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001-es BibID:	BIBFORM095583
035-os BibID:	(cikkazonosító)1361 (WoS)000675934700001 (Scopus)85110324174
Első szerző:	Ezzat, Gaballa Kassem Ahmed (agrár)
Cím:	Deficit Irrigation Strategies on Tree Physiological and Chemical Properties: Treatment Effects, Prediction Based Model Analyses and Inter-Correlations / Ahmed Ezzat, Abdel-Moety Salama, Szilárd Szabó, Arshad Abdulkhalq Yaseen, Bianka Molnár, Imre J. Holb
Dátum:	2021
ISSN:	2073-4395
Megjegyzések:	Irrigation is a key factor for different physiological aspects of fruit trees. Therefore, such irrigation protocols that can save water consumption during irrigation and maintain fruit trees productivity are an essential goal especially under semiarid climate conditions. The aim of this 3-year apricot study was to investigate the effect of four deficit irrigation (DI) treatments (control, moderate regulated deficit irrigation: RDIm, severe RDI: RDIs and continuous DI: CDI) on 15 tree physiological properties (chilling requirement?CR, heat requirement?HR, days from end?dormancy until fruit harvest?DEDFH, sum of growing degree days?sGDD, total number of buds?TNB, number of flower buds?NFB, number of vegetative buds?NVB, starting date of flowering?SDF, number of opened flower buds?NOFB, flower bud abscission?FBA, fruit set?FS, seasonal vegetative growth?SVG, fruit number per tree?FNT, fruit weight?FW, fruit yield?FY), and on two tree chemical properties (total soluble carbohydrates?TSC and total proline content?TPC) on apricot cultivars ♭Ninfa' and ♭Canino' in Egypt. Results showed that both DI treatments and cultivars significantly influenced the values of CR, HR, TNB, SDF, NOFB, FS, SVG, FNT, FY, TSC, and TPC. Values of FBA were significantly affected by years and DI treatments, while sGDD by years and cultivars. Values of DEDFH, NFB, and FW were significantly influenced only by cultivars, while NVB only by DI treatments. The RDIm treatment gave the most acceptable values for most measured properties compared to the fully irrigated control treatment. Prediction based model analysis demonstrated that generalized linear models (GLMs) can be predictors for the measured tree properties in the DI treatments. The best goodness-of-fit of the predicted GLMs was reached for HR, NOFB, FS, SVG, FNT, TSC, and TPC. In all the four DI treatments, 22 pair-variables (TNB versus (vs.) NFB, TNB vs. NOFB, TNB vs. NOFB, NFB vs. NOFB, NFB vs. FNT, NFB vs. FY, NFB vs. FW, NOFB vs. SVG, NOFB vs. FNT, NOFB vs. FY, FS vs. FNT, FS vs. FY, SVG vs. FNT, SVG vs. FY, SVG vs. TSC, FNT vs. FY, FY vs. FW, CR vs. TSC, HR vs. TNB, HR vs. NFB, HR vs. FNT, HR vs. FY, and NOFB vs. FBA) correlated significantly in Pearson correlation and regression analyses. Principal component analyses explained 82% of the total variance and PC1, PC2, and PC3 explained 23, 21, and 15% of the total variance and correlated with the HR, TNB, FS, FNT and FY; FBA, SVG, TSC, and TPC; and NFB, NVB and NOFB, respectively, indicating strong connections among tree physiological and chemical properties. In conclusion, DI techniques using moderate water deficits can be managed successfully in apricot production under semiarid Mediterranean climate conditions such as the one in Egypt.
