Effects of Soil Variability and Weather Conditions on Pesticide Leaching— A Farm-Level Evaluation

2002 ◽  
Vol 31 (3) ◽  
pp. 797 ◽  
Author(s):  
B. J. van Alphen ◽  
J. J. Stoorvogel
2013 ◽  
Vol 152 (2) ◽  
pp. 288-308 ◽  
Author(s):  
A. K. JONES ◽  
D. L. JONES ◽  
P. CROSS

SUMMARYLivestock production is a significant source of methane (CH4) and nitrous oxide (N2O) emissions globally. In any sheep-producing nation, an effective agricultural greenhouse gas (GHG) mitigation strategy must include sheep-targeted interventions. The most prominent interventions suited to sheep systems are reviewed in the current paper, with a focus on farm-level enteric CH4and soil N2O emissions. A small number of currently available interventions emerge which have broad consensus on their mitigation potential. These include breeding to increase lambing percentages and diet formulation to minimize nitrogen excretion. The majority of interventions still require significant research and development before deployment. Research into the efficacy of interventions such as incorporation of biochar is in its infancy, while for others such as dietary supplements, successes in isolated studies now need to be replicated in long-term field trials under a range of conditions. Enhancing understanding of underlying biological processes will allow capitalization of interventions such as vaccination against rumen methanogenesis and pasture drainage. Many interventions cannot be recommended at a regional or national scale because, either, their mitigation potential is inextricably linked to soil and weather conditions in the locality of use, or their use is restricted to more intensive, closely managed systems. Distilling the long list of interventions to produce an effective farm-level mitigation strategy must involve: accounting for all GHG fluxes and interactions, identifying complimentary sets of additive interventions, and accounting for baseline emissions and current practice. Tools such as whole farm GHG models and marginal abatement cost curves are crucial in the development of tailored, practical sheep farm GHG mitigation strategies.


2018 ◽  
Vol 10 (9) ◽  
pp. 1464 ◽  
Author(s):  
Carlos Pedraza ◽  
Nicola Clerici ◽  
Cristian Forero ◽  
América Melo ◽  
Diego Navarrete ◽  
...  

Due to the fast deforestation rates in the tropics, multiple international efforts have been launched to reduce deforestation and develop consistent methodologies to assess forest extension and change. Since 2010 Colombia implemented the Mainstream Sustainable Cattle Ranching project with the participation of small farmers in a payment for environmental services (PES) scheme where zero deforestation agreements are signed. To assess the fulfillment of such agreements at farm level, ALOS-1 and ALOS-2 PALSAR fine beam dual imagery for years 2010 and 2016 was processed with ad-hoc routines to estimate stable forest, deforestation, and stable nonforest extension for 2615 participant farms in five heterogeneous regions of Colombia. Landsat VNIR imagery was integrated in the processing chain to reduce classification uncertainties due to radar limitations. Farms associated with Meta Foothills regions showed zero deforestation during the period analyzed (2010–2016), while other regions showed low deforestation rates with the exception of the Cesar River Valley (75 ha). Results, suggests that topography and dry weather conditions have an effect on radar-based mapping accuracy, i.e., deforestation and forest classes showed lower user accuracy values on mountainous and dry regions revealing overestimations in these environments. Nevertheless, overall ALOS Phased Array L-band SAR (PALSAR) data provided overall accurate, relevant, and consistent information for forest change analysis for local zero deforestation agreements assessment. Improvements to preprocessing routines and integration of high dense radar time series should be further investigated to reduce classification errors from complex topography conditions.


2021 ◽  
Vol 37 (4) ◽  
pp. 691-700
Author(s):  
Thiago Borba Onofre ◽  
Clyde W Fraisse ◽  
Janise McNair ◽  
Jasmeet Judge ◽  
Lincoln Zotarelli ◽  
...  

Highlights We present an Internet of Things (IoT) platform to monitor site-specific weather conditions at the farm level. We built a distributed mesh network of sensor nodes using open-source and open-hardware tools. We tested different communication range scenarios and installation setups. Emerging IoT technologies are susceptible to failure but have the potential to improve site-specific data collection. Abstract . This article describes the design, deployment, and evaluation of an Internet of Things (IoT) platform to monitor site-specific weather conditions at the farm level using wireless sensor networks (WSN). A distributed mesh network of sensor nodes was developed using open-source software and hardware tools to monitor temperature and relative humidity in-field environmental conditions. The IoT prototype was tested at the University of Florida’s research farm. Data from the sensor nodes were compared to a Florida Automated Weather Network weather station. The results of this study will contribute to the implementation of site-specific collection tools and with site-specific decision management in specialty crop production systems. A significant advantage of IoT and WSN over a standalone weather station is the capability to monitor micro-weather conditions that may lead to site-specific management operations. Keywords: Affordable, Farm, Internet of Things, Mesh Network, Prototype, Wireless Sensor Network.


Agronomie ◽  
2003 ◽  
Vol 23 (1) ◽  
pp. 75-84 ◽  
Author(s):  
Andy Hart ◽  
Colin D. Brown ◽  
Kathy A. Lewis ◽  
John Tzilivakis

Author(s):  
Gregory W. Characklis ◽  
Mackenzie J. Dilts ◽  
Otto D. Simmons ◽  
Leigh-Anne H. Krometis ◽  
Christina Likirdopulos ◽  
...  

2020 ◽  
pp. 67-78
Author(s):  
Nandan Kumar ◽  
Sainath Shrikant Pawaskar

Flash fire caused by electric arc is different than that caused by flammable liquids/fumes or combustible dusts. A suitable protective clothing for protection against electric arc-flash must be designed as per Indian weather conditions. Currently available garments are manufactured using two or three layers of woven/nonwoven combinations to achieve higher Hazard Risk Category (HRC) rating (level 3 and above). However, they are heavy and not comfortable to the end users. Savesplash® is a single layer inherent flame-retardant knitted fabric. Its arc rating was determined using ASTM standards. It achieved arc thermal performance value (ATPV) of 41 cal/cm2, breakopen threshold energy (E_BT) of 42 cal/cm2 and heat attenuation factor (HAF) of 94% when tested as per ASTM F1959/F1959M-14 which translated into an arc rating of 41 cal/cm2. This is equivalent to HRC level 4 ratings as per National Fire Protection Association’s NFPA 70E standard (USA). Further, cut and sewn gloves (HM-100) developed using Savesplash® fabric reinforced with leather on palm area achieved ATPV of 63 cal/cm2 and HAF of 94.5% when tested as per ASTM F2675/F2675M-13.


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