965 resultados para Yield Adaptation
Resumo:
Many research projects in life sciences require purified biologically active recombinant protein. In addition, different formats of a given protein may be needed at different steps of experimental studies. Thus, the number of protein variants to be expressed and purified in short periods of time can expand very quickly. We have therefore developed a rapid and flexible expression system based on described episomal vector replication to generate semi-stable cell pools that secrete recombinant proteins. We cultured these pools in serum-containing medium to avoid time-consuming adaptation of cells to serum-free conditions, maintain cell viability and reuse the cultures for multiple rounds of protein production. As such, an efficient single step affinity process to purify recombinant proteins from serum-containing medium was optimized. Furthermore, a series of multi-cistronic vectors were designed to enable simultaneous expression of proteins and their biotinylation in vivo as well as fast selection of protein-expressing cell pools. Combining these improved procedures and innovative steps, exemplified with seven cytokines and cytokine receptors, we were able to produce biologically active recombinant endotoxin free protein at the milligram scale in 4-6weeks from molecular cloning to protein purification.
Resumo:
The objective of this work was to investigate the genotype-environment interaction in Mato Grosso State, MT. The relative importance of locations, years, sowing dates and cultivars and their interactions was analyzed from data collected in regional yield trials performed in a randomized complete block design with four replications, from 1994-1995 through 1999-2000, in nine locations and two sowing dates. Individual and pooled analyses of variance over years and locations were performed. Complementary analyses of variances partitioned MT State in two main and five smaller regions, respectively: North and South of Cuiabá; and MT-South-A (Pedra Preta area), MT-South-B (Rondonópolis and Itiquira), MT-East (Primavera do Leste and Campo Verde), MT-Central (Nova Mutum, Lucas do Rio Verde and Sorriso) and MT-Parecis (Campo Novo dos Parecis and Sapezal). Locations are relatively more important than years for yield testing soybeans in the MT State, therefore, investment should be made in increasing locations rather than years to improve experimental precision. Partitioning the MT State into regions has little impact on soybean yield testing results and, consequently, on the efficiency of the soybean breeding program in the State. Breeding genotypes with broad adaptation for the MT State is an efficient strategy for cultivar development.
Resumo:
The present investigation on “Coconut Phenology and Yield Response to Climate Variability and Change” was undertaken at the experimental site, at the Regional Station, Coconut Development Board, KAU Campus, Vellanikkara. Ten palms each of eight-year-old coconut cultivars viz., Tiptur Tall, Kuttiadi (WCT), Kasaragod (WCT) and Komadan (WCT) were randomly selected.The study therefore, reinforces our traditional knowledge that the coconut palm is sensitive to changing weather conditions during the period from primordium initiation to harvest of nuts (about 44 months). Absence of rainfall from December to May due to early withdrawal of northeast monsoon, lack of pre monsoon showers and late onset of southwest monsoon adversely affect the coconut productivity to a considerable extent in the following year under rainfed conditions. The productivity can be increased by irrigating the coconut palm during the dry periods.Increase in temperature, aridity index, number of severe summer droughts and decline in rainfall and moisture index were the major factors for a marginal decline or stagnation in coconut productivity over a period of time, though various developmental schemes were in operation for sustenance of coconut production in the State of Kerala. It can be attributed to global warming and climate change. Therefore, there is a threat to coconut productivity in the ensuing decades due to climate variability and change. In view of the above, there is an urgent need for proactive measures as a part of climate change adaptation to sustain coconut productivity in the State of Kerala.The coconut productivity is more vulnerable to climate variability such as summer droughts rather than climate change in terms of increase in temperature and decline in rainfall, though there was a marginal decrease (1.6%) in the decade of 1981-2009 when compared to that of 1951-80. This aspect needs to be examined in detail by coconut development agencies such as Coconut Development Board and State Agriculture Department for remedial measures. Otherwise, the premier position of Kerala in terms of coconut production is likely to be lost in the ensuing years under the projected climate change scenario. Among the four cultivars studied, Tiptur Tall appears to be superior in terms of reproduction phase and nut yield. This needs to be examined by the coconut breeders in their crop improvement programme as a part of stress tolerant under rainfed conditions. Crop mix and integrated farming are supposed to be the best combination to sustain development in the long run under the projected climate change scenarios. Increase in coconut area under irrigation during summer with better crop management and protection measures also are necessary measures to increase coconut productivity since the frequency of intensity of summer droughts is likely to increase under projected global warming scenario.
