scholarly journals Assessing the Effects of Agronomic Management Practices on Soybean (Glycine max L.) Post-Grain Harvest Residue Quality in the Lower Mississippi Delta

Plants ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 1337
Author(s):  
Srinivasa R. Pinnamaneni ◽  
Saseendran S. Anapalli
Keyword(s):  
Management Practices ◽  
Crop Residues ◽  
Soybean Seed ◽  
Grain Filling ◽  
Quality Parameters ◽  
Neutral Detergent Fiber ◽  
Net Energy ◽  
Residue Quality ◽  
Climate Conditions ◽  
Harvest Residue

Livestock producers often resort to either baling or grazing of crop residues due to high hay prices and reduced supply of other forages and silage in the markets. Soil-water-crop management practices can affect residue nutrient qualities for its use as cattle feedstock. A two-year study (2018–2019) was conducted to investigate the effects of irrigation (AI, all row-irrigation; ARI, alternate row irrigation; and RF, rainfed) and planting pattern, PP (SR, single row; and TR, twin-row) on soybean (maturity group IV cv. 31RY45 Dyna-Gro) post-grain harvest residue quality such as crude protein (CP), acid detergent fiber (ADF), neutral detergent fiber (NDF), acid detergent lignin (ADL), net energy for maintenance (NEM), net energy for gain (NEG), net energy for lactation (NEL), total digestible nutrients (TDN), and relative feed value (RFV). Irrigation has a significant effect on CP, ADF, NDF, and TDN while PP affected only NDF. All the above parameters were significantly affected except NEM by the contrasting climate conditions, particularly during July through August coinciding with early crop reproductive stages and maturity. The RFV values ranged from 70.4 to 81.6 and this lower range was attributable to nutrient translocation to seeds and higher lignification during plant senescence towards the grain filling stage of the crop as good quality hay records over 120 RFV. These results indicate that both irrigation and weather during soybean seed development can alter post-grain harvest residue quality parameters, thereby playing critical roles in its RFV.

scholarly journals Mathematical Modelling as a Tool for the Assessment of Impact of Thermodynamics on the Algal Growth in Dam Reservoirs – Case Study of the Goczalkowice Reservoir

2018 ◽  
Vol 29 (1) ◽  
pp. 21-29
Author(s):  
Rafał Ulańczyk ◽  
Czesław Kliś ◽  
Damian Absalon ◽  
Marek Ruman
Keyword(s):  
Chlorophyll A ◽  
Management Practices ◽  
Algal Growth ◽  
Quality Parameters ◽  
Ocean Model ◽  
Climate Conditions ◽  
Water Mixing ◽  
Dam Reservoirs ◽  
Basin Morphology ◽  
Coastal Ocean Model

Abstract Depending on climate conditions, bathymetry, basin morphology, management practices and other factors, some reservoirs are more or less prone to stratification, which can strongly affect both chemical and biological status of water. In the Goczalkowice Reservoir (the biggest dam reservoir in the south of Poland), water quality parameters, such as chlorophyll a concentration, change very dynamically. In the presented study, the Estuary, Lake and Coastal Ocean Model (ELCOM) was applied to simulate water thermodynamics in a period of summer and autumn when the highest concentrations of chlorophyll a were observed, based on the continuous water monitoring in the ZiZOZap project (Łaszczyca et al., 2011). The purpose of the application of ELCOM was to simulate the thermal stratification in the reservoir and to prepare a basis for analyses of the relationship between water thermodynamics and quality. Simulations allowed the identification of several short water mixing events in summer and the final mixing event at the end of summer. The study also included the first application of model results to analyse the relation of changes in water temperature with observed concentration of chlorophyll a (ChlA). Analysis confirmed that each water mixing event was followed by a significant increase in ChlA concentration.

scholarly journals The Effects of Management (Tillage, Fertilization, Plant Density) on Soybean Yield and Quality in a Three-Year Experiment under Transylvanian Plain Climate Conditions

Land ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 200
Author(s):  
Felicia Chețan ◽  
Cornel Chețan ◽  
Ileana Bogdan ◽  
Adrian Ioan Pop ◽  
Paula Ioana Moraru ◽  
...  
Keyword(s):  
Plant Density ◽  
Conventional Tillage ◽  
Quality Parameters ◽  
Soil Tillage ◽  
Reduced Tillage ◽  
Seeding Rate ◽  
Soybean Yield ◽  
Climate Conditions ◽  
Yield And Quality ◽  
Tillage System