Tárgyszavak:	Agrártudományok Növénytermesztési és kertészeti tudományok idegen nyelvű folyóiratközlemény külföldi lapban folyóiratcikk chilling requirement bud number shoot growth flowering fruit set yield soluble carbohydrates proline content prediction based GLMs regression analyses PCA
Megjelenés:	Agronomy-Basel. - 11 : 7 (2021), p. 1-34. -
További szerzők:	Salama, Abdel-Moety Szabó Szilárd (1974-) (geográfus) Yaseen, Arshad Abdulkhalq (1986-) (Agricultural Engineer) Molnár Bianka Holb Imre (1973-) (agrármérnök)
Pályázati támogatás:	Bolyai János Kutatási Ösztöndíj Egyéb NKFI K 131478 Egyéb TÁMOP-4.2.4.A/2-11/1- 2012-0001 TÁMOP TKP2020-NKA-04 Egyéb
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001-es BibID:	BIBFORM105337
035-os BibID:	(WoS)000846416200001 (Scopus)85137317190 (cikkazonosító)1858
Első szerző:	Hateffard, Fatemeh (digital soil mapping)
Cím:	High-Resolution Mapping and Assessment of Salt-Affectedness on Arable Lands by the Combination of Ensemble Learning and Multivariate Geostatistics / Fatemeh Hateffard, Kitti Balog, Tibor Tóth, János Mészáros, Mátyás Árvai, Zsófia Adrienn Kovács, Nóra Szűcs-Vásárhelyi, Sándor Koós, Péter László, Tibor József Novák, László Pásztor, Gábor Szatmári
Dátum:	2022
ISSN:	2073-4395
Megjegyzések:	Soil salinization is one of the main threats to soils worldwide, which has serious impacts on soil functions. Our objective was to map and assess salt-affectedness on arable land (0.85 km2) in Hungary, with high spatial resolution, using a combination of ensemble machine learning and multivariate geostatistics on three salt-affected soil indicators (i.e., alkalinity, electrical conductivity, and sodium adsorption ratio (n = 85 soil samples)). Ensemble modelling with five base learners (i.e., random forest, extreme gradient boosting, support vector machine, neural network, and generalized linear model) was carried out and the results showed that ensemble modelling outperformed the base learners for alkalinity and sodium adsorption ratio with R2 values of 0.43 and 0.96, respectively, while only the random forest prediction was acceptable for electrical conductivity. Multivariate geostatistics was conducted on the stochastic residuals derived from machine learning modelling, as we could reasonably assume that there is spatial interdependence between the selected salt-affected soil indicators. We used 10-fold cross-validation to check the performance of the spatial predictions and uncertainty quantifications, which provided acceptable results for each selected salt-affected soil indicator (for pH value, electrical conductivity, and sodium adsorption ratio, the root mean square error values were 0.11, 0.86, and 0.22, respectively). Our results showed that the methodology applied in this study is efficient in mapping and assessing salt-affectedness on arable lands with high spatial resolution. A probability map for sodium adsorption ratio represents sodic soils exceeding a threshold value of 13, where they are more likely to have soil structure deterioration and water infiltration problems. This map can help the land user to select the appropriate agrotechnical operation for improving soil quality and yield.
Tárgyszavak:	Természettudományok Földtudományok idegen nyelvű folyóiratközlemény külföldi lapban folyóiratcikk salt-affected soils digital soil mapping ensemble modelling geostatistics; uncertainty assessment satellite remote sensing unpiloted aerial vehicle
Megjelenés:	Agronomy-Basel. - 12 : 8 (2022), p. 1-19. -
További szerzők:	Balog Kitti Tóth Tibor Mészáros János Árvai Mátyás Kovács Zsófia Adrienn Szűcs-Vásárhelyi Nóra Koós Sándor (agrár) László Péter Novák Tibor (1973-) (geográfus) Pásztor László Szatmári Gábor
Pályázati támogatás:	K-131820 and K-124290 OTKA
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001-es BibID:	BIBFORM094218
035-os BibID:	(cikkazonosító)935 (WoS)000653289800001 (Scopus)85106529645
Első szerző:	Négyesi Gábor (geográfus)
Cím:	Influence of Soil Moisture and Crust Formation on Soil Evaporation Rate: A Wind Tunnel Experiment in Hungary / Gábor Négyesi, Szilárd Szabó, Botond Buró, Safwan Mohammed, József Lóki, Kálmán Rajkai, Imre J. Holb
Dátum:	2021
ISSN:	2073-4395
Megjegyzések:	In both arid and semiarid regions, erosion by wind is a significant threat against sustainability of natural resources. The objective of this work was to investigate the direct impact of various soil moisture levels with soil texture and organic matter on soil crust formation and evaporation. Eighty soil samples with different texture (sand: 19, loamy sand: 21, sandy loam: 26, loam: 8, and silty loam: 6 samples) were collected from the Nyírség region (Eastern Hungary). A wind tunnel experiment was conducted on four simulated irrigation rates (0.5, l.0, 2.0, and 5.0 mm) and four levels of wind speeds (4.5, 7.8, 9.2, and 15.5 m s?1). Results showed that watering with a quantity equal to 5 mm rainfall, with the exception of sandy soils, provided about 5?6 h protection against wind erosion, even in case of a wind velocity as high as 15.5 m s?1. An exponential connection was revealed between wind velocities and the times of evaporation (R2 = 0.88?0.99). Notably, a two-way ANOVA test revealed that both wind velocity (p < 0.001) and soil texture (p < 0.01) had a significant effect on the rate of evaporation, but their interaction was not significant (p = 0.26). In terms of surface crusts, silty loamy soils resulted in harder and more solid crusts in comparison with other textures. In contrast, crust formation in sandy soils was almost negligible, increasing their susceptibility to wind erosion risk. These results can support local municipalities in the development of a local plan against wind erosion phenomena in agricultural areas.
