Crop row detection in maize fields inspired on the human visual perception

This paper proposes a new method, oriented to image real-time processing, for identifying crop rows in maize fields in the images. The vision system is designed to be installed onboard a mobile agricultural vehicle, that is, submitted to gyros, vibrations, and undesired movements. The images are captured under image perspective, being affected by the above undesired effects. The image processing consists of two main processes: image segmentation and crop row detection. The first one applies a threshold to separate green plants or pixels (crops and weeds) from the rest (soil, stones, and others). It is based on a fuzzy clustering process, which allows obtaining the threshold to be applied during the normal operation process. The crop row detection applies a method based on image perspective projection that searches for maximum accumulation of segmented green pixels along straight alignments. They determine the expected crop lines in the images. The method is robust enough to work under the above-mentioned undesired effects. It is favorably compared against the well-tested Hough transformation for line detection.

Remote sensing of LAI, chlorophyll and leaf nitrogen pools of crop- and grasslands in five European landscapes.

Leaf nitrogen and leaf surface area influence the exchange of gases between terrestrial ecosystems and the atmosphere, and play a significant role in the global cycles of carbon, nitrogen and water. The purpose of this study is to use field-based and satellite remote-sensing-based methods to assess leaf nitrogen pools in five diverse European agricultural landscapes located in Denmark, Scotland (United Kingdom), Poland, the Netherlands and Italy. REGFLEC (REGularized canopy reFLECtance) is an advanced image-based inverse canopy radiative transfer modelling system which has shown proficiency for regional mapping of leaf area index (LAI) and leaf chlorophyll (CHLl) using remote sensing data. In this study, high spatial resolution (10–20 m) remote sensing images acquired from the multispectral sensors aboard the SPOT (Satellite For Observation of Earth) satellites were used to assess the capability of REGFLEC for mapping spatial variations in LAI, CHLland the relation to leaf nitrogen (Nl) data in five diverse European agricultural landscapes. REGFLEC is based on physical laws and includes an automatic model parameterization scheme which makes the tool independent of field data for model calibration. In this study, REGFLEC performance was evaluated using LAI measurements and non-destructive measurements (using a SPAD meter) of leaf-scale CHLl and Nl concentrations in 93 fields representing crop- and grasslands of the five landscapes. Furthermore, empirical relationships between field measurements (LAI, CHLl and Nl and five spectral vegetation indices (the Normalized Difference Vegetation Index, the Simple Ratio, the Enhanced Vegetation Index-2, the Green Normalized Difference Vegetation Index, and the green chlorophyll index) were used to assess field data coherence and to serve as a comparison basis for assessing REGFLEC model performance. The field measurements showed strong vertical CHLl gradient profiles in 26% of fields which affected REGFLEC performance as well as the relationships between spectral vegetation indices (SVIs) and field measurements. When the range of surface types increased, the REGFLEC results were in better agreement with field data than the empirical SVI regression models. Selecting only homogeneous canopies with uniform CHLl distributions as reference data for evaluation, REGFLEC was able to explain 69% of LAI observations (rmse = 0.76), 46% of measured canopy chlorophyll contents (rmse = 719 mg m−2) and 51% of measured canopy nitrogen contents (rmse = 2.7 g m−2). Better results were obtained for individual landscapes, except for Italy, where REGFLEC performed poorly due to a lack of dense vegetation canopies at the time of satellite recording. Presence of vegetation is needed to parameterize the REGFLEC model. Combining REGFLEC- and SVI-based model results to minimize errors for a "snap-shot" assessment of total leaf nitrogen pools in the five landscapes, results varied from 0.6 to 4.0 t km−2. Differences in leaf nitrogen pools between landscapes are attributed to seasonal variations, extents of agricultural area, species variations, and spatial variations in nutrient availability. In order to facilitate a substantial assessment of variations in Nl pools and their relation to landscape based nitrogen and carbon cycling processes, time series of satellite data are needed. The upcoming Sentinel-2 satellite mission will provide new multiple narrowband data opportunities at high spatio-temporal resolution which are expected to further improve remote sensing capabilities for mapping LAI, CHLl and Nl.

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.

Meta-analysis of strategies to control nitrate leaching in irrigated agricultural systems and their effects on crop yield.

