Comparison of performances of drying techniques of surfaces in agro food premises

International audienceCleaning and disinfection (C&D) are among the most important hazard control measures in ready-to-eat food plants. The C&D process requires a huge volume of water that wets the surfaces of the food processing premises. The water remaining on these surfaces are susceptible to be the source of a microbial reservoir as wet media are favorable to microbial growth. To face this problem, a rapid drying after C&D is to be sought. For this purpose, the humidity control of the air in the premises is to be obtained. In this purpose, three technologies could be employed: (i) a classical one based on dew point air treatment, (ii) the use of liquid desiccant and (iii) the use of desiccant wheels. This paper compares the energy consumption of these three techniques for typical premises which can be found in agrofood industry. The energy consumptions of these techniques are assessed with simplified approaches which may sometimes be open to discussion. Nevertheless, the results indicate some major tendencies and allow supporting interesting conclusions

Estimating yield potential in temperate high-yielding, direct-seeded US rice production systems

Accurate estimation of a crop’s yield potential (Yp) is critical to addressing long-term food security via identification of the exploitable yield gap. Due to lack of field data, efforts to quantify crop yield potential typically rely on crop models. Using the ORYZA rice crop model, we sought to estimate Yp of irrigated rice for two widely used rice varieties (M-206 and CXL745) in three major US rice-producing regions that together represent some of the highest yielding rice regions of the world. Three major issues with the crop model had to be addressed to achieve acceptable simulation of Yp; first, the model simulated leaf area index (LAI) and biomass agreed poorly for all direct-seeded systems using default settings;second, cold-induced sterility and associated yield losses were poorly simulated for environments with a large diurnal temperature variation; lastly, simulated Yp was sensitive to the specified definition of physiological maturity. Except for the simulation of cold-induced sterility, all issues could be remedied within the existing model structure. In contrast, simulation of cold-induced sterility posed a continuing challenge to accurate simulation—one that will likely require changes to ORYZA’s formulation. Estimates of Yp from the modified model were validated against large multi-year data sets of experimental yields covering the majority of US rice production areas. Validation showed the adjusted model simulated Yp well, with most top yields falling within 85% of Yp for both varieties (77% and 78% observed yields within15% of Yp for CXL745 and M-206 respectively). Maximum estimated Yp was 14.3 (range of 8.2–14.5) and14.5 (range of 8.7–15.3) t ha−1for the Southern US and CA, respectively

Estimating yield potential in temperate high-yielding, direct-seeded US rice production systems

Accurate estimation of a crop’s yield potential (Yp) is critical to addressing long-term food security via identification of the exploitable yield gap. Due to lack of field data, efforts to quantify crop yield potential typically rely on crop models. Using the ORYZA rice crop model, we sought to estimate Yp of irrigated rice for two widely used rice varieties (M-206 and CXL745) in three major US rice-producing regions that together represent some of the highest yielding rice regions of the world. Three major issues with the crop model had to be addressed to achieve acceptable simulation of Yp; first, the model simulated leaf area index (LAI) and biomass agreed poorly for all direct-seeded systems using default settings;second, cold-induced sterility and associated yield losses were poorly simulated for environments with a large diurnal temperature variation; lastly, simulated Yp was sensitive to the specified definition of physiological maturity. Except for the simulation of cold-induced sterility, all issues could be remedied within the existing model structure. In contrast, simulation of cold-induced sterility posed a continuing challenge to accurate simulation—one that will likely require changes to ORYZA’s formulation. Estimates of Yp from the modified model were validated against large multi-year data sets of experimental yields covering the majority of US rice production areas. Validation showed the adjusted model simulated Yp well, with most top yields falling within 85% of Yp for both varieties (77% and 78% observed yields within15% of Yp for CXL745 and M-206 respectively). Maximum estimated Yp was 14.3 (range of 8.2–14.5) and14.5 (range of 8.7–15.3) t ha−1for the Southern US and CA, respectively

