scholarly journals Evaluation of Scenarios for Improving the Collection System for a Milk Factory in Ethiopia

2021 ◽  
Vol 5 ◽  
Author(s):  
Bert Dijkink ◽  
Erik Esveld ◽  
Jan Broeze ◽  
Martijntje Vollebregt
Keyword(s):  
Cooling System ◽  
Ghg Emissions ◽  
Rejection Rate ◽  
Milk Supply ◽  
Smallholder Farms ◽  
Increased Risk ◽  
Reasonable Cost ◽  
Increase Milk Production ◽  
Morning Milk ◽  
Initial Contamination

The milk for a factory in Sululta (Ethiopia) is currently collected at ambient temperature. To increase milk production, the sourcing must be extended. This requires the collection of not only the morning milk but also the evening milk from smallholder farms. To accomplish this, the collection of milk from small farmers has to be improved, whereby the milk quality has to be assured with reasonable cost and environmental impact. A model predicting milk rejection was developed based on initial contamination and time and temperature profiles. With this model, different cooling scenarios we reevaluated regarding the expected effectiveness of reducing the rejection rate during collection. Second, cost estimations were made to implement the scenarios to collect morning and evening milk from smallholder farms. A third criterion was greenhouse gas (GHG) emissions per litre of collected milk. Finally, the feasibility of the scenarios was assessed in terms of technical, practical, and economic aspects. Including both quality and economics, the best scenario can be expected from a cooling centre where farmers bring their milk twice a day, except there are signals that the farmers would not be willing to deliver the evening milk to the centre at night. In that case, an additional collecting system would be needed to increase the milk supply. This would result in higher collection costs and an increased risk of milk rejection at the factory gate. Furthermore, this would reduce the value of the chilling centre, as in that case it would be better to deliver the milk directly to the factory. Both scenarios would increase GHG emissions compared with the current situation. Only the use of an off-grid solar power-driven cooling system at the farms would reduce the GHG emissions. However, this solution is less feasible economically. The applied combination of a simple model, economic analysis and the effect on GHG emissions gives valuable information on the effectiveness and limitations of different cooling scenarios for the milk factory. It can help to successfully apply a scenario for increasing the milk supply.

scholarly journals Pasture species and drought impacts on milk yield 2. Predicted farm milk yield at four sites

1998 ◽  
pp. 45-50 ◽  
Author(s):  
D.J. Barker ◽  
D.A. Clark ◽  
E.R. Thom ◽  
J.N. Couchman ◽  
R.N. Burton ◽  
...  
Keyword(s):  
Water Deficit ◽  
Milk Production ◽  
Milk Yield ◽  
Seasonal Pattern ◽  
System Modelling ◽  
Milk Supply ◽  
Increase Milk Production ◽  
Growth Differences ◽  
Highly Correlated ◽  
Farm System

A desirable option for increasing milk yield per farm is to increase milk production in summer without compromising peak-season production or the duration of lactation. The dairy industry has a goal to achieve a 4% per month post-peak decline of milk production. The effect of five pasture types and two summer water regimes on predicted farm milk yield, in Northland, Waikato, Manawatu and Canterbury was measured over 1 year. Two pasture treatments, resident pasture and Grasslands Nui ryegrass, were common to all sites. A third pasture treatment varied between sites: triple mix (Grasslands Advance tall fescue, Grasslands Kara cocksfoot, and Grasslands Maru phalaris) at the Manawatu site; the same triple mix but with Grasslands Raki paspalum at the Northland site; and low-endophyte ryegrass and Grasslands Kahu timothy (LER) at the Canterbury site; all sown treatments included red and white clover. All five pasture types were included at the Waikato site. On average for all pasture types, water deficit reduced summer herbage accumulation (HA) to 79, 68, 43 and 18% of irrigated controls, and annual HA to 88, 80, 73 and 63% of irrigated controls in Northland, Waikato, Manawatu and Canterbury, respectively. Since farm milk yield predicted by UDDER was highly correlated with annual HA (R2 = 83%), the effects of pasture type and water deficit on milk yield were similar to effects on HA. Seasonal and annual HA differed among the five pasture types at each of the four sites. The most important factor affecting predicted farm milk yield was annual HA, with relatively little effect from the seasonal pattern of pasture growth. Differences in shapes of the predicted milk supply curves for various treatments occurred, particularly when drought forced early drying-off. The best predicted summer milk yield was for the Canterbury irrigated LER pasture treatment, a 6.8% per month postpeak decline of milk production. Keywords: farm milk yield, farm system modelling, forage supply, pasture species, water deficit

How can grass-based dairy farmers reduce the carbon footprint of milk?

