Aerial Remote Sensing in Agriculture: A Practical Approach to Area Coverage and Path Planning for Fleets of Mini Aerial Robots

In this paper, a system that allows applying precision agriculture techniques is described. The application is based on the deployment of a team of unmanned aerial vehicles that are able to take georeferenced pictures in order to create a full map by applying mosaicking procedures for postprocessing. The main contribution of this work is practical experimentation with an integrated tool. Contributions in different fields are also reported. Among them is a new one-phase automatic task partitioning manager, which is based on negotiation among the aerial vehicles, considering their state and capabilities. Once the individual tasks are assigned, an optimal path planning algorithm is in charge of determining the best path for each vehicle to follow. Also, a robust flight control based on the use of a control law that improves the maneuverability of the quadrotors has been designed. A set of field tests was performed in order to analyze all the capabilities of the system, from task negotiations to final performance. These experiments also allowed testing control robustness under different weather conditions.

Drivers in adopting adaptation strategies to face increased water scarcity in agriculture. A case study in Doñana (Spain) and Makueni (Kenya)

La agricultura es uno de los sectores más afectados por el cambio climático. A pesar de haber demostrado a lo largo de la historia una gran capacidad para adaptarse a nuevas situaciones, hoy en día la agricultura se enfrenta a nuevos retos tales como satisfacer un elevado crecimiento en la demanda de alimentos, desarrollar una agricultura sostenible con el medio ambiente y reducir las emisiones de gases de efecto invernadero. El potencial de adaptación debe ser definido en un contexto que incluya el comportamiento humano, ya que éste juega un papel decisivo en la implementación final de las medidas. Por este motivo, y para desarrollar correctamente políticas que busquen influir en el comportamiento de los agricultores para fomentar la adaptación a estas nuevas condiciones, es necesario entender previamente los procesos de toma de decisiones a nivel individual o de explotación, así como los efectos de los factores que determinan las barreras o motivaciones de la implementación de medidas. Esta Tesis doctoral trata de profundizar en el análisis de factores que influyen en la toma de decisiones de los agricultores para adoptar estrategias de adaptación al cambio climático. Este trabajo revisa la literatura actual y desarrolla un marco metodológico a nivel local y regional. Dos casos de estudio a nivel local (Doñana, España y Makueni, Kenia) han sido llevados a cabo con el fin de explorar el comportamiento de los agricultores hacia la adaptación. Estos casos de estudio representan regiones con notables diferencias en climatología, impactos del cambio climático, barreras para la adaptación y niveles de desarrollo e influencia de las instituciones públicas y privadas en la agricultura. Mientras el caso de estudio de Doñana representa un ejemplo de problemas asociados al uso y escasez del agua donde se espera que se agraven en el futuro, el caso de estudio de Makueni ejemplifica una zona fuertemente amenazada por las predicciones de cambio climático, donde adicionalmente la falta de infraestructura y la tecnología juegan un papel crucial para la implementación de la adaptación. El caso de estudio a nivel regional trata de generalizar en África el comportamiento de los agricultores sobre la implementación de medidas. El marco metodológico que se ha seguido en este trabajo abarca una amplia gama de enfoques y métodos para la recolección y análisis de datos. Los métodos utilizados para la toma de datos incluyen la implementación de encuestas, entrevistas, talleres con grupos de interés, grupos focales de discusión, revisión de estudios previos y bases de datos públicas. Los métodos analíticos incluyen métodos estadísticos, análisis multi‐criterio para la toma de decisiones, modelos de optimización de uso del suelo y un índice compuesto calculado a través de indicadores. Los métodos estadísticos se han utilizado con el fin de evaluar la influencia de los factores socio‐económicos y psicológicos sobre la adopción de medidas de adaptación. Dentro de estos métodos se incluyen regresiones logísticas, análisis de componentes principales y modelos de ecuaciones estructurales. Mientras que el análisis multi‐criterio se ha utilizado con el fin de evaluar las opciones de adaptación de acuerdo a las opiniones de las diferentes partes interesadas, el modelo de optimización ha tenido como fin analizar la combinación óptima de medidas de adaptación. El índice compuesto se ha utilizado para evaluar a nivel regional la implementación de medidas de adaptación en África. En general, los resultados del estudio ponen de relieve la gran importancia de considerar diferentes escalas espaciales a la hora de evaluar la implementación de medidas de adaptación al cambio climático. El comportamiento de los agricultores es diferente