Resumo:
Poor adaptation to climate change is a major threat to sustainable rice production in Nigeria. Determinants of appropriate climate-change adaptation strategies used by rice farmers in Southwestern Nigeria have not been fully investigated. In this study, the determinants of climate change adaptation strategies used by rice farmers in Southwestern Nigeria were investigated. Data were obtained through Focus Group Discussions (FGDs) and field survey conducted in the study areas. Data obtained were analyzed using descriptive and inferential statistical tools such as percentage and regression analysis. The major climate change adaptation strategies used by the respondents included; planting improved rice variety such as Federal Agricultural Research Oryza (FARO) (80.5 %), seeking early warning information (80.9 %), shifting planting date until the weather condition was favourable (99.1 %), and using chemical fertilizer on their farms in order to maintain soil fertility (20.5 %). The determinants of climate change adaptation strategies used by the farmers, included access to early warning information (β=43.04), access to fertilizer (β=5.78), farm plot size (β=–12.04) and access to regular water supply (β=–24.79). Climate change adaptation required provision of incentives to farmers, training on drought and flood control, and the use of improved technology to obtain higher yield.
Resumo:
The impacts of climate change on nitrogen (N) in a lowland chalk stream are investigated using a dynamic modelling approach. The INCA-N model is used to simulate transient daily hydrology and water quality in the River Kennet using temperature and precipitation scenarios downscaled from the General Circulation Model (GCM) output for the period 1961-2100. The three GCMs (CGCM2, CSIRO and HadCM3) yield very different river flow regimes with the latter projecting significant periods of drought in the second half of the 21st century. Stream-water N concentrations increase over time as higher temperatures enhance N release from the soil, and lower river flows reduce the dilution capacity of the river. Particular problems are shown to occur following severe droughts when N mineralization is high and the subsequent breaking of the drought releases high nitrate loads into the river system. Possible strategies for reducing climate-driven N loads are explored using INCA-N. The measures include land use change or fertiliser reduction, reduction in atmospheric nitrate and ammonium deposition, and the introduction of water meadows or connected wetlands adjacent to the river. The most effective strategy is to change land use or reduce fertiliser use, followed by water meadow creation, and atmospheric pollution controls. Finally, a combined approach involving all three strategies is investigated and shown to reduce in-stream nitrate concentrations to those pre-1950s even under climate change. (c) 2006 Elsevier B.V. All rights reserved.
Resumo:
The importance of temperature in the determination of the yield of an annual crop (groundnut; Arachis hypogaea L. in India) was assessed. Simulations from a regional climate model (PRECIS) were used with a crop model (GLAM) to examine crop growth under simulated current (1961-1990) and future (2071-2100) climates. Two processes were examined: the response of crop duration to mean temperature and the response of seed-set to extremes of temperature. The relative importance of, and interaction between, these two processes was examined for a number of genotypic characteristics, which were represented by using different values of crop model parameters derived from experiments. The impact of mean and extreme temperatures varied geographically, and depended upon the simulated genotypic properties. High temperature stress was not a major determinant of simulated yields in the current climate, but affected the mean and variability of yield under climate change in two regions which had contrasting statistics of daily maximum temperature. Changes in mean temperature had a similar impact on mean yield to that of high temperature stress in some locations and its effects were more widespread. Where the optimal temperature for development was exceeded, the resulting increase in duration in some simulations fully mitigated the negative impacts of extreme temperatures when sufficient water was available for the extended growing period. For some simulations the reduction in mean yield between the current and future climates was as large as 70%, indicating the importance of genotypic adaptation to changes in both means and extremes of temperature under climate change. (c) 2006 Elsevier B.V. All rights reserved.
