Temporal Variations in N2O Emissions in Maize and Wheat Crop Seasons: Impact of N-Fertilization, Crop Growth, and Weather Variables

2016 ◽  
Vol 30 (1) ◽  
pp. 17-31 ◽  
Author(s):  
Harmanjit S. Dhadli ◽  
Babu S. Brar ◽  
Pavneet K. Kingra
Keyword(s):  
Temporal Variations ◽  
N Fertilization ◽  
Crop Growth ◽  
Wheat Crop ◽  
N2o Emissions ◽  
Weather Variables

scholarly journals Environmental Impact of Rotationally Grazed Pastures at Different Management Intensities in South Africa

Animals ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 1214
Author(s):  
Hendrik P. J. Smit ◽  
Thorsten Reinsch ◽  
Pieter A. Swanepoel ◽  
Ralf Loges ◽  
Christof Kluß ◽  
...  
Keyword(s):  
South Africa ◽  
N Fertilization ◽  
Yield Response ◽  
N2o Emissions ◽  
Pasture Management ◽  
N Losses ◽  
Enteric Fermentation ◽  
Soil C ◽  
Grazed Pastures ◽  
Soil C And N

Nitrogen fertilization, irrigation and concentrate feeding are important factors in rotational pasture management for dairy farms in South Africa. The extent to which these factors affect environmental efficiency is subject to current and intense debate among scientists. A three-year field study was conducted to investigate the yield response of different N-fertilizer treatments (0 (N0), 220 (N20), 440 (N40), 660 (N60) and 880 (N80) kg N ha−1 year−1) on grazed pastures and to calculate the carbon footprint (CF) of milk produced. Excessive N-fertilization (N60 and N80) did not increase herbage dry matter and energy yields from pastures. However, N80 indicated the highest N-yield but at the same time also the highest N surpluses at field level. A maximum fertilizer rate of 220 kg ha−1 year−1 (in addition to excreted N from grazing animals) appears sufficient to ensure adequate herbage yields (~20 t DM ha−1 year−1) with a slightly positive field-N-balance. This amount will prevent the depletion of soil C and N, with low N losses to the environment, where adequate milk yields of ~17 t ECM ha−1 with a low CF (~1.3 kg CO2 kg ECM−1) are reached. Methane from enteric fermentation (~49% ± 3.3) and N2O (~16% ± 3.2) emissions from irrigated pastures were the main contributors to the CF. A further CF reduction can be achieved by improved N-fertilization planning, low emission irrigation techniques and strategies to limit N2O emissions from pasture soils in South Africa.

scholarly journals THE INFLUENCE OF FERTILIZATION AND RAINFALL ON WHEAT PRODUCTION

1970 ◽  
Vol 62 ◽  
Author(s):  
C. Naidin
Keyword(s):  
Plant Development ◽  
Vegetation Period ◽  
N Fertilization ◽  
Wheat Crop ◽  
Growth Stages ◽  
P Fertilization ◽  
Wheat Production ◽  
Previous Crop ◽  
Rainfall Deficit ◽  
Higher Doses

In this paper, we analyze the influence of N and P fertilization on wheat yields, taking into account the previous crop and the level of rainfall accumulated until the end of the growth stages in plant development. In the wheat crops developed on the reddish-brown low luvi soil found at ARDS Simnic, the N fertilization has favorable effects in moderate doses (60 - 100 kg N/ha after corn and 60 - 90 kg N/ha after peas), while in higher doses (120 - 160 kg N/ha) fertilization determines a fall in production, both in the case of rainfall deficit and excess. The P has favorable effects on wheat crops, especially when the previous crop is peas. The rainfall quantity, as well as its repartition along the vegetation period, influences the wheat crop, causing great variations from year to year. The obtained data shows that rainfall deficit as well as rainfall excess determines a drop in wheat production; relatively high and stable average productions can be obtained in the case of rainfall levels close to the multi annual averages in different plant development stages.

