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Author Bellocchi, G.; Sándor, R.
Title Model intercomparison Type Report
Year 2015 Publication FACCE MACSUR Reports Abbreviated Journal
Volume 6 Issue Pages D-L2.4
Keywords
Abstract (down) This deliverable focuses on some illustrative results obtained with different grassland- specific, grassland adapted crop and dynamic vegetation models selected out of the first list of models compiled in D-L2.1.1 to simulate biomass and flux data from grassland sites in Europe and peri-Mediterranean regions (D-L2.1.1 and D-L2.1.2). Results from uncalibrated simulations were documented in the D-L2.3 report as a blind exercise. Some model improvements are emphasized in this report due to the higher information level of the model calibrations. The complete set of results will include simulations from uncalibrated and calibrated models. No Label
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes Approved no
Call Number MA @ admin @ Serial 2108
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Author Baker, A.; Ceasar, S.A.; Palmer, A.J.; Paterson, J.B.; Qi, W.; Muench, S.P.; Baldwin, S.A.
Title Replace, reuse, recycle: improving the sustainable use of phosphorus by plants Type Journal Article
Year 2015 Publication Journal of Experimental Botany Abbreviated Journal J. Experim. Bot.
Volume 66 Issue 12 Pages 3523-3540
Keywords Conservation of Natural Resources; Crops, Agricultural/growth & development/metabolism; Gene Expression Regulation, Plant; Phosphorus/*metabolism; Plant Proteins/genetics/metabolism; Plants/genetics/*metabolism; Fertilizers; membrane transporters; nutrient recycling; phosphate; phosphate signalling; transcription factors
Abstract (down) The ‘phosphorus problem’ has recently received strong interest with two distinct strands of importance. The first is that too much phosphorus (P) is entering into waste water, creating a significant economic and ecological problem. Secondly, while agricultural demand for phosphate fertilizer is increasing to maintain crop yields, rock phosphate reserves are rapidly declining. Unravelling the mechanisms by which plants sense, respond to, and acquire phosphate can address both problems, allowing the development of crop plants that are more efficient at acquiring and using limited amounts of phosphate while at the same time improving the potential of plants and other photosynthetic organisms for nutrient recapture and recycling from waste water. In this review, we attempt to synthesize these important but often disparate parts of the debate in a holistic fashion, since solutions to such a complex problem require integrated and multidisciplinary approaches that address both P supply and demand. Rapid progress has been made recently in our understanding of local and systemic signalling mechanisms for phosphate, and of expression and regulation of membrane proteins that take phosphate up from the environment and transport it within the plant. We discuss the current state of understanding of such mechanisms involved in sensing and responding to phosphate stress. We also discuss approaches to improve the P-use efficiency of crop plants and future direction for sustainable use of P, including use of photosynthetic organisms for recapture of P from waste waters.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0022-0957 1460-2431 ISBN Medium Review
Area Expedition Conference
Notes CropM Approved no
Call Number MA @ admin @ Serial 4548
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Author Foyer, C.H.; Siddique, K.H.M.; Tai, A.P.K.; Anders, S.; Fodor, N.; Wong, F.-L.; Ludidi, N.; Chapman, M.A.; Ferguson, B.J.; Considine, M.J.; Zabel, F.; Prasad, P.V.V.; Varshney, R.K.; Nguyen, H.T.; Lam, H.-M.
Title Modelling predicts that soybean is poised to dominate crop production across Africa Type Journal Article
Year 2019 Publication Plant Cell and Environment Abbreviated Journal Plant Cell Environ.
Volume 42 Issue 1 Pages 373-385
Keywords Climate-Change; Food Security; Sustainable Intensification; Smallholder; Farmers; Nitrogen-Fixation; Yield; Adaptation; Diversity; Impact; CO2
Abstract (down) The superior agronomic and human nutritional properties of grain legumes (pulses) make them an ideal foundation for future sustainable agriculture. Legume-based farming is particularly important in Africa, where small-scale agricultural systems dominate the food production landscape. Legumes provide an inexpensive source of protein and nutrients to African households as well as natural fertilization for the soil. Although the consumption of traditionally grown legumes has started to decline, the production of soybeans (Glycine max Merr.) is spreading fast, especially across southern Africa. Predictions of future land-use allocation and production show that the soybean is poised to dominate future production across Africa. Land use models project an expansion of harvest area, whereas crop models project possible yield increases. Moreover, a seed change in farming strategy is underway. This is being driven largely by the combined cash crop value of products such as oils and the high nutritional benefits of soybean as an animal feed. Intensification of soybean production has the potential to reduce the dependence of Africa on soybean imports. However, a successful “soybean bonanza” across Africa necessitates an intensive research, development, extension, and policy agenda to ensure that soybean genetic improvements and production technology meet future demands for sustainable production.