entre lugares considerados a una escala local relativamente pequeña, por lo que la generalización de los patrones del comportamiento a escalas regionales o globales resulta relativamente compleja. Los resultados obtenidos han permitido identificar factores determinantes tanto socioeconómicos como psicológicos y calcular su efecto sobre la adopción de medidas de adaptación. Además han proporcionado una mejor comprensión del distinto papel que desempeñan los cinco tipos de capital (natural, físico, financiero, social y humano) en la implementación de estrategias de adaptación. Con este trabajo se proporciona información de gran interés en los procesos de desarrollo de políticas destinadas a mejorar el apoyo de la sociedad a tomar medidas contra el cambio climático. Por último, en el análisis a nivel regional se desarrolla un índice compuesto que muestra la probabilidad de adoptar medidas de adaptación en las regiones de África y se analizan las causas que determinan dicha probabilidad de adopción de medidas. ABSTRACT Agriculture is and will continue to be one of the sectors most affected by climate change. Despite having demonstrated throughout history a great ability to adapt, agriculture today faces new challenges such as meeting growing food demands, developing sustainable agriculture and reducing greenhouse gas emissions. Adaptation policies planned on global, regional or local scales are ultimately implemented in decision‐making processes at the farm or individual level so adaptation potentials have to be set within the context of individual behaviour and regional institutions. Policy instruments can play a formative role in the adoption of such policies by addressing incentives/disincentives that influence farmer’s behaviour. Hence understanding farm‐level decision‐making processes and the influence of determinants of adoption is crucial when designing policies aimed at fostering adoption. This thesis seeks to analyse the factors that influence decision‐making by farmers in relation to the uptake of adaptation options. This work reviews the current knowledge and develops a methodological framework at local and regional level. Whilst the case studies at the local level are conducted with the purpose of exploring farmer’s behaviour towards adaptation the case study at the regional level attempts to up‐scale and generalise theory on adoption of farmlevel adaptation options. The two case studies at the local level (Doñana, Spain and Makueni, Kenya) encompass areas with different; climates, impacts of climate change, adaptation constraints and limits, levels of development, institutional support for agriculture and influence from public and private institutions. Whilst the Doñana Case Study represents an area plagued with water‐usage issues, set to be aggravated further by climate change, Makueni Case study exemplifies an area decidedly threatened by climate change where a lack of infrastructure and technology plays a crucial role in the uptake of adaptation options. The proposed framework is based on a wide range of approaches for collecting and analysing data. The approaches used for data collection include the implementation of surveys, interviews, stakeholder workshops, focus group discussions, a review of previous case studies, and public databases. The analytical methods include statistical approaches, multi criteria analysis for decision‐making, land use optimisation models, and a composite index based on public databases. Statistical approaches are used to assess the influence of socio‐economic and psychological factors on the adoption or support for adaptation measures. The statistical approaches used are logistic regressions, principal component analysis and structural equation modelling. Whilst a multi criteria analysis approach is used to evaluate adaptation options according to the different perspectives of stakeholders, the optimisation model analyses the optimal combination of adaptation options. The composite index is developed to assess adoption of adaptation measures in Africa. Overall, the results of the study highlight the importance of considering various scales when assessing adoption of adaptation measures to climate change. As farmer’s behaviour varies at a local scale there is elevated complexity when generalising behavioural patterns for farmers at regional or global scales. The results identify and estimate the effect of most relevant socioeconomic and psychological factors that influence adoption of adaptation measures to climate change. They also provide a better understanding of the role of the five types of capital (natural, physical, financial, social, and human) on the uptake of farm‐level adaptation options. These assessments of determinants help to explain adoption of climate change measures and provide helpful information in order to design polices aimed at enhancing societal support for adaptation policies. Finally the analysis at the regional level develops a composite index which suggests the likelihood of the regions in Africa to adopt farm‐level adaptation measures and analyses the main causes of this likelihood of adoption.