Etude comparative de méthodes de restauration d'images dans le cas d'un modèle de dégradation spatialement variant

Nous proposons une comparaison des méthodes de : Tikhonov-Miller, Tikhonov-Miller avec modèle a priori de la solution, Markov et Maximum d'Entropie, dans le cas d'un système de dégradation spatialement variant. L'approximation du modèle variant par un modèle invariant est précisée. Il est montré que le choix d'une méthode de restauration sera fonction du type d'information a priori disponible et des caractéristiques de la PSF (Point Spread Function). Dans le cas de l'imagerie par sténopé, il est indispensable de prendre en compte la variabilité spatiale

Water productivity of rainfed maize and wheat: A local to global perspective

Water productivity (WP) is a robust benchmark for crop production in relation to available water supply across spatial scales. Quantifying water-limited potential (WPw) and actual on-farm (WPa) WP to estimate WP gaps is an essential first step to identify the most sensitive factors influencing production capacity with limited water supply. This study combines local weather, soil, and agronomic data, and crop modeling in a spatial framework to determine WPw and WPa at local and regional levels for rainfed cropping systems in 17 (maize) and 18 (wheat) major grain-producing countries representing a wide range of cropping systems, from intensive, highyield maize in north America and wheat in west Europe to low-input, low-yield maize systems in sub-Saharan Africa and south Asia. WP was calculated as the quotient of either water-limited yield potential or actual yield, and simulated crop evapotranspiration. Estimated WPw upper limits compared well with maximum WP reported for field-grown crops. However, there was large WPw variation across regions with different climate and soil (CV=29% for maize and 27% for wheat), which cautions against the use of generic WPw benchmarks and highlights the need for region-specific WPw. Differences in simulated evaporative demand, crop evapotranspiration after flowering, soil evaporation, and intensity of water stress around flowering collectively explained two thirds of the variation in WPw. Average WP gaps were 13 (maize) and 10 (wheat) kg ha−1 mm−1, equivalent to about half of their respective WPw. We found that non-water related factors (i.e., management deficiencies, biotic and abiotic stresses, and their interactions) constrained yield more than water supply in ca. half of the regions. These findings highlight the opportunity to produce more food with same amount of water, provided limiting factors other than water supply can be identified and alleviated with improved management practices. Our study provides a consistent protocol for estimating WP at local to regional scale, which can be used to understand WP gaps and their mitigation

Can Bangladesh produce enough cereals to meet future demand?

Bangladesh faces huge challenges in achieving food security due to its high population, diet changes, and limited room for expanding cropland and cropping intensity. The objective of this study is to assess the degree to which Bangladesh can be self-sufficient in terms of domestic maize, rice and wheat production by the years 2030 and 2050 by closing the existing gap (Yg) between yield potential (Yp) and actual farm yield (Ya), accounting for possible changes in cropland area. Yield potential and yield gaps were calculated for the three crops using well-validated crop models and site-specific weather,management and soil data, and upscaled to the whole country.We assessed potential grain production in the years 2030 and 2050 for six land use change scenarios (general decrease in arable land; declining ground water tables in the north; cropping of fallow areas in the south; effect of sea level rise; increased cropping intensity; and larger share of cash crops) and three levels of Yg closure (1: no yield increase; 2: Yg closure at a level equivalent to 50% (50% Yg closure); 3: Yg closure to a level of 85% of Yp (irrigated crops) and 80% of water-limited yield potential or Yw (rainfed crops) (full Yg closure)). In addition, changes in demand with low and high population growth rates, and substitution of rice by maize in future diets were also examined. Total aggregated demand of the three cereals (in milled rice equivalents) in 2030 and 2050, based on the UN median population variant, is projected to be 21 and 24% higher than in 2010. Current Yg represent 50% (irrigated rice), 48–63% (rainfed rice), 49% (irrigated wheat), 40% (rainfed wheat), 46% (irrigated maize), and 44% (rainfed maize) of their Yp or Yw. With 50% Yg closure and for various land use changes, self-sufficiency ratio will be N1 for rice in 2030 and about one in 2050 but well below one for maize and wheat in both 2030 and 2050. With full Yg closure, self-sufficiency ratios will be well above one for rice and all three cereals jointly but below one for maize and wheat for all scenarios, except for the scenario with drastic decrease in boro rice area to allow for area expansion for cash crops. Full Yg closure of all cereals is needed to compensate for area decreases and demand increases, and then even some maize and large amounts of wheat imports will be required to satisfy demand in future. The results of this analysis have important implications for Bangladesh and other countries with high population growth rate, shrinking arable land due to rapid urbanization, and highly vulnerable to climate change

