scholarly journals Evaluating and improving corn nitrogen fertilizer recommendation tools across the U.S. Midwest

2018 ◽  
Author(s):  
◽  
Curtis Joel Ransom
Keyword(s):  
Regression Model ◽  
Linear Relationship ◽  
Fertilizer Application ◽  
Development Stage ◽  
Elastic Net ◽  
N Fertilizer ◽  
Available N ◽  
Weather Information ◽  
Fertilizer Recommendation ◽  
Wide Range

Determining which corn (Zea mays L.) nitrogen (N) recommendation tools best predict the economically optimal N rate (EONR) would be valuable for maximizing profits and minimizing environmental consequences. The objectives of this research were to evaluate the performance of publicly-available N fertilizer recommendation tools across a wide range of soil and weather environments for 1) prescribing EONR for planting and split N fertilizer applications, 2) improve understanding of the economic and environmental impact of these tools, 3) improve N recommendation tools by integrating soil and weather information, and 4) improve N recommendation tools by combing multiple tools. The evaluation was conducted on 49 N response trials that spanned eight states and three growing seasons. Soil and plant samples, weather, and management information were collected using standardized procedures to allow for a side-by-side comparison of tools. Tool N recommendations were for fertilizer applications either atplanting or an inseason applied at V9 corn development stage. Only 11of 31 tool recommendations were weakly related to EONR (P [less than or equal to] 0.10 and r[2] [less than or equal to] 0.24). These tools related to EONR resulted in only 21-47% of sites within [plus or minus]30 kg N ha-1 of EONR. When considering partial profit for these 11 tools the average profitability relative to EONR range from -$56 to -155 ha-1. An environmental assessment of these 11 tools found there was no difference found between tools, with environmental costs ranging from -$49 to 55 ha-1 relative to EONR. Using an elastic net regression model to incorporate soil and weather information helped to improve six N recommendation tools. This improvement resulted in a stronger linear relationship with EONR (r[2] [less than or equal to] 0.20 but [less than or equal to] 0.39; P less than 0.01) and resulted in [greater than or equal to] 35% but [less than or equal to] 55 % of the sites within [plus or minus] 30 kg N ha-1 of EONR. Using other ways to improve tools included combing two or three unique tools. The best results for an at-planting N fertilizer recommendation occurred when three at-planting N recommendation tools were combined with all interactions included in the elastic net regression model. This combined recommendation tool had an improved significant linear relationship with EONR (r[2] = 0.46; P less than 0.001) compared with the best tool evaluated alone (an increase in r2 of 0.27). The best combination of N recommendation tools for a split N fertilizer application occurred when using three tools with a decision tree (r[2] = 0.45; P less than 0.001) over the best tool evaluated alone (an increase in r[2] of 0.18). However, while improvements to these publicly-available tools were noteworthy, over half of the variation in EONR was still unexplained. This was not surprising since many other factors that impact soil-crop N dynamics are unconsidered, including factors that occur after a sidedress N application.

scholarly journals Improving Prediction of Peroxide Value of Edible Oils Using Regularized Regression Models

Molecules ◽  
2021 ◽  
Vol 26 (23) ◽  
pp. 7281
Author(s):  
William E. Gilbraith ◽  
J. Chance Carter ◽  
Kristl L. Adams ◽  
Karl S. Booksh ◽  
Joshua M. Ottaway
Keyword(s):  
Regression Model ◽  
Ridge Regression ◽  
Near Infrared ◽  
Edible Oils ◽  
Reference Method ◽  
Elastic Net ◽  
Spectral Information ◽  
Pls Regression ◽  
Spectral Window ◽  
Wide Range

We present four unique prediction techniques, combined with multiple data pre-processing methods, utilizing a wide range of both oil types and oil peroxide values (PV) as well as incorporating natural aging for peroxide creation. Samples were PV assayed using a standard starch titration method, AOCS Method Cd 8-53, and used as a verified reference method for PV determination. Near-infrared (NIR) spectra were collected from each sample in two unique optical pathlengths (OPLs), 2 and 24 mm, then fused into a third distinct set. All three sets were used in partial least squares (PLS) regression, ridge regression, LASSO regression, and elastic net regression model calculation. While no individual regression model was established as the best, global models for each regression type and pre-processing method show good agreement between all regression types when performed in their optimal scenarios. Furthermore, small spectral window size boxcar averaging shows prediction accuracy improvements for edible oil PVs. Best-performing models for each regression type are: PLS regression, 25 point boxcar window fused OPL spectral information RMSEP = 2.50; ridge regression, 5 point boxcar window, 24 mm OPL, RMSEP = 2.20; LASSO raw spectral information, 24 mm OPL, RMSEP = 1.80; and elastic net, 10 point boxcar window, 24 mm OPL, RMSEP = 1.91. The results show promising advancements in the development of a full global model for PV determination of edible oils.

