models, and for all three spatial scales of yield calibration data, we found that model skill is greatest where growing area is above 10-15 %. Thus information on area harvested would appear to be a priority for data collection efforts. These results are important for three reasons. First, understanding how different crop models rely on different characteristics of temperature, precipitation and crop yield data allows us to match the model type to the available data. Second, we can prioritize where improvements in climate and crop yield data should be directed. Third, as better climate and crop yield data becomes available, we can predict how crop model skill should improve.

Two chickpea genotypes viz. Bhakar-2011 (desi) and Noor-2013 (kabuli) were sown in soil filled pots supplied with low (0.3 mg kg-1) and high (3 mg kg-1 soil) zinc (Zn) under control (70% water holding capacity and 25/20 °C day/night temperature), drought (35% water holding capacity) and heat (35/30 °C day/night temperature) stresses. Drought and heat stresses reduced rate of photosynthesis, photosystem II efficiency, plant growth and Zn uptake in chickpea. Low Zn supply exacerbated adverse effects of drought and heat stresses in chickpea, and caused reduction in plant biomass, carbon assimilation, antioxidant activity, impeded Zn uptake and enhanced oxidative damage. However, adequate Zn supply ameliorated adverse effect of drought and heat stresses in both chickpea types. The improvements were more in desi than kabuli type. Adequate Zn nutrition is crucial to augment growth of chickpea plants under high temperature and arid climatic conditions.

AbstractRising atmospheric [CO2] and associated climate change are expected to modify primary productivity across a range of ecosystems globally. Increasing aridity is predicted to reduce grassland productivity, although rising [CO2] and associated increases in plant water use efficiency may partially offset the effect of drying on growth. Difficulties arise in predicting the direction and magnitude of future changes in ecosystem productivity, due to limited field experimentation investigating climate and CO2 interactions. We use repeat near‐surface digital photography to quantify the effects of water availability and experimentally manipulated elevated [CO2] (eCO2) on understorey live foliage cover and biomass over three growing seasons in a temperate grassy woodland in south‐eastern Australia. We hypothesised that (i) understorey herbaceous productivity is dependent upon soil water availability, and (ii) that eCO2 will increase productivity, with greatest stimulation occurring under conditions of low water availability. Soil volumetric water content (VWC) determined foliage cover and growth rates over the length of the growing season (August to March), with low VWC (<0.1 m3 m−3) reducing productivity. However, eCO2 did not increase herbaceous cover and biomass over the duration of the experiment, or mitigate the effects of low water availability on understorey growth rates and cover. Our findings suggest that projected increases in aridity in temperate woodlands are likely to lead to reduced understorey productivity, with little scope for eCO2 to offset these changes.

Alpine grasslands on the Qinghai-Tibetan Plateau are sensitive and vulnerable to climate change and human activities. Climate warming and overgrazing have already caused degradation in a large fraction of alpine grasslands on this plateau. However, it remains unclear how human activities (mainly livestock grazing) regulates vegetation dynamics under climate change. Here, alpine grassland productivity (substituted with the normalized difference vegetation index, NDVI) is hypothesized to vary in a nonlinear trajectory to follow climate fluctuations and human disturbances. With generalized additive mixed modelling (GAMM) and residual-trend (RESTREND) analysis together, both magnitude and direction of climatic (in terms of temperature, precipitation, and radiation) and anthropogenic impacts on NDVI variation were examined across alpine meadows, steppes, and desert-steppes on the Qinghai-Tibetan Plateau. The results revealed that accelerating warming and greening, respectively, took place in 76.2% and 78.8% of alpine grasslands on the Qinghai-Tibetan Plateau. The relative importance of temperature, precipitation, and radiation impacts was comparable, between 20.4% and 24.8%, and combined to explain 66.2% of NDVI variance at the pixel scale. The human influence was strengthening and weakening, respectively, in 15.5% and 14.3% of grassland pixels, being slightly larger than any sole climatic variable across the entire plateau. Anthropogenic and climatic factors can be in opposite ways to affect alpine grasslands, even within the same grassland type, likely regulated by plant community assembly and species functional traits. Therefore, the underlying mechanisms of how plant functional diversity regulates nonlinear ecosystem response to climatic and anthropogenic stresses should be carefully explored in the future.