Mapping rootable depth and root zone plant-available water holding capacity of the soil of sub-Saharan Africa

In rainfed crop production, root zone plant-available water holding capacity (RZ-PAWHC) of the soil has a large influence on crop growth and the yield response to management inputs such as improved seeds and fertilisers. However, data are lacking for this parameter in sub-Saharan Africa (SSA). This study produced the first spatially explicit, coherent and complete maps of the rootable depth and RZ-PAWHC of soil in SSA. We compiled georeferenced data from 28,000 soil profiles from SSA, which were used as input for digital soil mapping (DSM) techniques to produce soil property maps of SSA. Based on these soil properties, we developed and parameterised (pedotransfer) functions, rules and criteria to evaluate soil water retention at field capacity and wilting point, the soil fine earth fraction from coarse fragments content and, for maize, the soil rootability (relative to threshold values) and rootable depth. Maps of these secondary soil properties were derived using the primary soil property maps as input for the evaluation rules and the results were aggregated over the rootable depth to obtain a map of RZ-PAWHC, with a spatial resolution of 1 km2. The mean RZ-PAWHC for SSA is 74mm and the associated average root zone depth is 96 cm. Pearson correlation between the two is 0.95. RZ-PAWHC proves most limited by the rootable depth but is also highly sensitive to the definition of field capacity. The total soil volume of SSA potentially rootable by maize is reduced by one third (over 10,500 km3) due to soil conditions restricting root zone depth. Of these, 4800 km3 are due to limited depth of aeration, which is the factor most severely limiting in terms of extent (km2), and 2500 km3 due to sodicity which is most severely limiting in terms of degree (depth in cm). Depth of soil to bedrock reduces the rootable soil volume by 2500 km3, aluminium toxicity by 600 km3, porosity by 120 km3 and alkalinity by 20 km3. The accuracy of the map of rootable depth and thus of RZ-PAWHC could not be validated quantitatively due to absent data on rootability and rootable depth but is limited by the accuracy of the primary soil property maps. The methodological framework is robust and has been operationalised such that the maps can easily be updated as additional data become available

Food chain inefficiency (FCI) : accounting conversion efficiencies across entire food supply chains to re-define food loss and waste

Achieving global food security requires a new approach that integrates not only all aspects of the growing, harvesting and processing of food (necessary to ensure sufficient affordable and sustainable production to alleviate hunger) but also the complexities associated with food consumption including deterring unhealthy overconsumption. Inefficiencies occur at various points along the agri-food supply chain but at present they are inadequately conceptualized via separate accounts of food loss, food waste, supply chain management, and public health. Here we re-define food loss and waste through the concept of conversion efficiency applied to the entire system, an approach up to now only applied to the primary processes of crop productivity. Nine conversion efficiencies are defined: sunlight capture efficiency; photosynthesis use efficiency; biomass allocation efficiency; harvesting efficiency; storage and distribution efficiency; processing efficiency; retailing efficiency; consumption efficiency; and dietary efficiency. Using the production and consumption of bread in the UK as an example, we demonstrate how efficiencies may be estimated and thus where the main inefficiencies lie, so indicating where the most significant improvements could be made. We suggest that our approach, which introduces the term Food Chain Inefficiency (FCI) to re-define food loss and waste, provides a rational and effective way to devise the practical interventions and policies needed to deliver a sustainable agri-food system

Can Bangladesh produce enough cereals to meet future demand?