2016 ◽  
Vol 56 (3) ◽  
pp. 495 ◽  
Author(s):  
D. O'Brien ◽  
A. Geoghegan ◽  
K. McNamara ◽  
L. Shalloo
Keyword(s):  
Milk Production ◽  
Carbon Footprint ◽  
Economic Value ◽  
Ghg Emissions ◽  
Mitigation Strategies ◽  
Quota System ◽  
Dairy Farmers ◽  
Increase Milk Production ◽  
Fertiliser Use ◽  
Milk Solids

The Irish dairy industry aims to increase milk production from grass-based farms following the removal of the EU milk-quota system, but is also required to minimise greenhouse gas (GHG) emissions to meet European reduction targets. Consequently, the sector is under increasing pressure to reduce GHG emissions per unit of milk, or carbon footprint (CF). Therefore, the goal of the present study was to determine the main sources of the CF of grass-based milk production and to identify mitigation strategies that can be applied to reduce farm footprints. In total, the CF of milk was estimated for 62 grass-based dairy farms in 2014. The method used to quantify GHG emissions was a life cycle assessment (LCA), independently certified to comply with the British standard for LCA (PAS 2050). The LCA method was applied to calculate annual on- and off-farm GHG emissions associated with dairy production until milk was sold from the farm in CO2-equivalent (CO2-eq). Annual GHG emissions computed using LCA were allocated to milk on the basis of the economic value of dairy products and expressed per kilogram of fat- and protein-corrected milk to estimate CF. Enteric methane was the main source of the CF of milk (46%), followed by emissions from inorganic N fertilisers (16%), manure (16%) and concentrate feedstuffs (8%). The mean CF of milk from the 62 farms was 1.26 kg of CO2-eq per kilogram of fat- and protein-corrected milk, but varied from 0.98 kg to 1.67 kg as measured using the 95% confidence interval. The CF of milk was correlated with numerous farm attributes, particularly N-fertiliser, the percentage of grazed grass in the diet, and production of milk solids. Grass-based dairy farmers can significantly improve these farm attributes by increasing herd genetic merit, extending the length of the grazing season and optimising N fertiliser use and, thereby, reduce the CF of milk.

Domperidone Versus Metoclopramide: Self-Reported Side Effects in a Large Sample of Breastfeeding Mothers Who Used These Medications to Increase Milk Production

2018 ◽  
Vol 9 (1) ◽  
pp. 10-17 ◽  
Author(s):  
Thomas W. Hale ◽  
Kathleen Kendall-Tackett ◽  
Zhen Cong
Keyword(s):  
Side Effects ◽  
Milk Production ◽  
Cardiac Arrhythmias ◽  
Online Survey ◽  
Relative Safety ◽  
Increased Risk ◽  
Rare Side Effect ◽  
Increase Milk Production ◽  
The Central Nervous System ◽  
Cns Side Effects

Introduction: Metoclopramide and domperidone are medications that block dopamine receptors on the lactotrophs, allowing prolactin levels to rise. Both medications are prescribed to boost milk production in mothers with low milk production due to hypoprolactinemia. The Food and Drug Administration has not approved the use of domperidone in the U.S. because of concerns about increased risk of cardiac arrhythmias. Metoclopramide is often recommended instead. Unfortunately, metoclopramide affects the central nervous system (CNS) and increases the risk of both depression and tardive dyskinesia (TD).Method: The present study is an online survey of self-reported side effects of 1,990 mothers, representing 25 countries, who took metoclopramide, domperidone, or both medications to enhance milk production. Data were collected in 2010.Results: The results indicated that side effects, in general, affected only a small percentage of women who took either medication. Women were 3.6 times more likely to report no side effects when taking domperidone vs. metoclopramide. There were no significant differences in cardiac arrhythmias for women who took metoclopramide versus domperidone. Racing heart was more common with metoclopramide. Less than 1% reported these symptoms in both groups. However, CNS effects were significantly more common in women who took metoclopramide. Risk of depression increased by seven times, and symptoms of TD (tremors, involuntary grimaces, and jerking) increased by 4 to 19 times when women took metoclopramide.Discussion: The results of the present study are preliminary, but suggest that cardiac arrhythmias are a rare side effect with both medications. The CNS side effects with metoclopramide are more concerning, particularly depression and TD. It is hoped that the recommendations regarding the relative safety of these medications will be re-examined in light of these findings.

