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Methodological Aspects of On-Farm Monitoring of Cropping Systems Management for Sustainability Assessments
No full textTo conduct agro-environmental assessments at field and farm scale, detailed management data of crop and animal production systems are needed. However, this type of data is only rarely collected by public administrations. In the period 2005-2006, we made an experience of on-farm monitoring of cropping systems management, within a larger project aimed at assessing sustainability of agricultural systems in Italian Parks. In this paper, we describe and discuss the steps taken to carry out periodic face-to-face interviews in farms in the Sud Milano Agricultural Park (northern Italy). The first step was the selection of seven farms, which we identified by applying cluster analysis at a large database describing 733 farms of the Park. After having identified the most relevant agro-environmental issues in the studied area, we established a list of simple but sound indicators to evaluate the effects of agricultural management on the environment. The criteria used to select the indicators were that they should: be calculated on easily available data, not be based on direct measurements, make a synthesis of different aspects of reality, and be easily calculated and understood. The indicators selected evaluate nutrient management, fossil energy use, pesticide toxicity, soil management, and economic performance. Subsequently, we designed a data model to store input data used to calculate the indicators (farm configuration, flows of materials and money through the farm gate, animals and their rations, history of crop cultivation, crop management). The data model that we obtained is relatively complex, but adequate to store and analyse the large amount of data acquired during the two-year project. A questionnaire was developed to fully comply with the indicators selected and the data model. The questionnaire was used to carry out approximately six interviews per farm each year, with an investment of time of 1-2 hours per interview. Appropriate double checks of data collected in the interviews were put in place to ensure a good data quality. The data collected were used for the calculation of several agro-ecological indicators. The results show that nutrient management in maize is not satisfactory due to high surpluses, while meadows have the lowest surplus. The fertilisers and diesel consumption are the most important energy inputs to maize, while their importance is lower for the other crops. Seeds and fertilisers are the main costs for maize and winter cereals, while diesel consumption represents a large part of the economic costs for meadows; pesticides are the principal costs in rice. We concluded by identifying steps for further research
On-farm monitoring of economic and environmental performances of cropping systems: Results of a 2-year study at the field scale in northern Italy
No full textCropping systems in northern Italy are intensively managed, but an integrated environmental accounting of these systems has not been published yet. We conducted this study to evaluate cropping systems management in a study area in northern Italy using indicators. The study area is a regional agricultural Park, with cereal and livestock farms, cultivating mostly maize, rice, meadows, and winter cereals.
To select the indicators, we identified for the study area the most relevant issues concerning the potential impact of agriculture on the environment: nutrient and pesticide management, use of fossil energy and soil management. Subsequently, we selected indicators from the literature, which could address these issues. We also added indicators describing the economic performance. The data were collected at the field level by periodic face-to-face interviews with seven farm managers over 2 years. Indicators were calculated for all crops cultivated in each field (n = 266).
According to the methodology proposed, the best economic performance (gross margin) was obtained by rice, followed by maize, winter cereals, and forage crops. Nitrogen and phosphorus surpluses were high for maize (due to a large use of animal manures), and moderate for rice and permanent meadows (where mineral fertilisers are not usually applied). Maize used high fossil energy inputs; however, the output/input ratio (an indicator of the dependence of food and feed production on non-renewable energy) was elevated, due to high aboveground biomass production. The potential impact due to pesticide use (evaluated with indicators that consider the toxicity and the exposure to active ingredients) was relevant only for rice, moderate for maize and other cereals, and null for forages. Finally, soil management was evaluated for the 2-year crop succession on each field (n = 131): permanent meadows are excellent (due to continuous soil cover and large returns of organic carbon to soil), rice-based successions are unsatisfactory (due to low residues and manure application and continuous cropping), and maize successions are intermediate. This work shows that good quality data can be collected on-farm for economic and environmental accounting at field level. The indicators chosen for the analysis describe a range of issues in the study area, and make it possible to clearly separate and characterise different cropping systems. The procedure for their calculation is transparent and sound, and can be applied for ex-ante, ex-post, and monitoring procedures
Integrated sustainability assessment of cropping systems with agro-ecological and economic indicators in northern Italy
No full textThe sustainability of agricultural systems is frequently evaluated with indicators, which are synthetic variables describing complex systems. Each indicator deals with one aspect of sustainability (e.g. nutrients, pesticides, energy), and therefore the result of a complete assessment usually includes several indicator values. These values are frequently presented separately, while an integrated evaluation could benefit from the calculation of a single sustainability index. The aim of this work was to integrate 15 economic and environmental indicator values into a global sustainability index (Sg) ranging from 0 to 1.
To calculate the indicators, we used a large data set of cropping systems management for 131 fields cultivated with arable crops in northern Italy, obtained through periodic interviews with farmers over a 2-year period. The fields were chosen to represent the main cropping systems in the area (cereals and forages, on animal and cereal farms). The 15 indicators describe a large variety of sustainability aspects, i.e. the economic performance and the management of energy, nutrients, soil, and pesticides.
The indicator values were first converted into a sustainability score (Si; 0-1) applying continuous non-linear sustainability functions that use thresholds defining what is sustainable, unsustainable, or intermediate. We obtained 15 values of Si per each field, which we aggregated into Sg using indicator-specific weights provided by different stakeholders. This procedure permits not only the single indicators evaluation, but also to combine indicators for an assessment of cropping systems at field level.