Nitrate leaching (NL) is an important N loss process in irrigated agriculture that imposes a cost on the farmer and the environment. A meta-analysis of published experimental results from agricultural irrigated systems was conducted to identify those strategies that have proven effective at reducing NL and to quantify the scale of reduction that can be achieved. Forty-four scientific articles were identified which investigated four main strategies (water and fertilizer management, use of cover crops and fertilizer technology) creating a database with 279 observations on NL and 166 on crop yield. Management practices that adjust water application to crop needs reduced NL by a mean of 80% without a reduction in crop yield. Improved fertilizer management reduced NL by 40%, and the best relationship between yield and NL was obtained when applying the recommended fertilizer rate. Replacing a fallow with a non-legume cover crop reduced NL by 50% while using a legume did not have any effect on NL. Improved fertilizer technology also decreased NL but was the least effective of the selected strategies. The risk of nitrate leaching from irrigated systems is high, but optimum management practices may mitigate this risk and maintain crop yields while enhancing environmental sustainability.

Influence of denitrifiers abundance on N2O emissions in long term tillage system under a rainfed legume crop

Current studies about nitrous oxide (N2O) emissions from legume crops have raised considerable doubt, observing a high variability between sites (0.03-7.09 kg N2O–N ha−1 y -1) [1]. This high variability has been associated to climate and soil conditions, legume species and soil management practices (e.g. conservation or conventional tillage). Conservation tillage (i.e. no tillage (NT) and minimum tillage (MT)) has spread during the last decades because promotes several positive effects (increase of soil organic content, reduction of soil erosion and enhancement of carbon (C) sequestration). However, these benefits could be partly counterbalanced by negative effects on the release of N2O emissions. Among processes responsible for N2O production and consumption in soils, denitrification plays an importantrole both in tilled and no-tilled ropping systems [2]. Recently, amplification of functional bacterial genes involved in denitrification is being used to examine denitrifiers abundance and evaluate their influence on N2O emissions. NirK and nirS are functional genes encoding the cytochrome cd1 and copper nitrite reductase, which is the key enzyme regulating the denitrification process.

N2O emissions and N efficiency due to tillage systems and crop rotation under a rainfed Mediterranean agroecosystem

Application of nitrogen (N) fertilizers in agricultural soils increases the risk of N loss to the atmosphere in the form of ammonia (NH3), nitrous oxide (N2O) and nitric oxide (NO)and the water bodies as nitrate (NO3-). The implementation of agricultural management practices can affect these losses. In Mediterranean irrigation systems, the greatest losses of NO3-through leaching occur within the irrigation and the intercropperiod. One way to abate these losses during the intercrop period is the use of cover crops that absorb part of the residual N from the root zone (Gabriel and Quemada, 2011). Moreover, during the following crop, these species could be applied as amendments to the soil, providing both C and N to the soil. This effect of cover and catch crops on decreasing the pool of N potentially lost has focused primarily on NO3-leaching. The aim of this work was to evaluate the effect of cover crops on N2O emission during the in tercrop period in a maize system and its subsequent incorporation into the soil in the following maize crop.

Nutritive value and protein quality of soybean meals according to origin and crop year

Resultados de la investigación sobre el valor nutritivo y calidad de la proteína de la alimentación basada en soja en función del origen y del año de la recolección.

Evaluation of cover crops based on characteristics of nitrogen use, and aerial and root growth