A meta-analysis of sugarbeet yield responses to nitrogen fertilizer measured in England since 1980

2009 ◽  
Vol 147 (3) ◽  
pp. 287-301 ◽  
Author(s):  
K. W. JAGGARD ◽  
A. QI ◽  
M. J. ARMSTRONG
Keyword(s):  
Nitrogen Fertilizer ◽  
Meta Analysis ◽  
Peat Soil ◽  
Summer Rainfall ◽  
Sowing Date ◽  
Fertilizer Application ◽  
N Fertilizer ◽  
Fibrous Root ◽  
Mineral N ◽  
Available N

SUMMARYThe data from 161 experiments testing the response of sugarbeet yield to nitrogen fertilizer were assembled in a database. Three commonly used N response models (Mitscherlich, linear plus exponential and bilinear) were fitted to each set of fertilizer application rates and the models were then assessed on how well they fitted all the data. The bilinear model was judged the most appropriate model for fitting to beet root yield adjusted to a standard sugar concentration. The optimum N application was determined for each experiment. Attempts were then made to correlate these optima with factors associated with the site and the season (winter rainfall, soil texture, amount of soil mineral N at sowing, sowing date, summer rainfall and harvest date). Beet grown in peat soil never responded significantly to any applied N fertilizer and neither did crops treated recently with organic manure supplying large amounts (>150 kg N/ha) of available N. Variation in N optima between other sites could not be explained by factors that could be used to predict the amount of fertilizer to apply. In the absence of any method to make reliable predictions of variations in fertilizer need, the most economical uniform amount was calculated. At present fertilizer prices and beet values, this amount is between 100 and 110 kg N/ha. It is possible that the N fertilizer need of beet crops does not vary predictably because this variation is an experimental error. The crop needs a reasonably standard application of fertilizer because much N has to be taken up early in the crop's development, rapidly and predominantly from the topsoil that, at this stage, contains most of the small fibrous root system.

Asymptotic for LS estimators in the EV regression model for dependent errors

Filomat ◽  
2017 ◽  
Vol 31 (15) ◽  
pp. 4845-4856
Author(s):  
Konrad Furmańczyk
Keyword(s):  
Regression Model ◽  
Functional Dependence ◽  
Dependent Data ◽  
Errors In Variables ◽  
Mixing Conditions ◽  
Asymptotic Results ◽  
Dependence Measure ◽  
Wide Range ◽  
Ev Regression Model ◽  
Linear And Nonlinear

We study consistency and asymptotic normality of LS estimators in the EV (errors in variables) regression model under weak dependent errors that involve a wide range of linear and nonlinear time series. In our investigations we use a functional dependence measure of Wu [16]. Our results without mixing conditions complete the known asymptotic results for independent and dependent data obtained by Miao et al. [7]-[10].

scholarly journals Nitrogen Leaching and Nitrogen Balance under Differing Nitrogen Fertilization for Sugarcane Cultivation on a Subtropical Island

Water ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 740
Author(s):  
Ken Okamoto ◽  
Shinkichi Goto ◽  
Toshihiko Anzai ◽  
Shotaro Ando
Keyword(s):  
N Uptake ◽  
Fertilizer Application ◽  
Application Rate ◽  
N Fertilizer ◽  
N Leaching ◽  
N Recovery ◽  
N Application ◽  
Fertilizer Application Rate ◽  
Sugarcane Yield ◽  
Cropping Seasons