Estimation of winter wheat crop growth parameters using time series Sentinel-1A SAR data

2017 ◽  
Vol 33 (9) ◽  
pp. 942-956 ◽  
Author(s):  
P. Kumar ◽  
R. Prasad ◽  
D. K. Gupta ◽  
V. N. Mishra ◽  
A. K. Vishwakarma ◽  
...  
Keyword(s):  
Time Series ◽  
Winter Wheat ◽  
Growth Parameters ◽  
Crop Growth ◽  
Wheat Crop ◽  
Winter Wheat Crop ◽  
Sar Data

scholarly journals Satellite Constellation Reveals Crop Growth Patterns and Improves Mapping Accuracy of Cropping Practices for Subtropical Small-Scale Fields in Japan

2020 ◽  
Vol 12 (15) ◽  
pp. 2419
Author(s):  
Asahi Sakuma ◽  
Hiroya Yamano
Keyword(s):  
Classification Accuracy ◽  
Vegetation Indices ◽  
Temporal Variations ◽  
Crop Growth ◽  
Growth Patterns ◽  
Small Scale ◽  
Satellite Constellation ◽  
High Classification Accuracy ◽  
Crop Types ◽  
Spatio Temporal

Mapping of agricultural crop types and practices is important for setting up agricultural production plans and environmental conservation measures. Sugarcane is a major tropical and subtropical crop; in general, it is grown in small fields with large spatio-temporal variations due to various crop management practices, and satellite observations of sugarcane cultivation areas are often obscured by clouds. Surface information with high spatio-temporal resolution obtained through the use of emerging satellite constellation technology can be used to track crop growth patterns with high resolution. In this study, we used Planet Dove imagery to reveal crop growth patterns and to map crop types and practices on subtropical Kumejima Island, Japan (lat. 26°21′01.1″ N, long. 126°46′16.0″ E). We eliminated misregistration between the red-green-blue (RGB) and near-infrared band imagery, and generated a time series of seven vegetation indices to track crop growth patterns. Using the Random Forest algorithm, we classified eight crop types and practices in the sugarcane. All the vegetation indices tested showed high classification accuracy, and the normalized difference vegetation index (NDVI) had an overall accuracy of 0.93 and Kappa of 0.92 range of accuracy for different crop types and practices in the study area. The results for the user’s and producer’s accuracy of each class were good. Analysis of the importance of variables indicated that five image sets are most important for achieving high classification accuracy: Two image sets of the spring and summer sugarcane plantings in each year of a two-year observation period, and one just before harvesting in the second year. We conclude that high-temporal-resolution time series images obtained by a satellite constellation are very effective in small-scale agricultural mapping with large spatio-temporal variations.

Assessing soil moisture constraint on soil evaporation and plant transpiration fractioning

2020 ◽  
Author(s):  
Bouchra Ait Hssaine ◽  
Olivier Merlin ◽  
Jamal Ezzahar ◽  
Salah Er-raki ◽  
Saïd Khabba ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Water Resource Management ◽  
Root Zone ◽  
Temporal Variations ◽  
Soil Evaporation ◽  
Balance Model ◽  
Wheat Crop ◽  
Soil Resistance ◽  
Plant Transpiration

<p>Over semi-arid agricultural regions, detecting the crop water need at the onset of water stress is of paramount importance for optimizing the use of irrigation water. Evapotranspiration (ET) is a crucial component of the water cycle, it strongly impacts the water resource management, drought monitoring, and climate. Remote sensing observations provide very relevant information to feed ET models. In particular, the microwave-derived surface (0-5 cm) soil moisture (SM), which is the main controlling factor of soil evaporation, the visible/near-infratred-derived vegetation cover fraction (fc), which provides an essential structural constraint on the fractioning between vegetation transpiration and soil evaporation, and - thermal-derived land surface temperature (LST), which is a signature of both available energy and evapotranspiration (ET) rate. The aim of this work is to integrate those independent and complementary information on total ET within an energy balance model. As a state-of-the-art and commonly used model, we chose the TSEB modelling as a basis for developments. An innovative calibration procedure is proposed to retrieve the main parameters of soil evaporation (soil resistance, r<sub>ss</sub>) and plant transpiration (Priestly Taylor coefficient, α<sub>PT</sub>) based on a threshold on fc. The procedure is applied over an irrigated wheat field in the Tensift basin, central Morocco. Overall, the coupling of the soil resistance formulation with the TSEB formalism improves the estimation of soil evaporation, and consequently, improves the partitioning of ET. Analysis of the retrieved time series indicates that the daily α<sub>PT</sub> mainly follows the phenology of winter wheat crop with a maximum value coincident with the full development of green biomass and a minimum value reached at harvest. The temporal variations of α<sub>PT</sub> before senescence are attributed to the dynamics of both the root zone soil moisture and the amount of green biomass.</p>