La caracterización de los cultivos cubierta (cover crops) puede permitir comparar la idoneidad de diferentes especies para proporcionar servicios ecológicos como el control de la erosión, el reciclado de nutrientes o la producción de forrajes. En este trabajo se estudiaron bajo condiciones de campo diferentes técnicas para caracterizar el dosel vegetal con objeto de establecer una metodología para medir y comparar las arquitecturas de los cultivos cubierta más comunes. Se estableció un ensayo de campo en Madrid (España central) para determinar la relación entre el índice de área foliar (LAI) y la cobertura del suelo (GC) para un cultivo de gramínea, uno de leguminosa y uno de crucífera. Para ello se sembraron doce parcelas con cebada (Hordeum vulgare L.), veza (Vicia sativa L.), y colza (Brassica napus L.). En 10 fechas de muestreo se midieron el LAI (con estimaciones directas y del LAI-2000), la fracción interceptada de la radiación fotosintéticamente activa (FIPAR) y la GC. Un experimento de campo de dos años (Octubre-Abril) se estableció en la misma localización para evaluar diferentes especies (Hordeum vulgare L., Secale cereale L., x Triticosecale Whim, Sinapis alba L., Vicia sativa L.) y cultivares (20) en relación con su idoneidad para ser usadas como cultivos cubierta. La GC se monitorizó mediante análisis de imágenes digitales con 21 y 22 muestreos, y la biomasa se midió 8 y 10 veces, respectivamente para cada año. Un modelo de Gompertz caracterizó la cobertura del suelo hasta el decaimiento observado tras las heladas, mientras que la biomasa se ajustó a ecuaciones de Gompertz, logísticas y lineales-exponenciales. Al final del experimento se determinaron el C, el N y el contenido en fibra (neutrodetergente, ácidodetergente y lignina), así como el N fijado por las leguminosas. Se aplicó el análisis de decisión multicriterio (MCDA) con objeto de obtener un ranking de especies y cultivares de acuerdo con su idoneidad para actuar como cultivos cubierta en cuatro modalidades diferentes: cultivo de cobertura, cultivo captura, abono verde y forraje. Las asociaciones de cultivos leguminosas con no leguminosas pueden afectar al crecimiento radicular y a la absorción de N de ambos componentes de la mezcla. El conocimiento de cómo los sistemas radiculares específicos afectan al crecimiento individual de las especies es útil para entender las interacciones en las asociaciones, así como para planificar estrategias de cultivos cubierta. En un tercer ensayo se combinaron estudios en rhizotrones con extracción de raíces e identificación de especies por microscopía, así como con estudios de crecimiento, absorción de N y 15N en capas profundas del suelo. Las interacciones entre raíces en su crecimiento y en el aprovisionamiento de N se estudiaron para dos de los cultivares mejor valorados en el estudio previo: uno de cebada (Hordeum vulgare L. cv. Hispanic) y otro de veza (Vicia sativa L. cv. Aitana). Se añadió N en dosis de 0 (N0), 50 (N1) y 150 (N2) kg N ha-1. Como resultados del primer estudio, se ajustaron correctamente modelos lineales y cuadráticos a la relación entre la GC y el LAI para todos los cultivos, pero en la gramínea alcanzaron una meseta para un LAI>4. Antes de alcanzar la cobertura total, la pendiente de la relación lineal entre ambas variables se situó en un rango entre 0.025 y 0.030. Las lecturas del LAI-2000 estuvieron correlacionadas linealmente con el LAI, aunque con tendencia a la sobreestimación. Las correcciones basadas en el efecto de aglutinación redujeron el error cuadrático medio del LAI estimado por el LAI-2000 desde 1.2 hasta 0.5 para la crucífera y la leguminosa, no siendo efectivas para la cebada. Esto determinó que para los siguientes estudios se midieran únicamente la GC y la biomasa. En el segundo experimento, las gramíneas alcanzaron la mayor cobertura del suelo (83-99%) y la mayor biomasa (1226-1928 g m-2) al final del mismo. Con la mayor relación C/N (27-39) y contenido en fibra digestible (53-60%) y la menor calidad de residuo (~68%). La mostaza presentó elevadas GC, biomasa y absorción de N en el año más templado en similitud con las gramíneas, aunque escasa calidad como forraje en ambos años. La veza presentó la menor absorción de N (2.4-0.7 g N m-2) debido a la fijación de N (9.8-1.6 g N m-2) y escasa acumulación de N. El tiempo térmico hasta alcanzar el 30% de GC constituyó un buen indicador de especies de rápida cubrición. La cuantificación de las variables permitió hallar variabilidad entre las especies y proporcionó información para posteriores decisiones sobre la selección y manejo de los cultivos cubierta. La agregación de dichas variables a través de funciones de utilidad permitió confeccionar rankings de especies y cultivares para cada uso. Las gramíneas fueron las más indicadas para los usos de cultivo de cobertura, cultivo captura y forraje, mientras que las vezas fueron las mejor como abono verde. La mostaza alcanzó altos valores como cultivo de cobertura y captura en el primer año, pero el segundo decayó debido a su pobre actuación en los inviernos fríos. Hispanic fue el mejor cultivar de cebada como cultivo de cobertura y captura, mientras que Albacete como forraje. El triticale Titania alcanzó la posición más alta como cultiva de cobertura, captura y forraje. Las vezas Aitana y BGE014897 mostraron buenas aptitudes como abono verde y cultivo captura. El MCDA permitió la comparación entre especies y cultivares proporcionando información relevante para la selección y manejo de cultivos cubierta. En el estudio en rhizotrones tanto la mezcla de especies como la cebada alcanzaron mayor intensidad de raíces (RI) y profundidad (RD) que la veza, con valores alrededor de 150 cruces m-1 y 1.4 m respectivamente, comparados con 50 cruces m-1 y 0.9 m para la veza. En las capas más profundas del suelo, la asociación de cultivos mostró valores de RI ligeramente mayores que la cebada en monocultivo. La cebada y la asociación obtuvieron mayores valores de densidad de raíces (RLD) (200-600 m m-3) que la veza (25-130) entre 0.8 y 1.2 m de profundidad. Los niveles de N no mostraron efectos claros en RI, RD ó RLD, sin embargo, el incremento de N favoreció la proliferación