A. J. Kovács

56404010100

Publications - 22

Effect of pore size and temperature on the behaviour of alpha-lactalbumin and the A and B genetic variants of beta-lactoglobulin during protein fractionation microfiltration

G. Szafner A. J. Kovács Henrietta Buzás Mónika Krassóy Aline Wiedmann

Publication Name: Food Hydrocolloids

Publication Date: 2025-03-01

Volume: 160

Issue: Unknown

Page Range: Unknown

Description:

The aim of this study was to investigate the influence of membrane pore size and filtration temperature on six individual milk protein fractions (αS-CN, β- CN, κ-CN, α-LA, β-LG A, β-LG A) during the protein fractionation microfiltration process. Pasteurised skimmed milk was microfiltrated using two different pore sizes of spiral-wound membranes, with pore sizes of 0.2 μm and 0.5 μm, at temperatures of 15 °C and 45 °C respectively. The microfiltration process was carried out with a final volume reduction of 66% and a diafiltration volume of 120% (300 L) of the original feed (250 L). It was observed that neither the pore size nor the filtration temperature significantly (p < 0.05) affected the permeation of the α-LA fraction. However, the permeation of the β-LG A and β-LG B fractions can be influenced by membrane pore size and filtration temperature, and the behaviour of the three whey protein fractions, A and B genetic variants of the β-LG and α-LA fractions differs significantly during the microfiltration process. The results of this study could form the basis for the development of new, unique tailor-made milk protein ingredients.

Open Access: Yes

DOI: 10.1016/j.foodhyd.2024.110759

Field-grown tomato yield estimation using point cloud segmentation with 3D shaping and RGB pictures from a field robot and digital single lens reflex cameras

Z. Pék A. J. Kovács L. Helyes S. Takács Bálint Ambrus Gergely Teschner Tarek Alahmad A. Nyéki M. Neményi

Publication Name: Heliyon

Publication Date: 2024-10-30

Volume: 10

Issue: 20

Page Range: Unknown

Description:

The aim of this study was to estimate field-grown tomato yield (weight) and quantity of tomatoes using a self-developed robot and digital single lens reflex (DSLR) camera pictures. The authors suggest a new approach to predicting tomato yield that is based on images taken in the field, 3D scanning, and shape. Field pictures were used for tomato segmentation to determine the ripeness of the crop. A convolution neural network (CNN) model using TensorFlow library was devised for the segmentation of tomato berries along with a small robot, which had a 59.3 % F1 score. To enhance the accurate tomato crop model and to estimate the yield later, point cloud imaging was applied using a Ciclops 3D scanner. The best fitting sphere model was generated using the 3D model. The most optimal model was the 3D model, which gave the best representation and provided the weight of the tomatoes with a relative error of 21.90 % and a standard deviation of 17.9665 %. The results indicate a consistent object-based classification of the tomato crop above the plant/row level with an accuracy of 55.33 %, which is better than in-row sampling (images taken by the robot). By comparing the measured and estimated yield, the average difference for DSLR camera images was more favorable at 3.42 kg.

Open Access: Yes

DOI: 10.1016/j.heliyon.2024.e37997

Impact of Dehydration Techniques on the Nutritional and Microbial Profiles of Dried Mushrooms

E. Lakatos A. J. Kovács Imane Moutia

Publication Name: Foods

Publication Date: 2024-10-01

Volume: 13

Issue: 20

Page Range: Unknown

Description:

The global consumption of dried mushrooms has increased worldwide because of their rich nutritional value and culinary versatility. Dehydration methods such as sun drying, hot air drying, freeze drying, and microwave drying are employed to prolong the shelf life of a food product. These methods can also affect the food product’s nutritional value and the final product’s microbial profile. Each technique affects the retention of essential nutrients like vitamins, minerals, and bioactive compounds differently. Additionally, these techniques vary in their effectiveness at reducing microbial load, impacting the dried mushrooms’ safety and shelf life. This review addresses the gap in understanding how different dehydration methods influence dried mushrooms’ nutritional quality and microbial safety, which is crucial for optimizing their processing and consumption. It targets researchers, food processors, and consumers seeking to improve the quality and safety of dried mushrooms. This review comprehensively examines the impact of major dehydration techniques, including sun drying, hot air drying, microwave drying, and freeze drying, on the nutritional and microbial profiles of dried mushrooms. Each method is evaluated for its effectiveness in preserving essential nutrients and reducing microbial load. Current research indicates that freeze drying is particularly effective in preserving nutritional quality, while hot air and microwave drying significantly reduce microbial load. However, more well-designed studies are needed to fully understand the implications of these methods for safety and nutritional benefits. These findings are valuable for optimizing dehydration methods for high-quality dried mushrooms that are suited for culinary and medicinal use.

