Mapping of the apparent soil electrical conductivity (ECa) can be used to estimate the variability of forage yield within a plot. However, forage production can vary according to the growing season and to soil properties that do not affect the ECa (e.g. nitrogen (N) content). The aim of this study was to assess the relationship between ECa and forage yield of tall fescue (Lolium arundinaceum (Schreb.) Darbysh.) during different regrowth periods and contrasting levels of N availability and then use this information to determine potential management zones. The ECa was measured and geo-referenced in a 5.75-ha paddock that sustained a permanent pasture dominated by tall fescue. In addition, a 30 m by 30 m grid cell size was chosen and 43 sampling areas, each 4 m2 in size, were geo-referenced and divided into two experimental units of 1 m by 2 m, one of which was fertilised with 250 kg N ha–1 (N250) at the beginning of four regrowth periods (spring 2015, spring 2016, autumn 2016 and autumn 2017) and the other was not fertilised with N (N0). At the end of each regrowth period, we estimated the accumulated biomass. During the spring growing season, accumulated biomass was positively associated with ECa in both N0 and N250 treatments (R2 = 47% and 54%, respectively). By contrast, in autumn, accumulated biomass and ECa were poorly associated (R2 = 10% and 27% for N0 and N250). This may be due to seasonal interactions that alter soil–yield relationships. To assess whether ECa can be used to determine management zones, the differences in accumulated biomass were compared through analysis of variance. Results showed that ECa is associated with the spatial distribution of tall fescue forage yield variability in spring at different N availabilities. Thus, ECa can be reliably used for defining management zones in marginal soils under permanent pastures.
The spatial variability in soils used for livestock production (i.e. Natraquoll and Natraqualf) at farm and paddock scale is usually very high. Understanding this spatial variation within a field is the first step for site-specific crop management. For this reason, we evaluated whether apparent electrical conductivity (ECa), a widely used proximal soil sensing technology, is a potential estimator of the edaphic variability in these types of soils. ECa and elevation data were collected in a paddock of 16 ha. Elevation was negatively associated with ECa. Geo-referenced soil samples were collected and analyzed for soil organic matter (OM) content, pH, the saturation extract electrical conductivity (EC ext ), available phosphorous (P), and anaerobically incubated Nitrogen (Nan). Relationships between soil properties and ECa were analyzed using regression analysis, principal components analysis (PCA), and stepwise regression. Principal components (PC) and the PC-stepwise were used to determine which soil properties have an important influence on ECa. In this experiment elevation was negatively associated with ECa. The data showed that pH, OM, and EC ext exhibited a high correlation with ECa (R 2 =0.76; 0.70 and 0.65, respectively). Whereas P and Nan showed a lower correlation (R 2 =0.54 and 0.11 respectively). The model resulting from the PC-stepwise regression analysis explained slightly more than 69% of the total variation of the measured ECa, only retaining PC1. Therefore, EC ext , pH and OM were considered key latent variables because they substantially influence the relationship between the PC1 and the ECa (loading factors>0.4). Results showed that ECa is associated with the spatial distribution of some important soil properties. Thus, ECa can be used as a support tool to implement site-specific management in soils for livestock use.Additional key words: multivariate techniques; soil properties; geographic information system; lowland soils; spatial variability. Abbreviations used: ECa (apparent soil electrical conductivity); EC ext (electrical conductivity of the saturation extract); GWR (geographically weighted regression); Nan (anaerobically incubated nitrogen); OM (soil organic matter content); P (available phosphorous); PCA (principal component analysis); PC (principal component).Citation: Peralta, N. R.; Cicore, P. L.; Marino, M. A.; Marques da Silva, J. R.; Costa, J. L. (2015). Use of geophysical survey as a predictor of the edaphic properties variability in soils used for livestock production.
Late blight is the main disease of potatoes around the world. Because of the difficulties in applying effective control methods, the introduction of resistant cultivars represents a safe strategy. The potato species Solanum tarijense represents an attractive resistance source as its adaptation to long days is promissory, producing tubers of good size and aspect. Deposition of structural compounds like lignin and callose were described as a non-specific resistance mechanism. In this work, we measured polyphenoloxidases (PPO) and peroxidases (POX) activities and the accumulation of phenols, lignin and callose and their correlation with the resistance levels of S. tarijense. Clones Oka 6320.9 and Oka 5632.11 showed low infection rates and these were correlated with a higher accumulation of phenols, lignin and callose and a strong induction of PPO and POX activities. However, in highly infected clones, a lower or no accumulation of these compounds was observed. These results demonstrate a correlation between the amount of defence molecules and the resistance levels according to the detached-leaf assay. However, more field experiments are required to validate these results.
resumenEl objetivo fue evaluar, en diferentes posiciones topográficas, el crecimiento de agropiro alargado (Thinopyrum ponticum [Podp.] Barkworth & D. R. Dewey Phil) bajo diferente disponibilidad de nitrógeno (N). Se seleccionaron siete sitios en función de la elevación, y en cada sitio se evaluaron dos tratamientos: N-(sin aplicación de N) y N+ (300 kg ha -1 de N). En la biomasa aérea acumulada (BA) final se detectó interacción entre el nivel de N y el sitio. En N+ se hallaron diferencias significativas entre sitios, mientras que en el tratamiento N-no se encontraron diferencias. La variabilidad de la BA se debió principalmente a diferencias en la eficiencia de uso de la radiación. La altimetría de los sitios se relacionó negativamente con la BA. Esto indicaría que el factor que limitó la producción varió con la elevación. El contenido de agua del suelo podría ser este factor porque se relacionó inversamente con la elevación. En conclusión, pequeñas variaciones de altimetría podrían provocar cambios en la disponibilidad de agua y en consecuencia en la producción de forraje, que es capaz de ser detectada cuando no hay limitantes de N.Palabras clave: altimetría, humedad del suelo, pasturas, suelos bajos.
Little information is available on the degree of within-field variability of potential production of Tall wheatgrass (Thinopyrum ponticum) forage under unirrigated conditions. The aim of this study was to characterize the spatial variability of the accumulated biomass (AB) without nutritional limitations through vegetation indexes, and then use this information to determine potential management zones. A 27-×-27-m grid cell size was chosen and 84 biomass sampling areas (BSA), each 2 m 2 in size, were georeferenced. Nitrogen and phosphorus fertilizers were applied after an initial cut at 3 cm height. At 500°C day, the AB from each sampling area, was collected and evaluated. The spatial variability of AB was estimated more accurately using the Normalized Difference Vegetation Index (NDVI), calculated from LANDSAT 8 images obtained on 24 November 2014 (NDVI nov ) and 10 December 2014 (NDVI dec ) because the potential AB was highly associated with NDVI nov and NDVI dec (r 2 = 0.85 and 0.83, respectively). These models between the potential AB data and NDVI were evaluated by root mean squared error (RMSE) and relative root mean squared error (RRMSE). This last coefficient was 12 and 15 % for NDVI nov and NDVI dec , respectively. Potential AB and NDVI spatial correlation were quantified with semivariograms. The spatial dependence of AB was low. Six classes of NDVI were analyzed for comparison, and two management zones (MZ) were established with them. In order to evaluate if the NDVI method allows us to delimit MZ with different attainable yields, the AB estimated for these MZ were compared through an ANOVA test. The potential AB had significant differences among MZ. Based on these findings, it can be concluded that NDVI obtained from LANDSAT 8 images can be reliably used for creating MZ in soils under permanent pastures dominated by Tall wheatgrass.
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