Resumo:
Crop production is inherently sensitive to fluctuations in weather and climate and is expected to be impacted by climate change. To understand how this impact may vary across the globe many studies have been conducted to determine the change in yield of several crops to expected changes in climate. Changes in climate are typically derived from a single to no more than a few General Circulation Models (GCMs). This study examines the uncertainty introduced to a crop impact assessment when 14 GCMs are used to determine future climate. The General Large Area Model for annual crops (GLAM) was applied over a global domain to simulate the productivity of soybean and spring wheat under baseline climate conditions and under climate conditions consistent with the 2050s under the A1B SRES emissions scenario as simulated by 14 GCMs. Baseline yield simulations were evaluated against global country-level yield statistics to determine the model's ability to capture observed variability in production. The impact of climate change varied between crops, regions, and by GCM. The spread in yield projections due to GCM varied between no change and a reduction of 50%. Without adaptation yield response was linearly related to the magnitude of local temperature change. Therefore, impacts were greatest for countries at northernmost latitudes where warming is predicted to be greatest. However, these countries also exhibited the greatest potential for adaptation to offset yield losses by shifting the crop growing season to a cooler part of the year and/or switching crop variety to take advantage of an extended growing season. The relative magnitude of impacts as simulated by each GCM was not consistent across countries and between crops. It is important, therefore, for crop impact assessments to fully account for GCM uncertainty in estimating future climates and to be explicit about assumptions regarding adaptation.
Resumo:
Climate has been changing in the last fifty years in China and will continue to change regardless any efforts for mitigation. Agriculture is a climate-dependent activity and highly sensitive to climate changes and climate variability. Understanding the interactions between climate change and agricultural production is essential for society stable development of China. The first mission is to fully understand how to predict future climate and link it with agriculture production system. In this paper, recent studies both domestic and international are reviewed in order to provide an overall image of the progress in climate change researches. The methods for climate change scenarios construction are introduced. The pivotal techniques linking crop model and climate models are systematically assessed and climate change impacts on Chinese crops yield among model results are summarized. The study found that simulated productions of grain crop inherit uncertainty from using different climate models, emission scenarios and the crops simulation models. Moreover, studies have different spatial resolutions, and methods for general circulation model (GCM) downscaling which increase the uncertainty for regional impacts assessment. However, the magnitude of change in crop production due to climate change (at 700 ppm CO2 eq correct) appears within ±10% for China in these assessments. In most literatures, the three cereal crop yields showed decline under climate change scenarios and only wheat in some region showed increase. Finally, the paper points out several gaps in current researches which need more studies to shorten the distance for objective recognizing the impacts of climate change on crops. The uncertainty for crop yield projection is associated with climate change scenarios, CO2 fertilization effects and adaptation options. Therefore, more studies on the fields such as free air CO2 enrichment experiment and practical adaptations implemented need to be carried out
Resumo:
In the present report and for the first time in the international literature, the impact of the addition of NaCl upon growth and lipid production on the oleaginous yeast Rhodosporidium toruloides was studied. Moreover, equally for first time, lipid production by R. toruloides was performed under non-aseptic conditions. Therefore, the potentiality of R. toruloides DSM 4444 to produce lipid in media containing several initial concentrations of NaCl with glucose employed as carbon source was studied. Preliminary batch-flask trials with increasing amounts of NaCl revealed the tolerance of the strain against NaCl content up to 6.0% (w/v). However, 4.0% (w/v) of NaCl stimulated lipid accumulation for this strain, by enhancing lipid production up to 71.3% (w/w) per dry cell weight. The same amount of NaCl was employed in pasteurized batch-flask cultures in order to investigate the role of the salt as bacterial inhibiting agent. The combination of NaCl and high glucose concentrations was found to satisfactorily suppress bacterial contamination of R. toruloides cultures under these conditions. Batch-bioreactor trials of the yeast in the same media with high glucose content (up to 150 g/L) resulted in satisfactory substrate assimilation, with almost linear kinetic profile for lipid production, regardless of the initial glucose concentration imposed. Finally, fed-batch bioreactor cultures led to the production of 37.2 g/L of biomass, accompanied by 64.5% (w/w) of lipid yield. Lipid yield per unit of glucose consumed received the very satisfactory value of 0.21 g/g, a value amongst the highest ones in the literature. The yeast lipid produced contained mainly oleic acid and to lesser extent palmitic and stearic acids, thus constituting a perfect starting material for “second generation” biodiesel