Open Access: Yes

DOI: 10.3390/foods13203245

Yield Prediction Using NDVI Values from GreenSeeker and MicaSense Cameras at Different Stages of Winter Wheat Phenology

G. Milics Viktoria Vona Gabor Kukorelli Zoltán Varga A. J. Kovács István Mihály Kulmány Laszló Bede Gergely Teschner Sándor Zsebő Dávid Stencinger

Publication Name: Drones

Publication Date: 2024-03-01

Volume: 8

Issue: 3

Page Range: Unknown

Description:

This work aims to compare and statistically analyze Normalized Difference Vegetation Index (NDVI) values provided by GreenSeeker handheld crop sensor measurements and calculate NDVI values derived from the MicaSense RedEdge-MX Dual Camera, to predict in-season winter wheat (Triticum aestivum L.) yield, improving a yield prediction model with cumulative growing degree days (CGDD) and days from sowing (DFS) data. The study area was located in Mosonmagyaróvár, Hungary. A small-scale field trial in winter wheat was constructed as a randomized block design including Environmental: N-135.3, P2O5-77.5, K2O-0; Balance: N-135.1, P2O5-91, K2O-0; Genezis: N-135, P2O5-75, K2O-45; and Control: N, P, K 0 kg/ha. The crop growth was monitored every second week between April and June 2022 and 2023, respectively. NDVI measurements recorded by GreenSeeker were taken at three pre-defined GPS points for each plot; NDVI values based on the MicaSense camera Red and NIR bands were calculated for the same points. Results showed a significant difference (p ≤ 0.05) between the Control and treated areas by GreenSeeker measurements and Micasense-based calculated NDVI values throughout the growing season, except for the heading stage. At the heading stage, significant differences could be measured by GreenSeeker. However, remotely sensed images did not show significant differences between the treated and Control parcels. Nevertheless, both sensors were found suitable for yield prediction, and 226 DAS was the most appropriate date for predicting winter wheat’s yield in treated plots based on NDVI values and meteorological data.

Open Access: Yes

DOI: 10.3390/drones8030088

Challenges of ecocentric sustainable development in agriculture with special regard to the internet of things (IoT), an ICT perspective

A. J. Kovács Bálint Ambrus Gergely Teschner Tarek Alahmad A. Nyéki M. Neményi

Publication Name: Progress in Agricultural Engineering Sciences

Publication Date: 2023-12-20

Volume: 19

Issue: 1

Page Range: 113-122

Description:

“Feed the global population and regenerate the planet.” The conditions necessary for the implementation of the above commonly used slogan did not exist 10–15 years ago. We did not have access to the information and databases that would have allowed us to increase yields for the purpose of feeding the growing population. While increasingly meeting sustainability requirements and regenerating the Earth. Anthropocentrism, the belief that humans are superior to everything else, benefits humans by exploiting human greed and ignorance, which is a dead end for both individuals and societies. Only humans can ignore the dynamic equilibrium processes of nature and disregard the consequences that adversely affect future generations. Ecocentric agricultural practices have several prerequisites. It is important for the academic sphere to recognize its significance. Another fundamental challenge is the continuous monitoring of the production unit and its close and distant environment for the purpose of decision preparation using Big Data. The Internet of Things (IoT) is a global infrastructure that represents the network of physical (sensors) and virtual (reality) “things” through interoperable communication protocols. This allows devices to connect and communicate using cloud computing and artificial intelligence, contributing to the integrated optimization of the production system and its environment, considering ecocentric perspectives. This brings us closer to the self-decision-making capability of artificial intelligence, the practice of machine-to-machine (M2M) interaction, where human involvement in decision-making is increasingly marginalized. The IoT enables the fusion of information provided by deployed wireless sensors, data-gathering mobile robots, drones, and satellites to explore complex ecological relationships in local and global dimensions. Its significance lies, for example, in the prediction of plant protection. The paper introduces small smart data logger robots, including the Unmanned Ground Vehicles (robots) developed by the research team. These can replace sensors deployed in the Wireless Sensor Net (WSN).