Permanent meadows, due to good management of soil, pesticides and nutrients, obtained the highest Sg, even when different weights were used. Continuous rice obtained the lowest Sg (due to unsatisfactory soil management, low energy production, and high pest and weed pressure, which involved a large use of pesticides), while maize was intermediate, with good economic and energetic performance.
The methodology allows a transparent, repeatable, sound, and quantitative evaluation of sustainability of agricultural systems. It can be easily expanded by adding other indicators, and can be tailored by changing the thresholds used to calculate Si and the weights assigned by stakeholder groups
Energy, Nutrient and Economic Cross Indicators of Cropping Systems in Northern Italy
Full text linkAgro-ecological indicators are useful tools to provide synthetic representations of agricultural systems. Simple indicators can be combined to calculate cross indicators, for example efficiencies, calculated as a ratio between two simple indicators. In sustainability studies, efficiency is frequently calculated in energy terms (energy output / energy input); however, other “output” and “input” terms can be used. In this study, we evaluated how the ranking of systems changes when different metrics of agricultural production (economic gross margin vs. energy output) and resource use (nutrients inputs and surpluses, fossil energy inputs, economic costs) are used. The calculations were carried out for a study area in northern Italy (Sud Milano Agricultural Park), characterised by intensively cultivated arable cropping systems (cereals and forage crops). Crop types were ranked differently when metrics changed. In general, maize (a highly productive crop) had good performances when evaluated using the output / input energy ratio, while rice was good when we used the ratios based on gross margin. When energy or monetary outputs were divided by N surplus, all crop types had very similar median values, suggesting a common energetic and economic efficiency of N use. Overall, different cross indicators may provide a different representation of the system studied. This means that it is not possible to provide a unique synthetic evaluation of sustainability, which instead depends on the indicator(s) chosen.We conclude that it is very important to clarify the objective of sustainability studies and to select accordingly the most adequate indicators
Agro-ecological indicators of field-farming systems sustainability : 2. Nutrients and pesticides
No full textEvaluation of cropping and farming sustainability can be carried out with direct measurements, simulation models or indicators
the latter have the advantage of requiring a small amount of inputs, being fast to calculate and easy to interpret, allowing
comparisons in space and time, and representing a synthesis of processes in complex systems. In a previous paper,
we proposed a list of indicators related to the use of fossil energy and landscape and soil management. In this paper, we
discuss indicators related to the use of nutrients and pesticides. We selected indicators that can be applied on a field and
farm scale, based on data obtainable from the farmer and/or from existing agricultural databases; we excluded indicators
based on direct measurements.
A nutrient balance is the difference between inputs and outputs of a farm or field (surplus if positive, deficit if negative). Its
advantage is its simplicity, the relatively small data requirement, the identification of different inputs, and its applicability
to different mineral elements. However, nutrient balances do not indicate how much surplus can actually be lost from the
system and in which way. The water quality risk indicator integrates the surplus calculated at field level with simple climatic
and pedological information. We also describe two nitrogen management indicators that have been proposed for arable
crops and grasslands to overcome the limitations of nutrient balances, and the phosphorus management (P) indicator,
which compares the applied P amount with the recommended dose, identifying the risks of spoiling non–renewable resources
or depleting soil reserves.
Compared to nutrients, the use of risk indicators for pesticides is more problematic. As a matter of fact, pesticides show a
greater variety of potential effects on human health and on different ecosystems; consequently, the analysis of their potential
risk requires very complex and varied procedures depending on the environmental compartment considered (ground
water, surface water, air and soil). This has led to the development of several pesticide risk indicators that differ greatly in
terms of variables considered, field of activity, scale of analysis and methodologies utilized (interactive decision–tree, risk
ratio approach, scoring table, fuzzy system). Some indicators use simple algorithms to estimate the risk, others make use of
more complicated models. The simplest and generic indicators require very few data (such as the application rate), but in
general they do not consider the fate on the environment and the distribution of the chemicals. On the contrary, more complex
indicators require the use of predictive models to evaluate potential exposure of non target organisms to different active
ingredients. We present some pesticide risk indicators with different levels of complexity that can be utilized at farm
and field level, in order to obtain a picture of the different approaches available in literature and to point out their values
and limitations
Environmental and economic assessment of agricultural systems at crop, field, farm, and regional scale : Application of agro-ecological and economic indicators in northern Italy
Full text linkCastoldi, N, 2007. Environmental and economic assessment of agricultural systems at crop, field, farm, and regional scale. Application of agro-ecological and economic indicators in Northern Italy. Ph.D. Thesis, University of Milan, Italy, 335 pp, 25 figures, 45 tables, 243 references, 4 annexes.
In the last decades, the perception of relations between agriculture and environment has remarkably changed and concerns have been raised about the sustainability of agricultural production systems, involving consumers, citizens, policy makers and farmers.
As direct measurements are too expensive and time consuming, agricultural indicator should be applied for the evaluation of a large number of farms, because they are based on data already available or easy to collect.
In this work, agro-ecological and economic indicators were selected and applied at different scale (crop, field, farm, and regional) using data available in public agricultural databases or collected by farmer interviews. Indicators synthesize the management effects on the environment and the state of the farming system.
In order to evaluate the effectiveness of the tool used, the uncertainty of a single input variable was tested to quantify the corresponding uncertainty of the indicator
Valutazione dei consumi energetici e delle produzioni di "baby leaves" per la quarta gamma
No full text
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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