Climate Change, Water Scarcity in Agriculture and The Country-Level Economic Impacts. A Multimarket Analysis

Climate Change, Water Scarcity in Agriculture and the Country-Level Economic Impacts. A Multimarket Analysis. Abstract: Agriculture could be one of the most vulnerable economic sectors to the impacts of climate change in the coming decades. Considering the critical role that water plays for agricultural production, any shock in water availability will have great implications for agricultural production, land allocation, and agricultural prices. In this paper, an Agricultural Multimarket model is developed to analyze climate change impacts in developing countries, accounting for the uncertainty associated with the impacts of climate change. The model has a structure flexible enough to represent local conditions, resource availability, and market conditions. The results suggest different economic consequences of climate change depending on the specific activity, with many distributional effects across regions

Effect of nano-Si2O and nano-Al2O3 on cement mortars for use in agriculture and livestock production

The effect of nano-silica, nano-alumina and binary combinations on surface hardness, resistance to abrasion and freeze-thaw cycle resistance in cement mortars was investigated. The Vickers hardness, the Los Angeles coefficient (LA) and the loss of mass in each of the freeze–thaw cycles to which the samples were subjected were measured. Four cement mortars CEM I 52.5R were prepared, one as control, and the other three with the additions: 5% nano-Si, 5% nano-Al and mix 2.5% n-Si and 2.5% n-Al. Mortars were tested at 7, 28 and 90 d of curing to determine compression strength, total porosity and pore distribution by mercury intrusion porosimetry (MIP) and the relationship between the CSH gel and Portlandite total by thermal gravimetric analysis (TGA). The capillary suction coefficient and an analysis by a scanning electron microscope (SEM) was made. There was a large increase in Vickers surface hardness for 5% n-Si mortar and a slight increase in resistance to abrasion. No significant difference was found between the mortars with nano-particles, whose LA was about 10.8, classifying them as materials with good resistance to abrasion. The microstructure shows that the addition of n-Si in mortars refines their porous matrix, increases the amount of hydrated gels and generates significant changes in both Portlandite and Ettringite. This produced a significant improvement in freeze–thaw cycle resistance. The effect of n-Al on mortar was null or negative with respect to freeze–thaw cycle resistance.

Molecular basis of salt tolerance in Physcomitrella Patens model plant: potassium homeostasis and physiological roles of chx transporters