Fertilizer application during sugarcane cultivation is a main source of nitrogen (N) loads to groundwater on small islands in southwestern Japan. The aim of this study was to quantify the effect of reducing the N fertilizer application rate on sugarcane yield, N leaching, and N balance. We conducted a sugarcane cultivation experiment with drainage lysimeters and different N application rates in three cropping seasons (three years). N loads were reduced by reducing the first N application rate in all cropping seasons. The sugarcane yields of the treatment to which the first N application was halved (T2 = 195 kg ha−1 N) were slightly lower than those of the conventional application (T1 = 230 kg ha−1 N) in the first and third seasons (T1 = 91 or 93 tons ha−1, T2 = 89 or 87 tons ha−1). N uptake in T1 and T2 was almost the same in seasons 1 (186–188 kg ha−1) and 3 (147–151 kg ha−1). Based on the responses of sugarcane yield and N uptake to fertilizer reduction in two of the three years, T2 is considered to represent a feasible fertilization practice for farmers. The reduction of the first N fertilizer application reduced the underground amounts of N loads (0–19 kg ha−1). However, application of 0 N in the first fertilization would lead to a substantial reduction in yield in all seasons. Reducing the amount of N in the first application (i.e., replacing T1 with T2) improved N recovery by 9.7–11.9% and reduced N leaching by 13 kg ha−1. These results suggest that halving the amount of N used in the first application can improve N fertilizer use efficiency and reduce N loss to groundwater.

Energy Harvesting Under Harsh Conditions for the Oil & Gas Upstream Industry

2021 ◽  
Author(s):  
José Correia ◽  
Cátia Rodrigues ◽  
Ricardo Esteves ◽  
Ricardo Cesar Bezerra de Melo ◽  
José Gutiérrez ◽  
...  
Keyword(s):  
Energy Harvesting ◽  
Oil And Gas ◽  
Electrical Energy ◽  
Development Stage ◽  
Gas Extraction ◽  
Power Monitoring ◽  
Operational Conditions ◽  
Wide Range ◽  
First Time ◽  
Harsh Conditions

Abstract Environmental and safety sensing is becoming of high importance in the oil and gas upstream industry. However, present solutions to feed theses sensors are expensive and dangerous and there is so far no technology able to generate electrical energy in the operational conditions of oil and gas extraction wells. In this paper it is presented, for the first time in a relevant environment, a pioneering energy harvesting technology based on nanomaterials that takes advantage of fluid movement in oil extraction wells. A device was tested to power monitoring systems with locally harvested energy in harsh conditions environment (pressures up to 50 bar and temperatures of 50ºC). Even though this technology is in an early development stage this work opens a wide range of possible applications in deep underwater environments and in Oil and Gas extraction wells where continuous flow conditions are present.

Seed germination biology of sweet acacia (Vachellia farnesiana) and response of its seedlings to herbicides

Weed Science ◽  
2021 ◽  
pp. 1-19
Author(s):  
Bhagirath S. Chauhan ◽  
Shane Campbell ◽  
Victor J. Galea
Keyword(s):  
Sodium Chloride ◽  
Seed Germination ◽  
Development Stage ◽  
Hot Water ◽  
Control Treatment ◽  
Similar Species ◽  
Weed Species ◽  
Physical Dormancy ◽  
Seed Biology ◽  
Wide Range

Abstract Sweet acacia [Vachellia farnesiana (L.) Willd.]is a problematic thorny weed species in several parts of Australia. Knowledge of its seed biology could help to formulate weed management decisions for this and other similar species. Experiments were conducted to determine the effect of hot water (scarification), alternating temperatures, light, salt stress, and water stress on seed germination of two populations of V. farnesiana and to evaluate the response of its young seedlings (the most sensitive development stage) to commonly available POST herbicides in Australia. Both populations behaved similarly to all the environmental factors and herbicides; therefore, data were pooled over the populations. Seeds immersed in hot water at 90 C for 10 min provided the highest germination (88%), demonstrating physical dormancy in this species. Seeds germinated at a wide range of alternating day/night temperatures from 20/10 C (35%) to 35/25 C (90%) but no seeds germinated at 15/5 C. Germination was not affected by light, suggesting that seeds are nonphotoblastic and can germinate under a plant canopy or when buried in soil. Germination was not affected by sodium chloride concentrations up to 20 mM and about 50% of seeds could germinate at 160 mM sodium chloride, suggesting its high salt tolerance ability. Germination was only 13% at −0.2 MPa osmotic potential and no seeds germinated at −0.4 MPa, suggesting that V. farnesiana seeds may remain ungerminated until moisture conditions have become conducive for germination. A number of POST herbicides, including 2,4-D + picloram, glufosinate, paraquat and saflufenacil, provided >85% control of biomass of young seedlings compared with the nontreated control treatment. Knowledge gained from this study will help to predict the potential spread of V. farnesiana in other areas and help to integrate herbicide use with other management strategies.