Tárgyszavak:	Természettudományok Földtudományok idegen nyelvű folyóiratközlemény külföldi lapban folyóiratcikk wind tunnel wetting front SDGs regional planning
Megjelenés:	Agronomy-Basel. - 11 : 5 (2021), p. 1-16. -
További szerzők:	Szabó Szilárd (1974-) (geográfus) Buró Botond (1986-) (geográfus) Mohammed Safwan (1985-) (agrármérnök) Lóki József (1946-) (geográfus) Rajkai Kálmán (1951-) (biológus) Holb Imre (1973-) (agrármérnök)
Pályázati támogatás:	GINOP-2.3.2-15-2016-00009 GINOP K131478 OTKA TKP2020-NKA-04 Egyéb
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001-es BibID:	BIBFORM091585
035-os BibID:	(cikkazonosító)333 (WoS)000621996400001
Első szerző:	Phinzi, Kwanele
Cím:	Mapping Permanent Gullies in an Agricultural Area Using Satellite Images : Efficacy of Machine Learning Algorithms / Phinzi Kwanele, Holb Imre, Szabó Szilárd
Dátum:	2021
ISSN:	2073-4395
Megjegyzések:	Gullies are responsible for detaching massive volumes of productive soil, dissecting natural landscape and causing damages to infrastructure. Despite existing research, the gravity of the gully erosion problem underscores the urgent need for accurate mapping of gullies, a first but essential step toward sustainable management of soil resources. This study aims to obtain the spatial distribution of gullies through comparing various classifiers: k-dimensional tree K-Nearest Neighbor (k-d tree KNN), Minimum Distance (MD), Maximum Likelihood (ML), and Random Forest (RF). Results indicated that all the classifiers, with the exception of ML, achieved an overall accuracy (OA) of at least 0.85. RF had the highest OA (0.94), although it was outperformed in gully identification by MD (0% commission), but the omission error was 20% (MD). Accordingly, RF was considered as the best algorithm, having 13% error in both adding (commission) and omitting pixels as gullies. Thus, RF ensured a reliable outcome to map the spatial distribution of gullies. RF-derived gully density map reflected the agricultural areas most exposed to gully erosion. Our approach of using satellite imagery has certain limitations, and can be used only in arid or semiarid regions where gullies are not covered by dense vegetation as the vegetation biases the extracted gullies. The approach also provides a solution to the lack of laser scanned data, especially in the context of the study area, providing better accuracy and wider application possibilities.
Tárgyszavak:	Természettudományok Földtudományok idegen nyelvű folyóiratközlemény külföldi lapban folyóiratcikk gully erosion image classification K-Nearest Neighbor random forest minimum distance maximum likelihood
Megjelenés:	Agronomy-Basel. - 11 : 2 (2021), p. 1-16. -
További szerzők:	Holb Imre (1973-) (agrármérnök) Szabó Szilárd (1974-) (geográfus)
Pályázati támogatás:	TNN 123457 NKFI Egyéb Thematic Excellence Programme (TKP2020-NKA-04) of the Ministry for Innovation and Technology in Hungary projects Egyéb K131478 OTKA
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