El suelo salino impone un estrés abiótico importante que causa graves problemas en la agricultura ya que la mayoría de los cultivos se ven afectados por la salinidad debido a efectos osmóticos y tóxicos. Por ello, la contaminación y la escasez de agua dulce, la salinización progresiva de tierras y el aumento exponencial de la población humana representan un grave problema que amenaza la seguridad alimentaria mundial para las generaciones futuras. Por lo tanto, aumentar la tolerancia a la salinidad de los cultivos es un objetivo estratégico e ineludible para garantizar el suministro de alimentos en el futuro. Mantener una óptima homeostasis de K+ en plantas que sufren estrés salino es un objetivo importante en el proceso de obtención de plantas tolerantes a la salinidad. Aunque el modelo de la homeostasis de K+ en las plantas está razonablemente bien descrito en términos de entrada de K+, muy poco se sabe acerca de los genes implicados en la salida de K+ o de su liberación desde la vacuola. En este trabajo se pretende aclarar algunos de los mecanismos implicados en la homeostasis de K+ en plantas. Para ello se eligió la briofita Physcomitrella patens, una planta no vascular de estructura simple y de fase haploide dominante que, entre muchas otras cualidades, hacen que sea un modelo ideal. Lo más importante es que no sólo P. patens es muy tolerante a altas concentraciones de Na+, sino que también su posición filogenética en la evolución de las plantas abre la posibilidad de estudiar los cambios claves que, durante el curso de la evolución, se produjeron en las diversas familias de los transportadores de K+. Se han propuesto varios transportadores de cationes como candidatos que podrían tener un papel en la salida de K+ o su liberación desde la vacuola, especialmente miembros de la familia CPA2 que contienen las familias de transportadores KEA y CHX. En este estudio se intenta aumentar nuestra comprensión de las funciones de los transportadores de CHX en las células de las plantas usando P. patens, como ya se ha dicho. En esta especie, se han identificado cuatro genes CHX, PpCHX1-4. Dos de estos genes, PpCHX1 y PpCHX2, se expresan aproximadamente al mismo nivel que el gen PpACT5, y los otros dos genes muestran una expresión muy baja. La expresión de PpCHX1 y PpCHX2 en mutantes de Escherichia coli defectivos en el transporte de K+ restauraron el crecimiento de esta cepa en medios con bajo contenido de K+, lo que viii sugiere que la entrada de K+ es energizada por un mecanismo de simporte con H+. Por otra parte, estos transportadores suprimieron el defecto asociado a la mutación kha1 en Saccharomyces cerevisiae, lo que sugiere que podrían mediar un antiporte en K+/H+. La proteína PpCHX1-GFP expresada transitoriamente en protoplastos de P. patens co-localizó con un marcador de Golgi. En experimentos similares, la proteína PpCHX2-GFP localizó aparentemente en la membrana plasmática y tonoplasto. Se construyeron las líneas mutantes simples de P. patens ΔPpchx1 y ΔPpchx2, y también el mutante doble ΔPpchx2 ΔPphak1. Los mutantes simples crecieron normalmente en todas las condiciones ensayadas y mostraron flujos de entrada normales de K+ y Rb+; la mutación ΔPpchx2 no aumentó el defecto de las plantas ΔPphak1. En experimentos a largo plazo, las plantas ΔPpchx2 mostraron una retención de Rb+ ligeramente superior que las plantas silvestres, lo que sugiere que PpCHX2 promueve la transferencia de Rb+ desde la vacuola al citosol o desde el citosol al medio externo, actuando en paralelo con otros transportadores. Sugerimos que transportadores de K+ de varias familias están involucrados en la homeostasis de pH de orgánulos ya sea mediante antiporte K+/H+ o simporte K+-H+.ix ABSTRACT Soil salinity is a major abiotic stress causing serious problems in agriculture as most crops are affected by it. Moreover, the contamination and shortage of freshwater, progressive land salinization and exponential increase of human population aggravates the problem implying that world food security may not be ensured for the next generations. Thus, a strategic and an unavoidable goal would be increasing salinity tolerance of plant crops to secure future food supply. Maintaining an optimum K+ homeostasis in plants under salinity stress is an important trait to pursue in the process of engineering salt tolerant plants. Although the model of K+ homeostasis in plants is reasonably well described in terms of K+ influx, very little is known about the genes implicated in K+ efflux or release from the vacuole. In this work, we aim to clarify some of the mechanisms involved in K+ homeostasis in plants. For this purpose, we chose the bryophyte plant Physcomitrella patens, a nonvascular plant of simple structure and dominant haploid phase that, among many other characteristics, makes it an ideal model. Most importantly, not only P. patens is very tolerant to high concentrations of Na+, but also its phylogenetic position in land plant evolution opens the possibility to study the key changes that occurred in K+ transporter families during the course of evolution. Several cation transporter candidates have been proposed to have a role in K+ efflux or release from the vacuole especially members of the CPA2 family which contains the KEA and CHX transporter families. We intended in this study to increase our understanding of the functions of CHX transporters in plant cells using P. patens, in which four CHX genes have been identified, PpCHX1-4. Two of these genes, PpCHX1 and PpCHX2, are expressed at approximately the same level as the PpACT5 gene, but the other two genes show an extremely low expression. PpCHX1 and PpCHX2 restored growth of Escherichia coli mutants on low K+-containing media, suggesting they mediated K+ uptake that may be energized by symport with H+. In contrast, these genes suppressed the defect associated to the kha1 mutation in Saccharomyces cerevisiae, which suggest that they might mediate K+/H+ antiport. PpCHX1-GFP protein transiently expressed in P. patens protoplasts co-localized with a Golgi marker. In similar experiments, the PpCHX2-GFP protein appeared to localize to tonoplast and plasma x membrane. We constructed the ΔPpchx1 and ΔPpchx2 single mutant lines, and the ΔPpchx2 ΔPphak1 double mutant. Single mutant plants grew normally under all the conditions tested and exhibited normal K+ and Rb+ influxes; the ΔPpchx2 mutation did not increase the defect of ΔPphak1 plants. In long-term experiments, ΔPpchx2 plants showed a slightly higher Rb+ retention than wild type plants, which suggests that PpCHX2 mediates the transfer of Rb+ from either the vacuole to the cytosol or from the cytosol to the external medium in parallel with other transporters. We suggest that K+ transporters of several families are involved in the pH homeostasis of organelles by mediating either K+/H+ antiport or K+-H+ symport.