The effectiveness of nitrification inhibitor application on grain yield and quality, fertiliser nitrogen recovery and soil nitrous oxide emissions in a legume–wheat rotation under elevated carbon dioxide (FACE)

Soil Research ◽  
2018 ◽  
Vol 56 (2) ◽  
pp. 145
Author(s):  
Humaira Sultana ◽  
Helen C. Suter ◽  
Roger Armstrong ◽  
Marc E. Nicolas ◽  
Deli Chen
Keyword(s):  
Carbon Dioxide ◽  
Nitrous Oxide ◽  
Copper Concentration ◽  
Nitrification Inhibitor ◽  
Elevated Carbon Dioxide ◽  
Wheat Crop ◽  
N2o Emissions ◽  
N Concentration ◽  
Supplementary Irrigation ◽  
The Impact

Managing nitrogen (N) supply to better match crop demand and reduce losses will be an important goal under future predicted elevated carbon dioxide (e[CO2]) conditions. This study comprised two Free-Air Carbon dioxide Enrichment (FACE) experiments conducted in southern Australia in 2011. The first experiment (Exp-1) was a field experiment that investigated the impact of a nitrification inhibitor (NI), 3,4-dimethylpyrazole phosphate (DMPP), and supplementary irrigation on utilisation of legume (field pea) residual N by a wheat crop and soil nitrous oxide (N2O) emissions. The second experiment (Exp-2) used 15N techniques in soil cores to investigate the impact of DMPP on recovery of fertiliser N. In Exp-1, grain N concentration increased (by 12%, P < 0.001) with NI application compared with no NI application, irrespective of CO2 concentration ([CO2]) and supplementary irrigation. With NI application the grain N harvest index increased under e[CO2] (82%) compared with a[CO2] (79%). Applying the NI compensated for decreased grain copper concentration observed under e[CO2] conditions. NI had minimal effect on soil N2O emissions in the wheat crop regardless of [CO2]. In Exp-2, 65% (±1 standard error, n = 15) of the applied N fertiliser was recovered in the aboveground plant, irrespective of NI use. The use of a NI in a cereal–legume rotation may help to increase grain N concentration, increase the mobilisation of N towards the grain under e[CO2], and may also help to compensate for decreases in grain copper concentration under e[CO2]. However, use of a NI may not provide additional benefit for productivity or efficiency of N utilisation.

scholarly journals Crop Growth and Yield Losses in Wheat Due to Little Seed Canary Grass Infestation Differ with Weed Densities and Changes in Environment

2017 ◽  
Vol 35 (0) ◽  
Author(s):  
S. HUSSAIN ◽  
A. KHALIQ ◽  
A.A. BAJWA ◽  
A. MATLOOB ◽  
A. AREEB ◽  
...  
Keyword(s):  
Crop Growth ◽  
Growth And Yield ◽  
Wheat Crop ◽  
Dry Matter Accumulation ◽  
Yield Losses ◽  
Contributing Factors ◽  
Area Index ◽  
Weed Interference ◽  
Sowing Dates ◽  
Canary Grass

ABSTRACT: Understanding the weed interference with different sowing times of crop is inevitable for forecasting yield losses by weed infestation and designing sustainable weed management systems. A field experiment was carried out to evaluate the effects of sowing dates (20th November, 10th December) and various little seed canary grass (LCG) infestation levels (10, 20, 30 and 40 plant m-2) on growth and yield of wheat under semiarid conditions. Plots with two natural infestations of weeds including LCG (Unweeded control; UWC) and excluding LCG (UWC-LCG) were maintained for comparing its interference in pure stands with designated densities. A season-long weed-free (WFC) treatment was also run. All the weeds/LCG infestation levels starting from 10 LCG plants m-2 considerably reduced the wheat growth (leaf area index, crop growth rate, total dry matter accumulation) and hampered the yield contributing factors in both sowing dates. Presence of LCG was more detrimental for growth of late-sown wheat (10th Dec), therefore, 40 LCG plants m-2 recorded more reductions in growth indices of wheat even than UWC. In late sown wheat crop, the grain yield losses by 40 LCG plants m-2 and UWC were comparable, however, these losses were much greater than UWC LCG. In crux, delay in sowing of wheat not only reduced the crop growth and yield but also enhanced the LCG/weed interference. Furthermore, greater competitive ability of LCG particularly for late-sown wheat suggests that it should be controlled in order to provide healthy environment for crop plants.