Address 2019-01-10
Corporate Author Thesis
Publisher Place of Publication Editor
Language English Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN 0140-7791 ISBN Medium
Area Expedition Conference
Notes CropM, ft_macsur Approved no
Call Number MA @ admin @ Serial 5215
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Author Bojar, W.; Żarski, J.; Knopik, L.; Kuśmierek-Tomaszewska, R.; Sikora, M.; Dzieża, G.
Title Markov chain as a model of daily total precipitation and a prediction of future natural events Type Conference Article
Year 2015 Publication Abbreviated Journal
Volume Issue Pages
Keywords ft_macsur; MACSUR or FACCE acknowledged.
Abstract (down) The size of arable crop yields depends on many weather factors, such as precipitation and air temperature during the vegetation period. When studying the relation between yields and precipitation, not only the total amount of precipitation, but also the occurrence of long periods without precipitation must be taken into account. The paper [Bojar et al., 2014] demonstrated that barley yield significantly statistically depends on the length of the series of days without precipitation. This paper attempts to analyse the statistical data on daily precipitation totals recorded during the January – December periods in the years 1971 – 2013 at the weather station of the University of Science and Technology in Bydgoszcz, Faculty of Agriculture and Biotechnology, in the Research Centre located in an agricultural area in the Mochle township, situated 17 kilometres from Bydgoszcz. The primary statistical operation in the study is an attempt to estimate the Markov chain order. To this end, two criteria of chain order determination are applied: BIC (Bayesian information criterion, Schwarz 1978) and AIC (Akaike information criterion, Akaike 1974). Both are based on the log-likelihood functions for transition probability of the Markov chain constructed on certain data series. Statistical analysis of precipitation totals data leads to the conclusion that both AIC and BIC indicate the 2nd order for the studied Markov chain. The proposed method of estimating the variability of precipitation occurrence in the future will be utilised to improve region-related bio-physical and economical models, and to assess the risk of extreme events in the context of growing climate hazards. It will serve as basis for a search in agriculture for solutions mitigating those hazards.
Address
Corporate Author Thesis
Publisher Place of Publication Braunschweig (Germany) Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference FACCE MACSUR Joint Workshops October 2015, 2015-10-27 to 2015-10-30, Braunschweig
Notes Approved no
Call Number MA @ admin @ Serial 4236
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Author Bojar, W.; Żarski, J.; Knopik, L.; Kuśmierek-Tomaszewska, R.; Sikora, M.; Dzieża, G.
Title Markov chain as a model of daily total precipitation and a prediction of future natural events Type Conference Article
Year 2015 Publication Abbreviated Journal
Volume Issue Pages
Keywords ft_macsur; MACSUR or FACCE acknowledged.
Abstract (down) The size of arable crop yields depends on many weather factors, such as precipitation and air temperature during the vegetation period. When studying the relation between yields and precipitation, not only the total amount of precipitation, but also the occurrence of long periods without precipitation must be taken into account. The paper [Bojar et al., 2014] demonstrated that barley yield significantly statistically depends on the length of the series of days without precipitation. This paper attempts to analyse the statistical data on daily precipitation totals recorded during the January – December periods in the years 1971 – 2013 at the weather station of the University of Science and Technology in Bydgoszcz, Faculty of Agriculture and Biotechnology, in the Research Centre located in an agricultural area in the Mochle township, situated 17 kilometres from Bydgoszcz. The primary statistical operation in the study is an attempt to estimate the Markov chain order. To this end, two criteria of chain order determination are applied: BIC (Bayesian information criterion, Schwarz 1978) and AIC (Akaike information criterion, Akaike 1974). Both are based on the log-likelihood functions for transition probability of the Markov chain constructed on certain data series. Statistical analysis of precipitation totals data leads to the conclusion that both AIC and BIC indicate the 2nd order for the studied Markov chain. The proposed method of estimating the variability of precipitation occurrence in the future will be utilised to improve region-related bio-physical and economical models, and to assess the risk of extreme events in the context of growing climate hazards. It will serve as basis for a search in agriculture for solutions mitigating those hazards.
Address
Corporate Author Thesis
Publisher Place of Publication Braunschweig (Germany) Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference FACCE MACSUR Joint Workshops October 2015, 2015-10-27 to 2015-10-30, Braunschweig
Notes Approved no
Call Number MA @ admin @ Serial 4395
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