An example of integration between en economic and an hydrologic model in the framework of water resource management problems

Growing scarcity, increasing demand and bad management of water resources are causing weighty competition for water and consequently managers are facing more and more pressure in an attempt to satisfy users? requirement. In many regions agriculture is one of the most important users at river basin scale since it concentrates high volumes of water consumption during relatively short periods (irrigation season), with a significant economic, social and environmental impact. The interdisciplinary characteristics of related water resources problems require, as established in the Water Framework Directive 2000/60/EC, an integrated and participative approach to water management and assigns an essential role to economic analysis as a decision support tool. For this reason, a methodology is developed to analyse the economic and environmental implications of water resource management under different scenarios, with a focus on the agricultural sector. This research integrates both economic and hydrologic components in modelling, defining scenarios of water resource management with the goal of preventing critical situations, such as droughts. The model follows the Positive Mathematical Programming (PMP) approach, an innovative methodology successfully used for agricultural policy analysis in the last decade and also applied in several analyses regarding water use in agriculture. This approach has, among others, the very important capability of perfectly calibrating the baseline scenario using a very limited database. However one important disadvantage is its limited capacity to simulate activities non-observed during the reference period but which could be adopted if the scenario changed. To overcome this problem the classical methodology is extended in order to simulate a more realistic farmers? response to new agricultural policies or modified water availability. In this way an economic model has been developed to reproduce the farmers? behaviour within two irrigation districts in the Tiber High Valley. This economic model is then integrated with SIMBAT, an hydrologic model developed for the Tiber basin which allows to simulate the balance between the water volumes available at the Montedoglio dam and the water volumes required by the various irrigation users.

Automatic segmentation of relevant textures in agricultural images

One important issue emerging strongly in agriculture is related with the automatization of tasks, where the optical sensors play an important role. They provide images that must be conveniently processed. The most relevantimage processing procedures require the identification of green plants, in our experiments they come from barley and corn crops including weeds, so that some types of action can be carried out, including site-specific treatments with chemical products or mechanical manipulations. Also the identification of textures belonging to the soil could be useful to know some variables, such as humidity, smoothness or any others. Finally, from the point of view of the autonomous robot navigation, where the robot is equipped with the imaging system, some times it is convenient to know not only the soil information and the plants growing in the soil but also additional information supplied by global references based on specific areas. This implies that the images to be processed contain textures of three main types to be identified: green plants, soil and sky if any. This paper proposes a new automatic approach for segmenting these main textures and also to refine the identification of sub-textures inside the main ones. Concerning the green identification, we propose a new approach that exploits the performance of existing strategies by combining them. The combination takes into account the relevance of the information provided by each strategy based on the intensity variability. This makes an important contribution. The combination of thresholding approaches, for segmenting the soil and the sky, makes the second contribution; finally the adjusting of the supervised fuzzy clustering approach for identifying sub-textures automatically, makes the third finding. The performance of the method allows to verify its viability for automatic tasks in agriculture based on image processing

