Use of a pre-sidedress soil nitrate test (PSNT) to determine nitrogen fertilizer requirements for irrigated corn

In the present study, a 2-year N rate response experiment was conducted in different fields to monitor NO3-N soil profiles, N accumulation by the crop and final crop performance, in order to assess if soil NO3-N at pre-sidedressing (Pre-Sidedress Soil Nitrate Test, PSNT) is a reliable indicator for soil N availability for corn in the irrigated area served by canal d’Urgell (Lleida, Spain), and if the test can be used to separate responsive fields from non-responsive fields to sidedress N fertilizer applications. Preliminary soil N availability (N sidedress fertilizer rate + PSNT) critical levels to identify fields that need supplementary N fertilizer applications were established at ca. 300 and 210 kg NO3-N·ha–1, for PSNTrooting–zone and PSNT0–30 cm, respectively (for a yield goal of 14 t grain·ha–1).

A priori parameterisation of the CERES soil-crop models and tests against several European data sets

Mechanistic soil-crop models have become indispensable tools to investigate the effect of management practices on the productivity or environmental impacts of arable crops. Ideally these models may claim to be universally applicable because they simulate the major processes governing the fate of inputs such as fertiliser nitrogen or pesticides. However, because they deal with complex systems and uncertain phenomena, site-specific calibration is usually a prerequisite to ensure their predictions are realistic. This statement implies that some experimental knowledge on the system to be simulated should be available prior to any modelling attempt, and raises a tremendous limitation to practical applications of models. Because the demand for more general simulation results is high, modellers have nevertheless taken the bold step of extrapolating a model tested within a limited sample of real conditions to a much larger domain. While methodological questions are often disregarded in this extrapolation process, they are specifically addressed in this paper, and in particular the issue of models a priori parameterisation. We thus implemented and tested a standard procedure to parameterize the soil components of a modified version of the CERES models. The procedure converts routinely-available soil properties into functional characteristics by means of pedo-transfer functions. The resulting predictions of soil water and nitrogen dynamics, as well as crop biomass, nitrogen content and leaf area index were compared to observations from trials conducted in five locations across Europe (southern Italy, northern Spain, northern France and northern Germany). In three cases, the model’s performance was judged acceptable when compared to experimental errors on the measurements, based on a test of the model’s root mean squared error (RMSE). Significant deviations between observations and model outputs were however noted in all sites, and could be ascribed to various model routines. In decreasing importance, these were: water balance, the turnover of soil organic matter, and crop N uptake. A better match to field observations could therefore be achieved by visually adjusting related parameters, such as field-capacity water content or the size of soil microbial biomass. As a result, model predictions fell within the measurement errors in all sites for most variables, and the model’s RMSE was within the range of published values for similar tests. We conclude that the proposed a priori method yields acceptable simulations with only a 50% probability, a figure which may be greatly increased through a posteriori calibration. Modellers should thus exercise caution when extrapolating their models to a large sample of pedo-climatic conditions for which they have only limited information.

Effects of DMPP on the growth and chemical composition of ryegrass (Lolium perenne L.) raised on calcareous soil

Se llevó a cabo un experimento de 406 días en macetas para evaluar el nuevo inhibidor de la nitrificación, 3,4-dimetilpirazol fosfato (DMPP), añadido a purines de cerdo. Se utilizaron macetas que contenían tierra franca calcárea que fueron sujetas a los siguientes tratamientos: sin purín, 73,7; 147,3 y 221 cm3 de purín por maceta, todas con o sin tratamiento de DMPP. A los 18 días las macetas fueron sembradas con Lolium perenne L. El mayor rendimiento (36,3 g maceta-1) se obtuvo para el tratamiento con la dosis superior de purín y DMPP, siendo un 7,4% superior al mismo tratamiento sin inhibidor y un 46,1% superior al tratamiento control. Las plantas tratadas con dosis alta y mediana, más el DMPP, absorbieron el 70% del total del N durante la primera fase del experimento (104 días) mientras que sin inhibidor absorbieron el 55,3 y el 62% respectivamente. Se observó una reducción significativa del 17% en el N lixiviado en los tratamientos sin cultivo al aplicar DMPP. El inhibidor aumentó significativamente la eficiencia agronómica del purín (g materia seca g-1 N aplicado).

Use of nitrification inhibitor DMPP to improve nitrogen recovery in irrigated wheat on a calcareous soil

The 3,4-dimethyilpyirazole phosphate (DMPP), commercialized as Entec, is a nitrification inhibitor developed by BASF (Germany) that may help to minimize N losses and to obtain a higher profit from N fertilizers. A two-year field trial was established in 2001 in the Northeast of Spain to assess the effects of DMPP on N use efficiency (NUE) and to determine the economic returns. Seven treatments have been carried out comparing the effect of DMPP on pig slurry and on mineral fertilizers. The application of DMPP resulted in better efficiency indexes on mineral fertilizers. An apparent nitrogen recovery of 0.465 kg kg-1, on average, was obtained for the Entec treatment. A net benefit of € 809 ha-1, on average, was obtained for the Entec treatment compared with € 607 ha-1 for the control treatment. The results of this study suggest that the nitrification inhibitor could improve farmer profit in irrigated wheat on a calcareous soil.

Consideraciones acerca de los límites de aplicación del método del número de Curva del Soil Conservation Service

En el presente artículo se revisan las limitaciones de aplicación del método del Número de Curva del Soil Conservation Service, modelo conceptual ampliamente difundido para el cálculo de la escorrentía originada por una tormenta. Si bien es cierto que el método posee una serie de capacidades y ventajas que han motivado su éxito en la modelación hidrológica, en particular su simplicidad de uso y la economía en la obtención de los datos físicos necesarios, no es menos cierto que deben contemplarse una serie de restricciones de aplicación. La amplia difusión de la que ha sido objeto ha propiciado la discusión y revisión crítica del modelo, acotando paulatinamente sus límites. Entre los más significativos de éstos, destacan la necesidad de regionalizar, a partir de campañas de aforos, ciertas hipótesis y parámetros del método, así como las precauciones que deben adoptarse si se aplica a cuencas forestales densas con suelos muy permeables.

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 (R2 = 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.