scholarly journals Controls over N<sub>2</sub>O, NO<sub>x</sub> and CO<sub>2</sub> fluxes in a calcareous mountain forest soil

2005 ◽  
Vol 2 (5) ◽  
pp. 1423-1455 ◽  
Author(s):  
B. Kitzler ◽  
S. Zechmeister-Boltenstern ◽  
C. Holtermann ◽  
U. Skiba ◽  
K. Butterbach-Bahl
Keyword(s):  
Forest Soil ◽  
Co2 Emissions ◽  
Temporal Variations ◽  
Beech Forest ◽  
N Deposition ◽  
Measuring System ◽  
Mountain Forest ◽  
N2o Emissions ◽  
Minor Importance ◽  
Forest Site

Abstract. We measured nitrogen oxides (N2O and NOx), dinitrogen (N2) and carbon dioxide (CO2) emissions from a spruce-fir-beech forest soil in the North Tyrolean limestone Alps in Austria. The site received 12.1 kg nitrogen via wet and dry deposition. Fluxes of nitric oxide (NO) were measured by an automatic dynamic chamber system on an hourly basis over a two year period. Daily N2O emissions were obtained by a semi-automatic gas measuring system. In order to cover spatial variability biweekly manual measurements of N2O and CO2 emissions were carried out, additionally. For acquiring information on the effects of soil and meteorological conditions and of N-deposition on N-emissions we chose the autoregression procedure (time-series analysis) as our means of investigation. Hence, we could exclude the data's autocorrelation in the course of the time. We found that soil temperature, soil moisture and wet N-deposition followed by air temperature and precipitation were the most powerful influencing parameters effecting N-emissions. With these variables up to 89% of observed temporal variations of N-emissions could be explained. During the two-year investigation period between 2.5 and 3.5% of deposited N was reemitted in form of N2O whereas only 0.2% were emitted as NO. At our mountain forest site the main end-product of microbial activity processes was N2 and trace gases (N2O and NO) were only of minor importance.

scholarly journals Determination of Wheat Growth, Crop Coefficient (KC) and Water Stress Coefficient (Ks) under Different Salinity

2016 ◽  
Author(s):  
Meysam Abedinpour
Keyword(s):  
Water Stress ◽  
Crop Coefficient ◽  
Crop Growth ◽  
Growth Patterns ◽  
Wheat Crop ◽  
Growth Stages ◽  
Stress Coefficient ◽  
Salinity Levels ◽  
Water Stress Coefficient

A field experiment was conducted for determination of crop coefficient (KC) and water stress coefficient (Ks) for wheat crop under different salinity levels, during 2015-16. Complete randomized block design of five treatments were considered, i.e., 0.51 dS/m (fresh water) as a control treatment and other four saline water treatments (4, 6, 8 and 10 dS/m), for S1, S2, S3 and S4 with three replications. The results revealed that the water consumed by plants during the different crop growth stages follows the order of FW&gt;S1&gt;S2&gt;S3&gt;S4 salinity levels. According to the obtained results, the calculated values of crop coefficients significantly differed from those suggested by FAO No.56 for the crops. The Ks values clearly differ from one stage to another because the salt stress causes both osmotic stress, due to a decrease in the soil water potential, and ionic stress which the average values of water stress coefficient (Ks) follows this order; FW(1.0)=S1(1.0)&gt;S2(1.0)&gt;S3(0.93)&gt;S4(0.82). Overall, it was found the differences are attributed primarily to specific cultivar, the changes in local climatic conditions and seasonal differences in crop growth patterns. Thus, further studies are essential to determine the crop coefficient values under different variables, to make the best management practice (BMP) in agriculture.

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