Real-time image processing for crop/weed discrimination in maize fields

This paper presents a computer vision system that successfully discriminates between weed patches and crop rows under uncontrolled lighting in real-time. The system consists of two independent subsystems, a fast image processing delivering results in real-time (Fast Image Processing, FIP), and a slower and more accurate processing (Robust Crop Row Detection, RCRD) that is used to correct the first subsystem's mistakes. This combination produces a system that achieves very good results under a wide variety of conditions. Tested on several maize videos taken of different fields and during different years, the system successfully detects an average of 95% of weeds and 80% of crops under different illumination, soil humidity and weed/crop growth conditions. Moreover, the system has been shown to produce acceptable results even under very difficult conditions, such as in the presence of dramatic sowing errors or abrupt camera movements. The computer vision system has been developed for integration into a treatment system because the ideal setup for any weed sprayer system would include a tool that could provide information on the weeds and crops present at each point in real-time, while the tractor mounting the spraying bar is moving

Sustainability of irrigated farming systems in a Tunisian region: A recursive stochastic programming analysis

The aim of this study was to evaluate the sustainability of farm irrigation systems in the Cébalat district in northern Tunisia. It addressed the challenging topic of sustainable agriculture through a bio-economic approach linking a biophysical model to an economic optimisation model. A crop growth simulation model (CropSyst) was used to build a database to determine the relationships between agricultural practices, crop yields and environmental effects (salt accumulation in soil and leaching of nitrates) in a context of high climatic variability. The database was then fed into a recursive stochastic model set for a 10-year plan that allowed analysing the effects of cropping patterns on farm income, salt accumulation and nitrate leaching. We assumed that the long-term sustainability of soil productivity might be in conflict with farm profitability in the short-term. Assuming a discount rate of 10% (for the base scenario), the model closely reproduced the current system and allowed to predict the degradation of soil quality due to long-term salt accumulation. The results showed that there was more accumulation of salt in the soil for the base scenario than for the alternative scenario (discount rate of 0%). This result was induced by applying a higher quantity of water per hectare for the alternative as compared to a base scenario. The results also showed that nitrogen leaching is very low for the two discount rates and all climate scenarios. In conclusion, the results show that the difference in farm income between the alternative and base scenarios increases over time to attain 45% after 10 years.

Farm nitrogen balances in six European landscapes as an indicator for nitrogen losses and basis for improved management.