The regional agroecological conditions, specific to the Transylvanian Plain, are favorable to soybean crops, but microclimate changes related to global warming have imposed the need for agrotechnical adaptive measures in order to maintain the level of soybean yield. In this study, we consider the effect of two soil tillage systems, the seeding rate, as well as the fertilizer dosage and time of application on the yield and quality of soybean crops. A multifactorial experiment was carried out through the A × B × C × D − R: 3 × 2 × 3 × 3 − 2 formula, where A represents the year (a1, 2017; a2, 2018; and a3, 2019); B represents the soil tillage system (b1, conventional tillage with mouldboard plough; b2, reduced tillage with chisel cultivator); C represents the fertilizer variants (c1, unfertilized; c2, one single rate of fertilization: 40 kg ha−1 of nitrogen + 40 kg ha−1 of phosphorus; and c3, two rates of fertilization: 40 kg ha−1 of nitrogen + 40 kg ha−1 of phosphorus (at sowing) + 46 kg ha−1 of nitrogen at V3 stage); D represents the seeding rate (1 = 45 germinating grains (gg) m−2; d2 = 55 gg m−2; and d3 = 65 gg m−2); and R represents the replicates (r1 = the first and r2 = the second). Tillage had no effect, the climate specific of the years and fertilization affected the yield and the quality parameters. Regarding the soybean yield, it reacted favorably to a higher seeding rate (55–65 gg m−2) and two rates of fertilization. The qualitative characteristics of soybeans are affected by the fertilization rates applied to the crop, which influence the protein and fiber content in the soybean grains. Higher values of protein content were recorded with a reduced tillage system, i.e., 38.90 g kg−1 DM in the variant with one single rate of fertilization at a seeding rate of 45 gg per m−2 and 38.72 g kg−1 DM in the variant with two fertilizations at a seeding rate of 65 gg m−2.

scholarly journals Comparison of Forecasting Models for Real-Time Monitoring of Water Quality Parameters Based on Hybrid Deep Learning Neural Networks

Water ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 1547
Author(s):  
Jian Sha ◽  
Xue Li ◽  
Man Zhang ◽  
Zhong-Liang Wang
Keyword(s):  
Neural Network ◽  
Water Quality ◽  
Deep Learning ◽  
Real Time ◽  
Best Management Practices ◽  
Input Data ◽  
Management Practices ◽  
Quality Parameters ◽  
Water Quality Parameters ◽  
Real Time Monitoring

Accurate real-time water quality prediction is of great significance for local environmental managers to deal with upcoming events and emergencies to develop best management practices. In this study, the performances in real-time water quality forecasting based on different deep learning (DL) models with different input data pre-processing methods were compared. There were three popular DL models concerned, including the convolutional neural network (CNN), long short-term memory neural network (LSTM), and hybrid CNN–LSTM. Two types of input data were applied, including the original one-dimensional time series and the two-dimensional grey image based on the complete ensemble empirical mode decomposition algorithm with adaptive noise (CEEMDAN) decomposition. Each type of input data was used in each DL model to forecast the real-time monitoring water quality parameters of dissolved oxygen (DO) and total nitrogen (TN). The results showed that (1) the performances of CNN–LSTM were superior to the standalone model CNN and LSTM; (2) the models used CEEMDAN-based input data performed much better than the models used the original input data, while the improvements for non-periodic parameter TN were much greater than that for periodic parameter DO; and (3) the model accuracies gradually decreased with the increase of prediction steps, while the original input data decayed faster than the CEEMDAN-based input data and the non-periodic parameter TN decayed faster than the periodic parameter DO. Overall, the input data preprocessed by the CEEMDAN method could effectively improve the forecasting performances of deep learning models, and this improvement was especially significant for non-periodic parameters of TN.

scholarly journals Temperature Effects on Electricity and Gas Consumption: Empirical Evidence from Mexico and Projections under Future Climate Conditions

2020 ◽  
Vol 13 (1) ◽  
pp. 305
Author(s):  
W.J. Wouter Botzen ◽  
Tim Nees ◽  
Francisco Estrada
Keyword(s):  
Climate Change ◽  
Energy Consumption ◽  
Fixed Effects ◽  
Electricity Consumption ◽  
Energy Transition ◽  
Net Energy ◽  
Economic Costs ◽  
Climate Conditions ◽  
Linear Relationships ◽  
Gas Consumption

Fixed effects panel models are used to estimate how the electricity and gas consumption of various sectors and residents relate to temperature in Mexico, while controlling for the effects of income, manufacturing output per capita, electricity and gas prices and household size. We find non-linear relationships between energy consumption and temperature, which are heterogeneous per state. Electricity consumption increases with temperature, and this effect is stronger in warm states. Liquified petroleum gas consumption declines with temperature, and this effect is slightly stronger in cold states. Extrapolations of electricity and gas consumption under a high warming scenario reveal that electricity consumption by the end of the century for Mexico increases by 12%, while gas consumption declines with 10%, resulting in substantial net economic costs of 43 billion pesos per year. The increase in net energy consumption implies greater efforts to comply with the mitigation commitments of Mexico and requires a much faster energy transition and substantial improvements in energy efficiency. The results suggest that challenges posed by climate change also provide important opportunities for advancing social sustainability goals and the 2030 Agenda for Sustainable Development. This study is part of Mexico’s Sixth National Communication to the United Nations Framework Convention on Climate Change.