scholarly journals Nutrient Management Programs, Nitrogen Fertilizer Practices, and Groundwater Quality in Nebraska’s Central Platte Valley (U.S.), 1989–1998

2001 ◽  
Vol 1 ◽  
pp. 750-757 ◽  
Author(s):  
Stan Daberkow ◽  
Harold Taylor ◽  
Noel Gollehon ◽  
Milt Moravek
Keyword(s):  
Irrigation Water ◽  
Fertilizer Application ◽  
Management Program ◽  
N Fertilizer ◽  
N Availability ◽  
Modest Improvement ◽  
Total N ◽  
Drinking Water Standard ◽  
Irrigation Water Use ◽  
Farmer Behavior

Given the societal concern about groundwater pollution from agricultural sources, public programs have been proposed or implemented to change farmer behavior with respect to nutrient use and management. However, few of these programs designed to change farmer behavior have been evaluated due to the lack of detailed data over an appropriate time frame. The Central Platte Natural Resources District (CPNRD) in Nebraska has identified an intensively cultivated, irrigated area with average groundwater nitrate-nitrogen (N) levels about double the EPA’s safe drinking water standard. The CPNRD implemented a joint education and regulatory N management program in the mid-1980s to reduce groundwater N. This analysis reports N use and management, yield, and groundwater nitrate trends in the CPNRD for nearly 3000 continuous-corn fields from 1989 to 1998, where producers faced limits on the timing of N fertilizer application but no limits on amounts. Groundwater nitrate levels showed modest improvement over the 10 years of this analysis, falling from the 1989–1993 average of 18.9 to 18.1 mg/l during 1994–1998. The availability of N in excess of crop needs was clearly documented by the CPNRD data and was related to optimistic yield goals, irrigation water use above expected levels, and lack of adherence to commercial fertilizer application guidelines. Over the 10-year period of this analysis, producers reported harvesting an annual average of 9729 kg/ha, 1569 kg/ha (14%) below the average yield goal. During 1989�1998, producers reported annually applying an average of 162.5 kg/ha of commercial N fertilizer, 15.7 kg/ha (10%) above the guideline level. Including the N contribution from irrigation water, the potential N contribution to the environment (total N available less estimated crop use) was estimated at 71.7 kg/ha. This is an estimate of the nitrates available for denitrification, volatilization, runoff, future soil N, and leaching to groundwater. On average, between 1989–1993 and 1994–1998, producers more closely followed CPNRD N fertilizer recommendations and increased their use of postemerge N applications � an indication of improved synchrony between N availability and crop uptake.

scholarly journals DOSES AND SPLIT NITROGEN FERTILIZER APPLICATIONS ON THE PRODUCTIVITY AND QUALITY OF ARUGULA1

2021 ◽  
Vol 34 (4) ◽  
pp. 824-829
Author(s):  
CAMILA SENO NASCIMENTO ◽  
CAROLINA SENO NASCIMENTO ◽  
ARTHUR BERNARDES CECÍLIO FILHO
Keyword(s):  
Nutrient Management ◽  
Block Design ◽  
Fertilizer Application ◽  
Additional Treatment ◽  
N Fertilizer ◽  
Nitrate Content ◽  
Management Technique ◽  
Maximum Height ◽  
N Losses ◽  
Negative Environmental Impact

ABSTRACT Splitting nitrogen (N) fertilizer application can be an efficient nutrient management technique to improve productivity and plant quality, as well as to reduce the negative environmental impact caused by N losses. In this context, the present study investigated how the management of N affects the agronomic characteristics of field-grown arugula plants. Nine treatments were assessed in a randomized complete block design, in a 4 x 2 + 1 factorial scheme, with three replicates. The evaluated factors were doses of N (60, 120, 180 and 240 kg N ha-1), split N fertilizer applications at side-dress (two and three times) and an additional treatment without a N supply. Maximum height was obtained with the application of 198 kg N ha-1. Nitrate content, fresh mass and productivity increased with increasing N doses. There was no effect of split N fertilizer applications on the characteristics evaluated. Therefore, the supply of 240 kg N ha-1 divided into two portions was considered as the best management strategy.