Bangladesh faces huge challenges in achieving food security due to its high population, diet changes, and limited room for expanding cropland and cropping intensity. The objective of this study is to assess the degree to which Bangladesh can be self-sufficient in terms of domestic maize, rice and wheat production by the years 2030 and 2050 by closing the existing gap (Yg) between yield potential (Yp) and actual farm yield (Ya), accounting for possible changes in cropland area. Yield potential and yield gaps were calculated for the three crops using well-validated crop models and site-specific weather,management and soil data, and upscaled to the whole country.We assessed potential grain production in the years 2030 and 2050 for six land use change scenarios (general decrease in arable land; declining ground water tables in the north; cropping of fallow areas in the south; effect of sea level rise; increased cropping intensity; and larger share of cash crops) and three levels of Yg closure (1: no yield increase; 2: Yg closure at a level equivalent to 50% (50% Yg closure); 3: Yg closure to a level of 85% of Yp (irrigated crops) and 80% of water-limited yield potential or Yw (rainfed crops) (full Yg closure)). In addition, changes in demand with low and high population growth rates, and substitution of rice by maize in future diets were also examined. Total aggregated demand of the three cereals (in milled rice equivalents) in 2030 and 2050, based on the UN median population variant, is projected to be 21 and 24% higher than in 2010. Current Yg represent 50% (irrigated rice), 48–63% (rainfed rice), 49% (irrigated wheat), 40% (rainfed wheat), 46% (irrigated maize), and 44% (rainfed maize) of their Yp or Yw.With 50% Yg closure and for various land use changes, self-sufficiency ratio will be N1 for rice in 2030 and about one in 2050 but well below one for maize and wheat in both 2030 and 2050. With full Yg closure, self-sufficiency ratios will be well above one for rice and all three cereals jointly but below one for maize and wheat for all scenarios, except for the scenario with drastic decrease in boro rice area to allow for area expansion for cash crops. Full Yg closure of all cereals is needed to compensate for area decreases and demand increases, and then even some maize and large amounts of wheat imports will be required to satisfy demand in future. The results of this analysis have important implications for Bangladesh and other countries with high population growth rate, shrinking arable land due to rapid urbanization, and highly vulnerable to climate change

Integrating agri-environmental indicators, ecosystem services assessment, life cycle assessment and yield gap analysis to assess the environmental sustainability of agriculture

Agriculture's primary function is the production of food, feed, fibre and fuel for the fast-growing world population. However, it also affects human health and ecosystem integrity. Policymakers make policies in order to avoid harmful impacts. How to assess such policies is a challenge. In this paper, we propose a conceptual framework to help evaluate the impacts of agricultural policies on the environment. Our framework represents the global system as four subsystems and their interactions. These four components are the cells of a 2 by 2 matrix [Agriculture, Rest of the word]; [Socio-eco system, Ecological system]. We then developed a set of indicators for environmental issues and positioned these issues in the framework. To assess these issues, we used four well-known existing approaches: Life Cycle Assessment, Ecosystem Services Analysis, Yield Gap Analysis and Agro-Environmental Indicators. Using these four approaches together provided a more holistic view of the impacts of a given policy on the system. We then applied our framework on existing cover crop policies using an extensive literature survey and analysing the different environmental issues mobilised by the four assessment approaches. This demonstration case shows that our framework may be of help for a full systemic assessment. Despite their differences (aims, scales, standardization, data requirements, etc.), it is possible and profitable to use the four approaches together. This is a significant step forward, though more work is needed to produce a genuinely operational tool. © 2022 The Author