scholarly journals Establishment of Regional Phytoremediation Buffer Systems for Ecological Restoration in the Great Lakes Basin, USA. I. Genotype × Environment Interactions

Forests ◽  
2021 ◽  
Vol 12 (4) ◽  
pp. 430 ◽  
Author(s):  
Ronald S. Zalesny ◽  
Andrej Pilipović ◽  
Elizabeth R. Rogers ◽  
Joel G. Burken ◽  
Richard A. Hallett ◽  
...  
Keyword(s):  
Great Lakes ◽  
Best Management Practices ◽  
Management Practices ◽  
Recurrent Selection ◽  
Lake Michigan ◽  
Great Lakes Basin ◽  
Annual Increment ◽  
Climate Conditions ◽  
The North ◽  
Local Soil

Poplar remediation systems are ideal for reducing runoff, cleaning groundwater, and delivering ecosystem services to the North American Great Lakes and globally. We used phyto-recurrent selection (PRS) to establish sixteen phytoremediation buffer systems (phyto buffers) (buffer groups: 2017 × 6; 2018 × 5; 2019 × 5) throughout the Lake Superior and Lake Michigan watersheds comprised of twelve PRS-selected clones each year. We tested for differences in genotypes, environments, and their interactions for health, height, diameter, and volume from ages one to four years. All trees had optimal health. Mean first-, second-, and third-year volume ranged from 71 ± 26 to 132 ± 39 cm3; 1440 ± 575 to 5765 ± 1132 cm3; and 8826 ± 2646 to 10,530 ± 2110 cm3, respectively. Fourth-year mean annual increment of 2017 buffer group trees ranged from 1.1 ± 0.7 to 7.8 ± 0.5 Mg ha−1 yr−1. We identified generalist varieties with superior establishment across a broad range of buffers (‘DM114’, ‘NC14106’, ‘99038022’, ‘99059016’) and specialist clones uniquely adapted to local soil and climate conditions (‘7300502’, ‘DN5’, ‘DN34’, ‘DN177’, ‘NM2’, ‘NM5’, ‘NM6’). Using generalists and specialists enhances the potential for phytoremediation best management practices that are geographically robust, being regionally designed yet globally relevant.

scholarly journals Irrigation with Coalbed Methane Co-Produced Water Reduces Forage Yield and Increase Soil Sodicity However Does Not Impact Forage Quality

2021 ◽  
Vol 13 (6) ◽  
pp. 3545
Author(s):  
Shital Poudyal ◽  
Valtcho D. Zheljazkov
Keyword(s):  
Fresh Water ◽  
Coalbed Methane ◽  
Produced Water ◽  
Forage Quality ◽  
Dry Weight ◽  
Quality Parameters ◽  
Forage Yield ◽  
Neutral Detergent Fiber ◽  
Forage Crops ◽  
Feed Value

The extraction of coalbed methane produces a significant amount of coalbed methane co-produced water (CBMW). Coalbed methane co-produced water is often characterized by high levels of pH, total dissolved solids (TDS), sodium (Na) and bicarbonate (HCO−3) and if used for irrigation without treatment, it may be detrimental to the surrounding soil, plants and environment. CBMW ideally should be disposed of by reinjection into the ground, but because of the significant cost associated, CBMW is commonly discharged onto soil or water surfaces. This study was conducted to elucidate the effect of the CBMW (with TDS value of <1500 ppm) at various blending ratios with fresh water on the yield and quality of representative forage crops [i.e., oat (Avena sativa) and alfalfa (Medicago sativa)]. Various blends of CBMW with fresh water reduced fresh and dry weight of alfalfa by 21.5–32% and 13–30%, respectively and fresh and dry weight of oat by 0–17% and 0–14%, respectively. Irrigation with various blends of CBMW and fresh water increased soil pH and soil sodium adsorption ratio. However, forage quality parameters such as crude protein (CP), acid detergent fiber (ADF), neutral detergent fiber (NDF), total digestible nutrients (TDN) and relative feed value (RFV) of both forage crops remained unaffected.

