Four ponded depressional areas were selected in a cultivated field near Ste-Agnes de Dundee, Quebec. In 1988, land, soil, water and crop parameters were measured under ponding and non-ponding conditions in order to formalate a drainage investigation procedure for ponded depressions. / A sweet corn yield reduction of 39% was measured in depressions compared to ridges; this yield reduction occurred with 3 to 5 year interval of recurrence rainfalls. Loss of yield in depressional areas gave an overall reduction of 5% for the whole field. There was an additional loss in quality from poor uniformity of the corn cobs. The Ste-Agnes corn yield was estimated at 20% of the regional average. There was no significant difference between soil characteristics in depressions and ridges except for hydraulic characteristics such as infiltration and percolation rates as determined with the infiltrometer, and hydraulic conductivity as determined with the auger hole method. / The ponding runoff coefficients (mean PRC = 0.11) measured during the summer of 1988 were similar to the ones (mean PRC = 0.13) calculated using the CN curve method (USDA, SCS). / The low percolation rate of the subplow layer was found to be the main constraint to the subsurface drainage of the ponded depressions. / Soil survey and ponding study results were used to formulate a drainage investigation procedure for ponded depressional areas in the St. Lawrence Lowlands.

No description available.

The purpose of this study was to investigate the effect of maize (Zea mays L.) hybrids, plant population, rates of fertilization and irrigation in 1984 and 1985 on soil test levels, soil pH, yield and yield components as well as nutrient uptake. / High rates of fertilization increased soil test P and K but decreased soil test Ca and Mg and soil pH. Irrigation decreased soil test K, Ca and Mg. In both years maximum grain yields (at 15.5% moisture) were obtained when all factors were at high levels. Hybrid Pioneer 3925 and and hybrid CO-OP 2645 produced a maximum yield of 11.9 and 15.2 Mg ha$ sp{-1}$ in 1984 and 1985, respectively. Increasing plant population alone increased grain yield from 9.6 to 10.4 Mg ha$ sp{-1}$ in 1984, bu increases in grain yield with high plant population in 1985 could only be obtained when high rate of nutrients and supplemental irrigation were applied. / Nutrient uptake was usually greater for hybrid 2645 than hybrid 3925 in 1985, and greater for hybrid 3925 than for hybrid 3949 in 1984. Increasing plant population, rate of fertilization as well as available soil moisture generally brought about greater nutrient uptake. Ear leaf nutrient concentration at silking time was influenced by these factors but the differences obtained were not agronomically significant.

No description available.

No description available.

The use of crop growth simulation models such asthose incorporated into Decision Support Systems for Agrotechnology Transfer (DSSAT) are useful tools for assessing the impacts of various management practices on crop productivity. The maize growth model of DSSAT is CERES-maize. To evaluate its predictive capability under western Quebec conditions, data on corn (Zea mays L.) yield and above-ground biomass were collected from a field-scale water table management experiment conducted during the 1996 and 1997 growing seasons at St. Emmanuel, Soulanges County, Quebec. The model was calibrated using various crop growth and development data observed during the 1996 growing season. Cultivar-specific coefficients were determined during the calibration. All measured data on phenology, grain yield and biomass collected in 1997 were used for model validation. / Validation results showed good agreement between predicted and measured yields. In 1996, the Root Mean Square Error (RMSE) was 0.64 and 0.66 Mg/ha for the free drainage plots with 200 kg/ha N (FD200) and 120 kg/ha N (FD120), respectively. In 1997, the RMSE for FD200 and FD120 were 1.07 and 1.23 Mg/ha respectively. However, the model overpredicted the biomass for 1997, and grain number for both FD200 and FD120 treatments in both years. The mean difference (MD) between simulated and observed biomass at maturity was statistically significant at (P < 0.01) for both treatments. Sensitivity analyses showed that the CERES-Maize model was most sensitive to changes in air temperature. The model was also sensitive to soil water and crop genetic parameters.

An incubation study was conducted to evaluate the effects of added urea, NH$ sb4$Cl, and KCl on fixation of NH$ sb4 sp{+}$ and K$ sp{+}$. A field study was carried out to observe the effects of rates and methods of added urea and KCl on the forms and distribution of N and K in soils, and on yields and nutrient uptake of silage corn. / Generally, the fixation of NH$ sb4 sp{+}$ was increased by added N but reduced by added K and vice versa. One exception was that added K increased NH$ sb4 sp{+}$ fixation when NH$ sb4$Cl was the N source. In comparison with NH$ sb4$Cl, urea resulted in greater K$ sp{+}$ fixation but less NH$ sb4 sp{+}$ fixation. / Band placement of urea and KCl showed apparent accumulation of NH$ sb4$-N and NO$ sb3$-N, and exchangeable K$ sp{+}$ in the fertilizer bands, particularly early in the growing season. On the other hand, band placement resulted in lower levels of available N and K in soil between the bands in comparison with broadcast. / Yields of silage corn and nutrient uptake values were increased by N and K fertilizers, except for one soil in the first year. Band placement of urea was superior in the case of frequent and light rainfall but inferior with dry surface soil conditions followed by a relatively large rainfall 3 or 4 days after application. In the latter condition, banding K resulted in less yields on one soil, and banding the two fertilizers together further reduced N utilization on another soil. / Additions of K suppressed Ca and Mg uptake but did not influence N uptake, whereas K uptake was usually enhanced by added N.