de raíces de veza en la asociación en capas profundas del suelo, con un ratio cebada/veza situado entre 25 a N0 y 5 a N2. La absorción de N de la cebada se incrementó en la asociación a expensas de la veza (de ~100 a 200 mg planta-1). Las raíces de cebada en la asociación absorbieron también más nitrógeno marcado de las capas profundas del suelo (0.6 mg 15N planta-1) que en el monocultivo (0.3 mg 15N planta-1). ABSTRACT Cover crop characterization may allow comparing the suitability of different species to provide ecological services such as erosion control, nutrient recycling or fodder production. Different techniques to characterize plant canopy were studied under field conditions in order to establish a methodology for measuring and comparing cover crops canopies. A field trial was established in Madrid (central Spain) to determine the relationship between leaf area index (LAI) and ground cover (GC) in a grass, a legume and a crucifer crop. Twelve plots were sown with either barley (Hordeum vulgare L.), vetch (Vicia sativa L.), or rape (Brassica napus L.). On 10 sampling dates the LAI (both direct and LAI-2000 estimations), fraction intercepted of photosynthetically active radiation (FIPAR) and GC were measured. A two-year field experiment (October-April) was established in the same location to evaluate different species (Hordeum vulgare L., Secale cereale L., x Triticosecale Whim, Sinapis alba L., Vicia sativa L.) and cultivars (20) according to their suitability to be used as cover crops. GC was monitored through digital image analysis with 21 and 22 samples, and biomass measured 8 and 10 times, respectively for each season. A Gompertz model characterized ground cover until the decay observed after frosts, while biomass was fitted to Gompertz, logistic and linear-exponential equations. At the end of the experiment C, N, and fiber (neutral detergent, acid and lignin) contents, and the N fixed by the legumes were determined. Multicriteria decision analysis (MCDA) was applied in order to rank the species and cultivars according to their suitability to perform as cover crops in four different modalities: cover crop, catch crop, green manure and fodder. Intercropping legumes and non-legumes may affect the root growth and N uptake of both components in the mixture. The knowledge of how specific root systems affect the growth of the individual species is useful for understanding the interactions in intercrops as well as for planning cover cropping strategies. In a third trial rhizotron studies were combined with root extraction and species identification by microscopy and with studies of growth, N uptake and 15N uptake from deeper soil layers. The root interactions of root growth and N foraging were studied for two of the best ranked cultivars in the previous study: a barley (Hordeum vulgare L. cv. Hispanic) and a vetch (Vicia sativa L. cv. Aitana). N was added at 0 (N0), 50 (N1) and 150 (N2) kg N ha-1. As a result, linear and quadratic models fitted to the relationship between the GC and LAI for all of the crops, but they reached a plateau in the grass when the LAI > 4. Before reaching full cover, the slope of the linear relationship between both variables was within the range of 0.025 to 0.030. The LAI-2000 readings were linearly correlated with the LAI but they tended to overestimation. Corrections based on the clumping effect reduced the root mean square error of the estimated LAI from the LAI-2000 readings from 1.2 to less than 0.50 for the crucifer and the legume, but were not effective for barley. This determined that in the following studies only the GC and biomass were measured. In the second experiment, the grasses reached the highest ground cover (83- 99%) and biomass (1226-1928 g/m2) at the end of the experiment. The grasses had the highest C/N ratio (27-39) and dietary fiber (53-60%) and the lowest residue quality (~68%). The mustard presented high GC, biomass and N uptake in the warmer year with similarity to grasses, but low fodder capability in both years. The vetch presented the lowest N uptake (2.4-0.7 g N/m2) due to N fixation (9.8-1.6 g N/m2) and low biomass accumulation. The thermal time until reaching 30% ground cover was a good indicator of early coverage species. Variable quantification allowed finding variability among the species and provided information for further decisions involving cover crops selection and management. Aggregation of these variables through utility functions allowed ranking species and cultivars for each usage. Grasses were the most suitable for the cover crop, catch crop and fodder uses, while the vetches were the best as green manures. The mustard attained high ranks as cover and catch crop the first season, but the second decayed due to low performance in cold winters. Hispanic was the most suitable barley cultivar as cover and catch crop, and Albacete as fodder. The triticale Titania attained the highest rank as cover and catch crop and fodder. Vetches Aitana and BGE014897 showed good aptitudes as green manures and catch crops. MCDA allowed comparison among species and cultivars and might provide relevant information for cover crops selection and management. In the rhizotron study the intercrop and the barley attained slightly higher root intensity (RI) and root depth (RD) than the vetch, with values around 150 crosses m-1 and 1.4 m respectively, compared to 50 crosses m-1 and 0.9 m for the vetch. At deep soil layers, intercropping showed slightly larger RI values compared to the sole cropped barley. The barley and the intercropping had larger root length density (RLD) values (200-600 m m-3) than the vetch (25-130) at 0.8-1.2 m depth. The topsoil N supply did not show a clear effect on the RI, RD or RLD; however increasing topsoil N favored the proliferation of vetch roots in the intercropping at deep soil layers, with the barley/vetch root ratio ranging from 25 at N0 to 5 at N2. The N uptake of the barley was enhanced in the intercropping at the expense of the vetch (from ~100 mg plant-1 to 200). The intercropped barley roots took up more labeled nitrogen (0.6 mg 15N plant-1) than the sole-cropped barley roots (0.3 mg 15N plant-1) from deep layers.