Soil respiration under different agricultural land use types in Croatia

2021 ◽  
Author(s):  
Darija Bilandžija ◽  
Marija Galić ◽  
Željka Zgorelec
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Soil Respiration ◽  
Management Practices ◽  
Agricultural Land ◽  
Ghg Emissions ◽  
Paris Agreement ◽  
Energy Crop ◽  
Climate Conditions ◽  
Uncertainty Estimates

&lt;p&gt;In order to mitigate climate change and reduce the anthropogenic greenhouse gas (GHG) emissions, the Kyoto protocol has been adopted in 1997 and the Paris Agreement entered into force in 2016. The Paris Agreement have ratified 190 out of 197 Parties of the United Nations Framework Convention on Climate Change (UNFCCC) and Croatia is one of them as well. Each Party has obliged regularly to submit the national inventory report (NIR) providing the information on the national anthropogenic GHG emissions by sources and removals by sinks to the UNFCCC. Reporting under the NIR is divided into six categories / sectors, and one of them is land use, land use change and forestry (LULUCF) sector, where an issue of uncertainty estimates on carbon emissions and removals occurs. As soil respiration represents the second-largest terrestrial carbon flux, the national studies on soil respiration can reduce the uncertainty and improve the estimation of country-level carbon fluxes. Due to the omission of national data, the members of the University of Zagreb Faculty of Agriculture, Department of General Agronomy have started to study soil respiration rates in 2012, and since then many different studies on soil respiration under different agricultural land uses (i.e. annual crops, energy crop and vineyard), management practices (i.e. tillage and fertilization) and climate conditions (i.e. continental and mediterranean) in Croatia have been conducted. The obtained site specific results on field measurements of soil carbon dioxide concentrations by &lt;em&gt;in situ&lt;/em&gt; closed static chamber method will be presented in this paper.&lt;/p&gt;

Nutritional recommendations and management practices adopted by feedlot cattle nutritionists: the 2016 Brazilian survey

2019 ◽  
Vol 99 (2) ◽  
pp. 392-407 ◽  
Author(s):  
Ana C.J. Pinto ◽  
Danilo D. Millen
Keyword(s):  
Management Practices ◽  
Energy Content ◽  
Primary Source ◽  
Feedlot Cattle ◽  
Neutral Detergent Fiber ◽  
Nutritional Management ◽  
Finishing Diets ◽  
Feeding Management ◽  
Grain Processing ◽  
Management Recommendations

The feedlot industry in Brazil is still evolving, and some nutritional management recommendations adopted by nutritionists changes from year to year. The main objective of this survey was to provide a snapshot of current nutritional management practices adopted in Brazilian feedlots. The 33 nutritionists surveyed were responsible for approximately 4 228 254 animals. Corn remained as the primary source of grain used in feedlot diets by the participants, whereas fine grinding was the primary grain processing method. Corn silage was the primary roughage source indicated by nutritionists, and for the first time, physically effective neutral detergent fiber was the preferred fiber analysis method. The average dietary fat recommended was 50 g kg−1 of dry matter, which is about 10% higher than values reported in previous surveys. The use of truck-mounted mixers increased, which may have increased the percentage of feedlots using programmed feed delivery per pen, allowing the increase of energy content of finishing diets. Feedlots did not increase their capacity and nutritionists reported an improvement in feeding management. Results reported in the current study provide a baseline that can be used to improve practices and aid in the development of feedlot industry in Brazil and similar tropical climates.

scholarly journals Yield and quality of Maralfalfa forage during long days on three dairy farms in northern Puerto Rico

1969 ◽  
Vol 98 (2) ◽  
pp. 169-177
Author(s):  
Rafael Ramos-Santana ◽  
Yamil Quijano-Cabrera ◽  
Raúl Macchiavelli
Keyword(s):  
Puerto Rico ◽  
Dry Matter ◽  
Forage Quality ◽  
Neutral Detergent Fiber ◽  
Net Energy ◽  
Regression Equations ◽  
Dry Matter Yield ◽  
Yield And Quality ◽  
Harvest Intervals

An experiment was conducted to evaluate the dry matter yield and quality performance of Maralfalfa forage obtained at six harvest intervals (HI; 40, 50, 60, 70, 80, 90 d) on three dairies in northern Puerto Rico during the long day season. The 40-day harvest interval was significantly (P < 0.05) inferior in dry matter yield to those of 60, 80, and 90 days; no significant (P < 0.05) differences in yield were observed among intervals of 40, 50 and 70 days. The 40-day interval showed the highest forage quality as indicated by crude protein content, digestibility in vitro of dry matter and neutral detergent fiber, and estimated net energy, index of relative forage quality and theoretical milk production. Although significant (P < 0.05) differences were observed in some of these criteria between 40- and 50-day harvest intervals, the latter maintained a good nutritional value in contrast to drastic losses in quality observed with the longer harvest intervals under study. The simple regression equations between digestibility in vitro of dry matter and of neutral detergent fiber versus harvest interval showed a decrease in digestibility of 2.7 and 3.0 percentage points for each additional 10 days of harvest interval, respectively.

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