scholarly journals Carbon Footprint Assessment of Spanish Dairy Cattle Farms: Effectiveness of Dietary and Farm Management Practices as a Mitigation Strategy

Animals ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. 2083
Author(s):  
Ridha Ibidhi ◽  
Sergio Calsamiglia
Keyword(s):  
Greenhouse Gas ◽  
Carbon Footprint ◽  
Management Practices ◽  
Ghg Emissions ◽  
System Model ◽  
Feeding Strategies ◽  
Management Scenarios ◽  
Dietary Practices ◽  
Enteric Methane ◽  
Increase Milk Production

Greenhouse gas emissions and the carbon footprint (CF) were estimated in twelve Spanish dairy farms selected from three regions (Mediterranean, MED; Cantabric, CAN; and Central, CEN) using a partial life cycle assessment through the Integrated Farm System Model (IFSM). The functional unit was 1 kg of energy corrected milk (ECM). Methane emissions accounted for the largest contribution to the total greenhouse gas (GHG) emissions. The average CF (kg CO2-eq/kg of ECM) was 0.84, being the highest in MED (0.98), intermediate in CEN (0.84), and the lowest in CAN (0.67). Two extreme farms were selected for further simulations: one with the highest non-enteric methane (MED1), and another with the highest enteric methane (CAN2). Changes in management scenarios (increase milk production, change manure collection systems, change manure-type storage method, change bedding type and installation of an anaerobic digester) in MED1 were evaluated with the IFSM model. Changes in feeding strategies (reduce the forage: concentrate ratio, improve forage quality, use of ionophores) in CAN2 were evaluated with the Cornell Net Carbohydrate and Protein System model. Results indicate that changes in management (up to 27.5% reduction) were more efficient than changes in dietary practices (up to 3.5% reduction) in reducing the carbon footprint.

scholarly journals Exploring the Factors Associated with Climate-Related Issues in a Special Economic Development Zone: Application of a DPSIR Framework

2021 ◽  
Vol 16 (8) ◽  
pp. 1529-1540
Author(s):  
Saniwan Buaban ◽  
Vilas Nitivattananon ◽  
Sangam Shrestha ◽  
Sylvia Szabo
Keyword(s):  
Water Scarcity ◽  
Structural Equation ◽  
Sustainability Assessment ◽  
Ghg Emissions ◽  
Climate Change Impacts ◽  
Equation Modeling ◽  
Future Research ◽  
Development Zone ◽  
Dpsir Framework ◽  
Increased Risk

The rapid global increase in Special Economic Zones (SEZs) raises concerns regarding potential impacts on the environment, especially water use intensity, an increased risk of natural disasters, and an elevated greenhouse gas (GHG) emissions. However, studies examining these impacts are limited. Therefore, the aim of this paper is to examine the influence of SEZ development factors on flooding, water scarcity, and GHG emissions using Tak SEZ in Thailand as a case study. A Driver-Pressure-State-Impact-Response (DPSIR) framework, together with structural equation modeling (SEM) through the partial least squares (PLS) approach, has been used to examine the interrelationships between these factors. The results revealed that economic, industrial, and urban development are key drivers associated with flooding, water scarcity, and GHG emissions in the zone. The increased population density, water consumption, waste generation, and vehicular traffic are all significantly put pressure on climate change impacts. The integration of DPSIR framework together with PLS-SEM technique to explore the relationship among multiple sustainability indicators contributes to the existing sustainability assessment methodology. Future research can utilize the presented indicators to identify potential factors for the evaluation of other types of development zones that have a variety of socio-economic activities.