How do various maize crop models vary in their responses to climate change factors?

Comments This article is a U.S. government work, and is not subject to copyright in the United States. Abstract Potential consequences of climate change on crop production can be studied using mechanistic crop simulation models. While a broad variety of maize simulation models exist, it is not known whether different models diverge on grain yield responses to changes in climatic factors, or whether they agree in their general trends related to phenology, growth, and yield. With the goal of analyzing the sensitivity of simulated yields to changes in temperature and atmospheric carbon dioxide concentrations [CO2], we present the largest maize crop model intercomparison to date, including 23 different models. These models were evaluated for four locations representing a wide range of maize production conditions in the world: Lusignan (France), Ames (USA), Rio Verde (Brazil) and Morogoro (Tanzania). While individual models differed considerably in absolute yield simulation at the four sites, an ensemble of a minimum number of models was able to simulate absolute yields accurately at the four sites even with low data for calibration, thus suggesting that using an ensemble of models has merit. Temperature increase had strong negative influence on modeled yield response of roughly 0.5 Mg ha 1 per °C. Doubling [CO2] from 360 to 720 lmol mol 1 increased grain yield by 7.5% on average across models and the sites. That would therefore make temperature the main factor altering maize yields at the end of this century. Furthermore, there was a large uncertainty in the yield response to [CO2] among models. Model responses to temperature and [CO2] did not differ whether models were simulated with low calibration information or, simulated with high level of calibration information.

Automatic expert system based on images for accuracy crop row detection in maize fields

This paper proposes an automatic expert system for accuracy crop row detection in maize fields based on images acquired from a vision system. Different applications in maize, particularly those based on site specific treatments, require the identification of the crop rows. The vision system is designed with a defined geometry and installed onboard a mobile agricultural vehicle, i.e. submitted to vibrations, gyros or uncontrolled movements. Crop rows can be estimated by applying geometrical parameters under image perspective projection. Because of the above undesired effects, most often, the estimation results inaccurate as compared to the real crop rows. The proposed expert system exploits the human knowledge which is mapped into two modules based on image processing techniques. The first one is intended for separating green plants (crops and weeds) from the rest (soil, stones and others). The second one is based on the system geometry where the expected crop lines are mapped onto the image and then a correction is applied through the well-tested and robust Theil–Sen estimator in order to adjust them to the real ones. Its performance is favorably compared against the classical Pearson product–moment correlation coefficient.