Resumo:
Case-Based Reasoning is a methodology for problem solving based on past experiences. This methodology tries to solve a new problem by retrieving and adapting previously known solutions of similar problems. However, retrieved solutions, in general, require adaptations in order to be applied to new contexts. One of the major challenges in Case-Based Reasoning is the development of an efficient methodology for case adaptation. The most widely used form of adaptation employs hand coded adaptation rules, which demands a significant knowledge acquisition and engineering effort. An alternative to overcome the difficulties associated with the acquisition of knowledge for case adaptation has been the use of hybrid approaches and automatic learning algorithms for the acquisition of the knowledge used for the adaptation. We investigate the use of hybrid approaches for case adaptation employing Machine Learning algorithms. The approaches investigated how to automatically learn adaptation knowledge from a case base and apply it to adapt retrieved solutions. In order to verify the potential of the proposed approaches, they are experimentally compared with individual Machine Learning techniques. The results obtained indicate the potential of these approaches as an efficient approach for acquiring case adaptation knowledge. They show that the combination of Instance-Based Learning and Inductive Learning paradigms and the use of a data set of adaptation patterns yield adaptations of the retrieved solutions with high predictive accuracy.
Resumo:
Warm-season grasses are economically important for cattle production in tropical regions and tools to aid in management and research on these forages would be highly beneficial both in research and the industry. This research was conducted to adapt the CROPGRO-Perennial Forage model to simulate growth of the tropical species guineagrass (Panicum maximum Jacq. cv. 'Tanzania') and to describe model adaptation for this species. To develop the CROPGRO parameters for this species, we began with values and relationships reported in the literature. Some parameters and relationships were calibrated by comparison with observed growth, development, dry matter accumulation, and partitioning during a 17-mo experiment with Tanzania guineagrass in Piracicaba, SP, Brazil. Compared with starting parameters for palisadegrass [Brachiaria brizantha (A. Rich.) Stapf. cv. 'Xaraes'], dormancy effects of the perennial forage model had to be minimized, partitioning to storage tissue or root decreased, and partitioning to leaf and stem increased to provide for more leaf and stem growth and less root. Parameters affecting specific leaf area and senescence of plant tissues were improved. After these changes were made to the model, biomass accumulation was better simulated, mean predicted herbage yield was 6576 kg ha(-1), averaged across 11 regrowth cycles of 35 (summer) or 63 d (winter), with a RMSE of 494 kg ha(-1) (Willmott's index of agreement d = 0.985, simulated/observed ratio = 1.014). The model also gave good predictions against an independent data set, with similar RMSE, ratio, and d. The results of the adaptation suggest that the CROPGRO model is an efficient tool to integrate physiological aspects of guineagrass and can be used to simulate growth.
Resumo:
Despite the great importance of soybeans in Brazil, there have been few applications of soybean crop modeling on Brazilian conditions. Thus, the objective of this study was to use modified crop models to estimate the depleted and potential soybean crop yield in Brazil. The climatic variable data used in the modified simulation of the soybean crop models were temperature, insolation and rainfall. The data set was taken from 33 counties (28 Sao Paulo state counties, and 5 counties from other states that neighbor São Paulo). Among the models, modifications in the estimation of the leaf area of the soybean crop, which includes corrections for the temperature, shading, senescence, CO2, and biomass partition were proposed; also, the methods of input for the model's simulation of the climatic variables were reconsidered. The depleted yields were estimated through a water balance, from which the depletion coefficient was estimated. It can be concluded that the adaptation soybean growth crop model might be used to predict the results of the depleted and potential yield of soybeans, and it can also be used to indicate better locations and periods of tillage.