Improved management of nitrogen (N) in agriculture is necessary to achieve a sustainable balance between the production of food and other biomass, and the unwanted effects of N on water pollution, greenhouse gas emissions, biodiversity deterioration and human health. To analyse farm N-losses and the complex interactions within farming systems, efficient methods for identifying emissions hotspots and evaluating mitigation measures are therefore needed. The present paper aims to fill this gap at the farm and landscape scales. Six agricultural landscapes in Poland (PL), the Netherlands (NL), France (FR), Italy (IT), Scotland (UK) and Denmark (DK) were studied, and a common method was developed for undertaking farm inventories and the derivation of farm N balances, N surpluses and for evaluating uncertainty for the 222 farms and 11 440 ha of farmland included in the study. In all landscapes, a large variation in the farm N surplus was found, and thereby a large potential for reductions. The highest average N surpluses were found in the most livestock-intensive landscapes of IT, FR, and NL; on average 202 ± 28, 179 ± 63 and 178 ± 20 kg N ha−1 yr−1, respectively. All landscapes showed hotspots, especially from livestock farms, including a special UK case with large-scale landless poultry farming. Overall, the average N surplus from the land-based UK farms dominated by extensive sheep and cattle grazing was only 31 ± 10 kg N ha−1 yr−1, but was similar to the N surplus of PL and DK (122 ± 20 and 146 ± 55 kg N ha−1 yr−1, respectively) when landless poultry farming was included. We found farm N balances to be a useful indicator for N losses and the potential for improving N management. Significant correlations to N surplus were found, both with ammonia air concentrations and nitrate concentrations in soils and groundwater, measured during the period of N management data collection in the landscapes from 2007–2009. This indicates that farm N surpluses may be used as an independent dataset for validation of measured and modelled N emissions in agricultural landscapes. No significant correlation was found with N measured in surface waters, probably because of spatial and temporal variations in groundwater buffering and biogeochemical reactions affecting N flows from farm to surface waters. A case study of the development in N surplus from the landscape in DK from 1998–2008 showed a 22% reduction related to measures targeted at N emissions from livestock farms. Based on the large differences in N surplus between average N management farms and the most modern and N-efficient farms, it was concluded that additional N-surplus reductions of 25–50%, as compared to the present level, were realistic in all landscapes. The implemented N-surplus method was thus effective for comparing and synthesizing results on farm N emissions and the potentials of mitigation options. It is recommended for use in combination with other methods for the assessment of landscape N emissions and farm N efficiency, including more detailed N source and N sink hotspot mapping, measurements and modelling.

Probabilistic analysis of water availability for agriculture and associated crop net margins.

Rising water demands are difficult to meet in many regions of the world. In consequence, under meteorological adverse conditions, big economic losses in agriculture can take place. This paper aims to analyze the variability of water shortage in an irrigation district and the effect on farmer?s income. A probabilistic analysis of water availability for agriculture in the irrigation district is performed, through a supply-system simulation approach, considering stochastically generated series of stream-flows. Net margins associated to crop production are as well estimated depending on final water allocations. Net margins are calculated considering either single-crop farming, either a polyculture system. In a polyculture system, crop distribution and water redistribution are calculated through an optimization approach using the General Algebraic Modeling System (GAMS) for several scenarios of irrigation water availability. Expected net margins are obtained by crop and for the optimal crop and water distribution. The maximum expected margins are obtained for the optimal crop combination, followed by the alfalfa monoculture, maize, rice, wheat and finally barley. Water is distributed as follows, from biggest to smallest allocation: rice, alfalfa, maize, wheat and barley.

Unbalanced value chain in perishable agricultural products.

Value chain in agriculture is a current issue affecting from farmers to consumers. It questions important issues as profitability, and even though continuity of certain sectors. Although there has been an evolution along time in the structure and concentration of intermediate and final levels of the value chain between distribution and retail sector, a similar evolution seems not to arrive at the initial level of the chain, the production sector. This produces large imbalances in power and leverage between levels of the value chain that could imply several problems for rural actors. Relatively little attention has been paid to possible market distortions caused by the high level of concentration distribution side of the agrifood system.

Discrete element analysis for the assessment of the accuracy of load cell-based dynamic weighing systems in grape harvesters under different ground conditions

Dynamic weighing systems based on load cells are commonly used to estimate crop yields in the field. There is lack of data, however, regarding the accuracy of such weighing systems mounted on harvesting machinery, especially on that used to collect high value crops such as fruits and vegetables. Certainly, dynamic weighing systems mounted on the bins of grape harvesters are affected by the displacement of the load inside the bin when moving over terrain of changing topography. In this work, the load that would be registered in a grape harvester bin by a dynamic weighing system based on the use of a load cell was inferred by using the discrete element method (DEM). DEM is a numerical technique capable of accurately describing the behaviour of granular materials under dynamic situations and it has been proven to provide successful predictions in many different scenarios. In this work, different DEM models of a grape harvester bin were developed contemplating different influencing factors. Results obtained from these models were used to infer the output given by the load cell of a real bin. The mass detected by the load cell when the bin was inclined depended strongly on the distribution of the load within the bin, but was underestimated in all scenarios. The distribution of the load was found to be dependent on the inclination of the bin caused by the topography of the terrain, but also by the history of inclination (inclination rate, presence of static periods, etc.) since the effect of the inertia of the particles (i.e., representing the grapes) was not negligible. Some recommendations are given to try to improve the accuracy of crop load measurement in the field.