Discriminating Crop, Weeds and Soil Surface with a Terrestrial LIDAR Sensor

In this study, the evaluation of the accuracy and performance of a light detection and ranging (LIDAR) sensor for vegetation using distance and reflection measurements aiming to detect and discriminate maize plants and weeds from soil surface was done. The study continues a previous work carried out in a maize field in Spain with a LIDAR sensor using exclusively one index, the height profile. The current system uses a combination of the two mentioned indexes. The experiment was carried out in a maize field at growth stage 12–14, at 16 different locations selected to represent the widest possible density of three weeds: Echinochloa crus-galli (L.) P.Beauv., Lamium purpureum L., Galium aparine L.and Veronica persica Poir.. A terrestrial LIDAR sensor was mounted on a tripod pointing to the inter-row area, with its horizontal axis and the field of view pointing vertically downwards to the ground, scanning a vertical plane with the potential presence of vegetation. Immediately after the LIDAR data acquisition (distances and reflection measurements), actual heights of plants were estimated using an appropriate methodology. For that purpose, digital images were taken of each sampled area. Data showed a high correlation between LIDAR measured height and actual plant heights (R 2 = 0.75). Binary logistic regression between weed presence/absence and the sensor readings (LIDAR height and reflection values) was used to validate the accuracy of the sensor. This permitted the discrimination of vegetation from the ground with an accuracy of up to 95%. In addition, a Canonical Discrimination Analysis (CDA) was able to discriminate mostly between soil and vegetation and, to a far lesser extent, between crop and weeds. The studied methodology arises as a good system for weed detection, which in combination with other principles, such as vision-based technologies, could improve the efficiency and accuracy of herbicide spraying.

Crop rotation and residues influence N2O emission and N efficiency rather than tillage under a rainfed Mediterranean agroecosystem

Conservation tillage and crop rotation have spread during the last decades because promotes several positive effects (increase of soil organic content, reduction of soil erosion, and enhancement of carbon sequestration) (Six et al., 2004). However, these benefits could be partly counterbalanced by negative effects on the release of nitrous oxide (N2O) (Linn and Doran, 1984). There is a lack of data on long-term tillage system study, particularly in Mediterranean agro-ecosystems. The aim of this study was to evaluate the effects of long-term (>17 year) tillage systems (no tillage (NT), minimum tillage (MT) and conventional tillage (CT)); and crop rotation (wheat (W)-vetch (V)-barley (B)) versus wheat monoculture (M) on N2O emissions. Additionally, Yield-scaled N2O emissions (YSNE) and N uptake efficiency (NUpE) were assessed for each treatment.

Influence of Tillage and Liming on N2O emission from a rainfed crop

Nitrous oxide (N2O) is the main greenhouse gas (GHG) produced by agricultural soils due to microbial processes. The application of N fertilizers is associated with an increase of N2O losses. However, it is possible to mitigate these emissions by the introduction of adequate management practices (Snyder et al., 2009). Soil conservation practices (i.e.no tillage, NT) have recently become widespread because they promote several positive effects (increases in soil organic carbonand soil fertility, reduction of soil erosion, etc). In terms of GHG emissions, there is no consensus in the literature on the effects of tillage on N2O. Several studies found that NT can produce greater (Baggs et al., 2003), lower (Malhi et al., 2006) or similar (Grandey et al., 2006) N2O emissions compared to traditional tillage (TT). This large uncertainty is associated with the duration of tillage practices and climatic variability. Liming is widely use to solve problems of soil acidity (Al toxicity, yield penalties, etc). Several studies show a decrease in N2O emissions with liming (Barton et al., 2013) whereas no significant effects or increases were observed in others (Galbally et al., 2010). The aim of this work was to evaluate the effects of tillage (NT vs TT) and liming application or not of Ca-amendment) on N2O emissions from an acid soil during a rainfed crop.

Soil P and cation availability and crop uptake in a forage rotation under conventional and reduced tillage

Long-term conservation tillage can modify vertical distribution of nutrients in soil profiles and alter nutrient availability and yields of crops.

Efficiency and environmental indexes to evaluate the sustainability of mineral and organic fertilization in an irrigated melon crop

Melon is traditionally cultivated in fertigated farmlands in the center of Spain with high inputs of water and N fertilizer. Excess N can have a negative impact, from the economic point of view, since it can diminish the production and quality of the fruit, from the environmental point of view, since it is a very mobile element in the soil and can contaminate groundwater. From health point of view, nitrate can be accumulated in fruit pulp, and, in addition, groundwater is the fundamental supply source of human populations. Best management practices are particularly necessary in this region as many zones have been declared vulnerable to NO3- pollution (Directive 91/676/CEE) During successive years, a melon crop (Cucumis melo L.) was grown under field conditions applying mineral and organic fertilizers under drip irrigation. Different doses of ammonium nitrate were used as well as compost derived from the wine-distillery industry which is relevant in this area. The present study reviews the most common N efficiency indexes under the different management options with a view to maximizing yield and minimizing N loss.