Irrigation Needs in Ukraine According to Current Aridity Level

Lykhovyd, Pavlo

doi:10.12911/22998993/140478

Cited by 11 publications

(10 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The main goal of this study is to find out the best approach among common regression analysis techniques, used nowadays in crops' yield modeling, for the yield prediction of major crops, cultivated in the South of Ukraine, by the volumes of their water use. Such models are of great importance for sustainable crop production in the region, as it is one that belongs to the area of highly risky agriculture because of constant lack of natural water supply [14].…”

Section: Introductionmentioning

confidence: 99%

Choosing the Best Model for Crop Yield Prediction by the Means of Regression Analysis on the Example of “Crop Yield – Water Use” Simulations Through Best Subsets Approach

Lykhovyd¹,

Вожегова²,

Piliarska³

et al. 2023

Preprint

View full text Add to dashboard Cite

Crop yield prediction is relevant subject of current agricultural science. There are various mathematical approaches to crop yield prediction, and regression analysis, notwithstanding the fact that it is somewhat outdated, is still one of the most used ones in this purpose. The quality of predictive model is of great importance, and it is strongly dependent on the rational choice of the target function. The goal of this study is to find out the best regression model for winter wheat, soybeans, and grain corn yield prediction depending on the crops’ water use. The data on true crops’ yields and water use were collected within 1970-2020 at the experimental fields of the Institute of Climate-Smart Agriculture, Kherson region, Ukraine. In total, 145 data pairs were processed by the best subsets regression to find out the best model in terms of fitting quality (assessed by the Pearson’s coefficient of correlation), and prediction accuracy (assessed by the values of the minimum and maximum absolute errors and mean average percentage error). As a result, it was established that the best fitting quality for all the studied crops is attributed to cubic function, while the best accuracy is recorded for hyperbolic (reverse) function in soybeans (mean absolute percentage error is 12.27%), quadratic and hyperbolic functions in winter wheat (mean absolute percentage error is 20.54%), and cubic function in grain corn (mean absolute percentage error is 14.92%). To sum up the results of the study, it is recommended to apply cubic regression function for modeling crops’ yields in agricultural studies.

show abstract

Section: Introductionmentioning

confidence: 99%

Choosing the Best Model for Crop Yield Prediction by the Means of Regression Analysis on the Example of “Crop Yield – Water Use” Simulations Through Best Subsets Approach

Lykhovyd¹,

Вожегова²,

Piliarska³

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…Generally, Europe and Asia cover 78% of the total global wheat grain production [FAO-Stat, 2020]. Current global food crisis, connected with climate change and simultaneous deficit of natural resources and their deterioration (e.g., soil degradation, freshwater deficit, unfavorable weather phenomena), under the constant trend to the increase in global population implies a forecasted wheat consumption increase by 132 M mt/ year by 2050 [Lykhovyd, 2021;Erenstein et al, 2022]. To face the challenge of global starvation, steps should be taken to increase wheat production.…”

Section: Introductionmentioning

confidence: 99%

Choosing Important Traits for the Model of High-Yielding Winter Wheat Variety Based on the Results of Regional Ecological Varietal Testing

Lykhovyd¹

2023

J. Ecol. Eng.

View full text Add to dashboard Cite

Current study is devoted to the development of an ideotype of winter wheat variety for cultivation in the conditions of the South of Ukraine. The investigation is based on the results of regional ecological varietal testing, conducted in the Southern Steppe zone on the non-irrigated lands. Varietal traits, included in the study, embraced growing season duration, 1000 grains weight, plant height, and ear length. The results of the testing were further processed using statistical procedures of linear Pearson's correlation analysis and multiple regression analysis. As a result, the model of a winter wheat variety for the non-irrigated lands of the South of Ukraine was developed. The developed model is characterized by very high fitting quality (R 2 = 0.9476) and good prediction accuracy (MAPE = 23.27%). According to the model, the variety should be late ripening with moderate to high plant height to provide the highest grain yield. The trait of 1000 grains weight was found out to be unimportant. The main trait, providing for the grain yield increase, is growing season duration, which must be long enough. Further ecological varietal testing studies with inclusion of additional varietal traits, such as cold-resistance, drought-resistance, frostresistance, tolerance to diseases, etc., are to be conducted to extend the ideotype of winter wheat.

show abstract

“…The modern climate in most of the territory of Ukraine is semi-arid. It was found that 46.05% of acreage cannot provide sustainable crop production without irrigation, and 42.65% need irrigation to grow plants with high water use (Lykhovyd, 2021). The need to increase the production of vegetables against the background of a constant decline in soil quality and climate change to a more arid one, causes elevated interest in finding new measures that would provide plants with sufficient water.…”

Section: Introductionmentioning

confidence: 99%

Influence of Various Forms of Absorbent and Mulching Materials on the Yield of Vining Cucumber and Fruit Quality in the Forest-Steppe of Ukraine

Ternavskyi

Shchetyna

Slobodianyk

et al. 2022

Scientific Horizons

View full text Add to dashboard Cite

Against the background of global climate change, most of the territory of Ukraine today is semi-arid, which causes a decrease in the efficiency of the vegetable growing industry. Due to aridity and elevated temperatures in summer, the normal growth and development of plants, namely vining cucumber, is disrupted. The efficiency of artificial irrigation is also decreasing due to the rise in the price of fresh water and energy carriers for its supply to plants. Soil absorbents and the use of mulching can solve these issues. The purpose of this study was to investigate the effect of various forms of soil absorbent against the background of the use of various mulching materials of organic and synthetic origin on the productivity of vining cucumber. This study involved field, laboratory, statistical, and computational-analytical methods. Studies have established that upon mulching the soil with black polyethylene film together with the introduction of a soil absorbent in the form of a gel, phenological phases of growth and development occur most quickly in vining cucumber plants, and the fruiting period increases by 11 days compared to the control. The combination of film mulching and absorbent gel allowed increasing the height of the main stem by 15.2%, the number of leaves on the plant by 43.9%, and the leaf area by 26.5% compared to the control version. It was established that the highest commercial yield is provided by mulching the soil with a black film together with the introduction of an absorbent in the form of pellets and gel – 56.6-56.8 t/ha, which is 27.5-27.9% more than the control. The marketability of the yield was 99.2-99.4%. Cucumber fruits for mulching with a film and applying an absorbent in the form of a gel had a high content of dry matter (5.3%) and the sum of sugars (2.20%). Lowest nitrate level (N-NO3) in cucumber fruits provided mulching with black agrofibre without an absorbent (53.0 mg/kg)

show abstract

Irrigation Needs in Ukraine According to Current Aridity Level

Cited by 11 publications

References 10 publications

Choosing the Best Model for Crop Yield Prediction by the Means of Regression Analysis on the Example of “Crop Yield – Water Use” Simulations Through Best Subsets Approach

Choosing the Best Model for Crop Yield Prediction by the Means of Regression Analysis on the Example of “Crop Yield – Water Use” Simulations Through Best Subsets Approach

Choosing Important Traits for the Model of High-Yielding Winter Wheat Variety Based on the Results of Regional Ecological Varietal Testing

Influence of Various Forms of Absorbent and Mulching Materials on the Yield of Vining Cucumber and Fruit Quality in the Forest-Steppe of Ukraine

Contact Info

Product

Resources

About