Irrigated agriculture: Water resources management for a sustainable environment

In the last decade, research on irrigation has mainly been aimed at reducing crop water consumption. In arid and semi-arid environments, in relation to the limited water resources, the use of low quality water in agriculture has also been investigated in order to detect their effects on soil physical properties and on crop production. More recently, even the reduction of energy consumption in agriculture, as well as the effects of external factors, climate change and agricultural policies, have been major research interests. All these objectives have been considered in the papers included in this special issue. However, in the last years, approaches aimed at reducing crop water requirements have significantly changed. Remote sensing with satellites or unmanned vehicles, and vegetation spectral measurements, among others, represent in fact the newest frontier of existing technologies. Knowledge of soil hydraulic properties, often forgotten because of the difficulty of their estimation, can also be considered as a new way to reduce water consumption.

Effects of a bifenthrin-treated net on the natural enemies Aphidius colemani (Haliday) and Adalia bipunctata L. in a cucumber crop in Central Spain. Semi-field experiments

Pest management practices that rely on pesticides are growing increasingly less effective and environmentally inappropriate in many cases and the search of alternatives is under focus nowadays. Exclusion of pests from the crop by means of pesticide-treated screens can be an eco-friendly method to protect crops, especially if pests are vectors of important diseases. The mesh size of nets is crucial to determine if insects can eventually cross the barrier or exclude them because there is a great variation in insect size depending on the species. Long-lasting insecticide-treated (LLITN) nets, factory pre-treated, have been used since years to fight against mosquitoes vector of malaria and are able to retain their biological efficacy under field for 3 years. In agriculture, treated nets with different insecticides have shown efficacy in controlling some insects and mites, so they seem to be a good tool in helping to solve some pest problems. However, treated nets must be carefully evaluated because can diminish air flow, increase temperature and humidity and decrease light transmission, which may affect plant growth, pests and natural enemies. As biological control is considered a key factor in IPM nowadays, the potential negative effects of treated nets on natural enemies need to be studied carefully. In this work, the effects of a bifentrhin-treated net (3 g/Kg) (supplied by the company Intelligent Insect Control, IIC) on natural enemies of aphids were tested on a cucumber crop in Central Spain in autumn 2011. The crop was sown in 8x6.5 m tunnels divided in 2 sealed compartments with control or treated nets, which were simple yellow netting with 25 mesh (10 x 10 threads/cm2; 1 x 1 mm hole size). Pieces of 2 m high of the treated-net were placed along the lateral sides of one of the two tunnel compartments in each of the 3 available tunnels (replicates); the rest was covered by a commercial untreated net of a similar mesh. The pest, Aphis gossypii Glover (Aphidae), the parasitoid Aphidius colemani (Haliday) (Braconidae) and the predator Adalia bipunctata L. (Coccinellidae) were artificially introduced in the crop. Weekly sampling was done determining the presence or absence of the pest and the natural enemies (NE) in the 42 plants/compartment as well as the number of insects in 11 marked plants. Environmental conditions (temperature, relative humidity, UV and PAR radiation) were recorded. Results show that when aphids were artificially released inside the tunnels, neither its number/plant nor their distribution was affected by the treated net. A lack of negative effect of the insecticide-treated net on natural enemies was also observed. Adalia bipunctata did not establish in the crop and only a short term control of aphids was observed one week after release. On the other hand, A. colemani did establish in the crop and a more long-term effect on the numbers of aphids/plant was detected irrespective of the type of net. KEY WORDS: bifenthrin-treated net, Adalia bipunctata, Aphidius colemani, Aphis gossypii, semi-field