No description available.

The use of agricultural chemicals, such as nitrogen fertilizers in corn production, often results in water pollution. This research, comprising three parts, was designed to investigate the effects of nitrogen fertilizer application rates, water table management, and corn cropping systems on drainage water quality. The first part was a field study, to investigate the impact of two cropping systems and water table management on nitrate loss through tile drainage. The considered water table treatments were free drainage, and subirrigation with target water table depths at 0.5 m or 0.75 M below the soil surface. Corn (Zea mays L.) monoculture and corn intercropped with annual ryegrass (Lolium multiflorum Lam.) were investigated. The highest annual tile drainage losses of 21.9 kg N/ha were measured in monocropped, freely draining plots. Subirrigation with a water table depth of 0.5 m reduced tile drainage loss of N by over 70%, and intercropping corn with ryegrass under free drainage reduced leaching losses by 50%. / The second part of the research was a simulation study with the water quality model, DRAINMOD-N. The water quality impact of fertilizer application rate under free drainage, subirrigation and controlled drainage was evaluated. Leaching losses, denitrification and N accumulation in the soil profile were investigated. Using data obtained from the field experiment, the performance of DRAINMOD-N was evaluated. DRAINMOD-N assumes that denitrification follows first order kinetics, contrary to field measurements which showed little correlation between denitrification rate and NO$ sb3 sp-$-N concentration. Therefore, DRAINMOD-N was modified by replacing the original denitrification function with the Michaelis-Menten relationship. In so doing, denitrification is expressed as a first order process when NO$ sb3 sp-$-N concentration limits denitrification, and as a zero order process for non-limiting NO$ sb3 sp-$-N concentration. / For denitrification to be a decision making criterion of water table management, inexpensive but reliable measurement techniques are required. Thus, the purpose of the final part of this research was to formulate a technique for measuring real-time denitrification rate. Denitrification rate could be expressed as a function of soil redox potential (Eh) and temperature. Laboratory and field studies showed that factors such as soil nitrate and organic carbon had negligible effect on denitrification rate. Therefore, it can be concluded that for most agricultural soil, Eh and soil temperature will satisfactorily describe denitrification variation.

This study used hyperspectral data to determine nitrogen, weed, and water stresses in a corn (Zea mays L.) field in southwestern Quebec, and incorporated these data in crop growth models for better crop growth simulation under stressful conditions. / In 2000, aerial hyperspectral images (72 wavebands, ranging from 407 to 949 nm) were acquired, and analyzed using a stepwise approach to identify wavebands useful in detecting weed and nitrogen stresses. Discriminant analysis (DA) was used to classify different weed and nitrogen treatments and their combinations. This analysis showed greater classification accuracy (nearly 75%) than those obtained with artificial neural networks (58%) or decision tree algorithms (60%), at the initial growth stages, the time when remedial actions are most needed to alleviate weed and nitrogen stresses. / To explore the possibility of improving nitrogen stress detection in corn in the presence of a confounding water stress, ground-based 2151 narrow-waveband reflectance values (350 to 2500 nm), were collected in 2002. Using DA with the chosen subset of narrow-wavebands, a classification accuracy of greater than 95% was obtained. / For crop growth monitoring, the STICS model was evaluated for yield and biomass estimation in cornfields under different stressful growth conditions using the data collected from 2000 to 2002. Measured yield, biomass, and leaf area index (LAI) were used for both calibration and validation of the model. High correlation coefficients between the measured and estimated grain yield (0.96), biomass (0.98), and LAI (0.93) indicated that the model has good potential in the simulation of corn growth. The model was also linked with LAI values estimated from the hyperspectral observations using the Support Vector Machines technique. Coupling STICS with remote sensing resulted in an overall improvement in the simulation of corn yield (6.3%) and biomass (3.7%). / A new approach was developed to apply crop growth models for yield estimation in weedy areas. The proposed method first corrects the measured/estimated LAI values in weed infested fields for weed effect, and then uses the corrected LAI values as input to the crop growth model. The results showed that the crop yield and biomass predictions were correctly simulated by this method.* / *This dissertation is a compound document (contains both a paper copy and a CD as part of the dissertation).