scholarly journals Wellbeing of Breastfeeding Women in Australia and New Zealand during the COVID-19 Pandemic: A Cross-Sectional Study

Nutrients ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 1831
Author(s):  
Vanessa S. Sakalidis ◽  
Alethea Rea ◽  
Sharon L. Perrella ◽  
Jacki McEachran ◽  
Grace Collis ◽  
...  
Keyword(s):  
Mental Health ◽  
New Zealand ◽  
Perceived Stress ◽  
Online Survey ◽  
Mental Wellbeing ◽  
Milk Supply ◽  
Cross Sectional ◽  
Health Concerns ◽  
Increased Risk ◽  
Mental Health Concerns

During the COVID-19 pandemic, breastfeeding women have experienced restricted access to support, placing them at increased risk of mental health concerns and limited breastfeeding assistance. This study investigated the effect of the pandemic on feeding choices and maternal wellbeing amongst breastfeeding mothers living in Australian and New Zealand. We conducted a cross-sectional online survey that examined feeding methods, maternal mental wellbeing, worries, challenges, and positive experiences during the pandemic. Most women were exclusively breastfeeding (82%). Partial breastfeeding was associated with perceived low milk supply and longer pregnancy duration during the pandemic. Reduced mental health and wellbeing was associated with lower levels of family functioning, increased perceived stress, and perinatal anxiety. Longer pregnancy duration during the pandemic was associated with lower mental health wellbeing scores, while higher perceived stress scores were reported for regions with higher COVID-19 infection rates and women with perceived low milk supply. Women reported that the pandemic resulted in less pressure and more time for family bonding, while worries about the pandemic, family health, and parenting challenges were also cited. Mental health concerns of breastfeeding women appear to be exacerbated by COVID-19, highlighting a critical need for access to mental health and broader family support during the pandemic.

scholarly journals Dynamic simulation for optimisation solution of manufacturing processes

2018 ◽  
Vol 244 ◽  
pp. 01010 ◽  
Author(s):  
Vladimíra Schindlerová ◽  
Ivana Šajdlerová ◽  
Dominika Lehocká
Keyword(s):  
Computer Simulations ◽  
Lead Time ◽  
Cooling System ◽  
Industrial Processes ◽  
System Component ◽  
Optimal Parameters ◽  
Industrial Practice ◽  
Increased Risk ◽  
Comparison Of The Results ◽  
The Right

One way how to study the real behaviour of industrial processes or systems in practice is to use computer simulations. We can simulate different conditions and find optimal parameters without increased risk. The right application of these parameters in practice can produce the desired results. The advantage is not only the safe verification of various variants of the simulated parameters, but also the possibility of their use in different areas of industrial practice. This article deals with an example of the use of simulation in the production of the selected automobile cooling system component. The simulation model was created to design the correct number of Kanban circuits to shorten production lead time and to reduce inter-operational supplies. The suitability of using computer simulations to optimize the production processes and systems in practice can be confirmed based on comparison of the results from the computer simulation with results achieved in practice.

scholarly journals Food Loss-Reducing Intervention Strategies for Potato Smallholders in Kenya—A Positive Business Case with Reduced Greenhouse Gas Emissions

Agronomy ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. 1857
Author(s):  
Han Soethoudt ◽  
Bob Castelein
Keyword(s):  
Food Security ◽  
Greenhouse Gas ◽  
Business Models ◽  
Impact Analysis ◽  
Ghg Emissions ◽  
Real Life ◽  
Potato Production ◽  
Business Case ◽  
Agricultural Crop ◽  
Smallholder Farms

This paper is focused on intervention scenarios for smallholder potato value chains in Kenya that improve yields, reduce losses, minimize greenhouse gas (GHG) emissions and increase economic performance and food security. For that, business models and GHG emission estimates are developed, based on the existing data, combined with relevancy and time-to-impact analysis using practical real-life information from stakeholders in the potato sector, which is the second largest agricultural crop in Kenya after maize. The results show that profitability, environmental improvement and food security can go hand in hand with realistic short-term interventions for potato production at smallholder farms.

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