scholarly journals Online Fertilizer Recommendation System (OFRS): A Step Towards Precision Agriculture And Optimized Fertilizer Usage By Smallholder Farmers In Bangladesh

2020 ◽  
Vol 1 (4) ◽  
Author(s):  
M. A. Hossain ◽  
M. N. A. Siddique
Keyword(s):  
Precision Agriculture ◽  
Recommendation System ◽  
Smallholder Farmers ◽  
Fertilizer Application ◽  
Soil Test ◽  
Total Production ◽  
Soil Database ◽  
Fertilizer Recommendation ◽  
Fertilizer Recommendations ◽  
Input Cost

The recent progression and Green Revolution (approx. between the 1990s-2010s) in agriculture of Bangladesh resulted in an increase of total production despite yield-gap to ensure food security. But agriculture in Bangladesh is still backed-up by higher use of inputs (agrochemicals-fertilizers, pesticides; modern varieties, irrigation etc.) and inversion tillage. This conventional agrochemical-based smallholder agriculture may lead to soil and environmental degradation, soil acidification, and a decline in soil fertility. Therefore, it is significant to optimize input application in intensive agriculture, especially fertilizers. This paper introduces the potential online facilities of generating online fertilizer recommendations for smallholder farmers in Bangladesh to ensure proper usage of fertilizers and enable sustainable agricultural production. We also highlighted how the usage of fertilizers increased with an increase in total production over time. But the sustainability of production in the years to come still remain challenging. With the aim of sustainable crop production, reduction in the misuse of fertilizers and reduction of input cost by optimizing the present pattern of excessive fertilizer application, the Soil Resource Development Institute (SRDI) provides location-specific fertilizer recommendation through both the manual and soil test based interpretation of plant nutrients: soil database in Upzazila Nirdeshika and static laboratory soil analysis. Recently, SRDI developed web-based software named Online Fertilizer Recommendation System (OFRS). The system is capable of generating location-specific fertilizer recommendations for selected crops by analyzing the national soil database developed by this governmental institute. The software requires farmer field location, respective soil and land type, and crop type and variety information to generate crop-specific instant fertilizer recommendation. It was observed that by using fertilizer according to the recommended dose calculated on the basis of soil test values, farmers could harvest approx. 7-22% higher yield of different crops over usual farmers practice. If this system can be popularized and disseminated by effective agricultural extension, this would immensely contribute to the promotion of precision agriculture, input cost reduction and it would certainly enable us to optimize fertilizer application by the smallholder farmers in Bangladesh.

scholarly journals COMPARATIVE ANALYSIS OF DIFFERENT CRITERIA OF SITE STRUCTURAL STABILITY IN THE TIME SERIES

2019 ◽  
pp. 119-128
Author(s):  
Liliya Andreevna Landman ◽  
Andrei Vladimirovich Faddeenkov
Keyword(s):  
Time Series ◽  
Regression Model ◽  
Structural Changes ◽  
Least Squares Method ◽  
Complex Structure ◽  
Standard Normal Distribution ◽  
Regression Equations ◽  
Unknown Parameters ◽  
Chow Test ◽  
Wide Range

The concept of structure is used to describe a set of stable relations between the main parts of the object, which describe its integrity and identity, i.e, preserving the basic properties for a wide range of internal and external changes. This concept usually relates to the concepts of system and organization. The structure expresses a stable part of the system that is slightly changed during different reforms. Over the years structural changes take place because of active economic policy or as a result of spontaneous, uncontrollable processes. Therefore, it seems to be quite natural to find out whether there have been structural changes in the observation period, and to find them reflected in the specification of the model. The basic ideas of methods for determining structural changes in the time series dynamics have been considered, such as Chow test, Gujarati test and Poirier method. The power study was conducted for the three possible cases of change in time series trends. The random error was modeled according to the standard normal distribution. A linear multiple regression model with three independent variables was used as a time series model. Estimation of the vector of unknown parameters of the model was conducted using least squares method. For each of the three criteria the of test the null hypothesis about time series instability was carried out using the F -criterion, which involves finding the residual sum of squares of a regression model and analysis of correlation between its decline and the loss of degrees of freedom. It can be noted that Gujarati and Poirier equations have a more complex structure than equation of Chow test; however, using Chow test assumes estimation of the parameters of the three regression equations.

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