Resumo:
Wine grape must deal with serious problems due to the unfavorable climatic conditions resulted from global warming. High temperatures result in oxidative damages to grape vines. The excessive elevated temperatures are critical for grapevine productivity and survival and contribute to degradation of grape and wine quality and yield. Elevated temperature can negatively affect anthocyanin accumulation in red grape. Particularly, cv. Sangiovese was identified to be very sensitive to such condition. The quantitative real-time PCR analysis showed that flavonoid biosynthetic genes were slightly repressed by high temperature. Also, the heat stress repressed the expression of the transcription factor “VvMYBA1” that activates the expression of UFGT. Moreover, high temperatures had repressing effects on the activity of the flavonoids biosynthetic enzymes “PAL” and “UFGT”.Anthocyanin accumulation in berry skin is due to the balance between its synthesis and oxidation. In grape cv. Sangiovese, the gene transcription and activity of peroxidases enzyme was elevated by heat stress as a defensive mechanism of ROS-scavenging. Among many isoforms of peroxidases genes, one gene (POD 1) was induced in Sangiovese under thermal stress condition. This gene was isolated and evaluated via the technique of genes transformation from grape to Petunia. Reduction in anthocyanins concentration and higher enzymatic activity of peroxidase was observed in POD 1 transformed Petunia after heat shock compared to untrasformed control. Moreover, in wine producing regions, it is inevitable for the grape growers to adopt some adaptive strategies to alleviate grape damages to abiotic stresses. Therefore, in this thesis, the technique of post veraison trimming was done to improve the coupling of phenolic and sugar ripening in Vitis vinifera L. cultivar Sangiovese. Trimming after veraison showed to be executable to slow down the rate of sugar accumulation in grape (to decrease the alcohol potential in wines) without evolution of the main berry flavonoids compounds.
Resumo:
Prevention and treatment of osteoporosis rely on understanding of the micromechanical behaviour of bone and its influence on fracture toughness and cell-mediated adaptation processes. Postyield properties may be assessed by nonlinear finite element simulations of nanoindentation using elastoplastic and damage models. This computational study aims at determining the influence of yield surface shape and damage on the depth-dependent response of bone to nanoindentation using spherical and conical tips. Yield surface shape and damage were shown to have a major impact on the indentation curves. Their influence on indentation modulus, hardness, their ratio as well as the elastic-to-total work ratio is well described by multilinear regressions for both tip shapes. For conical tips, indentation depth was not statistically significant (p<0.0001). For spherical tips, damage was not a significant parameter (p<0.0001). The gained knowledge can be used for developing an inverse method for identification of postelastic properties of bone from nanoindentation.
Resumo:
Besides its primary role in producing food and fiber, agriculture also has relevant effects on several other functions, such as management of renewable natural resources. Climate change (CC) may lead to new trade-offs between agricultural functions or aggravate existing ones, but suitable agricultural management may maintain or even improve the ability of agroecosystems to supply these functions. Hence, it is necessary to identify relevant drivers (e.g., cropping practices, local conditions) and their interactions, and how they affect agricultural functions in a changing climate. The goal of this study was to use a modeling framework to analyze the sensitivity of indicators of three important agricultural functions, namely crop yield (food and fiber production function), soil erosion (soil conservation function), and nutrient leaching (clean water provision function), to a wide range of agricultural practices for current and future climate conditions. In a two-step approach, cropping practices that explain high proportions of variance of the different indicators were first identified by an analysis of variance-based sensitivity analysis. Then, most suitable combinations of practices to achieve best performance with respect to each indicator were extracted, and trade-offs were analyzed. The procedure was applied to a region in western Switzerland, considering two different soil types to test the importance of local environmental constraints. Results show that the sensitivity of crop yield and soil erosion due to management is high, while nutrient leaching mostly depends on soil type. We found that the influence of most agricultural practices does not change significantly with CC; only irrigation becomes more relevant as a consequence of decreasing summer rainfall. Trade-offs were identified when focusing on best performances of each indicator separately, and these were amplified under CC. For adaptation to CC in the selected study region, conservation soil management and the use of cropped grasslands appear to be the most suitable options to avoid trade-offs.