Open Access: Yes

DOI: 10.1556/446.2023.00099

Aflatoxin M1 detection in raw milk and drinking milk in Hungary by ELISA − A one-year survey

Attila Hucker Róbert Kocsis G. Szafner Solveig Bukovics Judit Süle A. J. Kovács Katalin Szabó Henrietta Buzás Sárvári Loretta Csilla Katalin Nagy-Kovács

Publication Name: Journal of Food Composition and Analysis

Publication Date: 2023-08-01

Volume: 121

Issue: Unknown

Page Range: Unknown

Description:

The aim of this study was to monitor the aflatoxin M1(AFM1) contamination in raw milk and drinking milk in Hungary over a one-year period. A total of 474 milk samples of raw milk (n = 278) and commercial milk (n = 196) were collected and analysed between September 2021 and November 2022. Enzyme-Linked Immunosorbent Assay (ELISA) determined the concentration of AFM1. It was found that 68.7% (191/278) of the raw cow milk samples were contaminated by AFM1 in the range 5.0–173 ng/L, the mean of the positive samples was 30.7 ± 24.7 ng/L, and the median was 21.8 ng/L. The percentage of contamination in drinking milk was 79.1% (155/196). The mean, median, and range of the positive samples were 18.0 ± 10.9 ng/L, 16.18 ng/L, and 5.3–100 ng/L, respectively. Overall, 9.4% (26/278) of raw milk samples and only 1 commercial milk sample of 196 (0.5%) contained AFM1 exceeding the maximum residue level (MRL) of 50 ng/L set by the European Union. Our study suggests that based on calculated AFM1-related health risk indicators, the Hungarian adult population are not exposed to high levels of AFM1, but regular monitoring of aflatoxins is necessary not only for dairy farmers but also for the milk processing sectors.

Open Access: Yes

DOI: 10.1016/j.jfca.2023.105368

Challenges of sustainable agricultural development with special regard to Internet of Things: Survey

E. Harsányi Judit Oláh Popp József A. J. Kovács Erdei Edina Bálint Ambrus Gergely Teschner A. Nyéki M. Neményi

Publication Name: Progress in Agricultural Engineering Sciences

Publication Date: 2022-12-02

Volume: 18

Issue: 1

Page Range: 95-114

Description:

If we want to increase the efficiency of precision technologies to create sustainable agriculture, we need to put developments and their application on a new footing; moreover, a general paradigm shift is needed. There is a need to rethink close-At-hand and far-off innovation concepts to further develop precision agriculture, from both an agricultural, landscape, and natural ecosystem sustainability perspective. With this, unnecessary or misdirected developments and innovation chains can be largely avoided. The efficiency of the agrotechnology and the accuracy of yield prediction can be ensured by continuously re-planning during the growing season according to changing conditions (e.g., meteorological) and growing dataset. The aim of the paper is to develop a comprehensive, thought-provoking picture of the potential application of new technologies that can be used in agriculture, primarily in precision technology-based arable field crop production, which emphasizes the importance of continuous analysis and optimisation between the production unit and its environment. It should also be noted that the new system contributes to reconciling agricultural productivity and environmental integrity. The study also presents research results that in many respects bring fundamental changes in technical and technological development in field production. The authors believe that treating the subsystems of agriculture, landscape, and natural ecosystem (ALNE) as an integrated unit will create a new academic interdisciplinarity. ICT, emphasizing WSN (Wireless Sensor Network), remote sensing, cloud computing, AI (Artificial Intelligence), economics, sociology, ethics, and the cooperation with young students in education can play a significant role in research. This study treats these disciplines according to sustainability criteria. The goal is to help management fulfil the most important expectation of reducing the vulnerability of the natural ecosystem. The authors believe that this article may be one of the starting points for a new interdisciplinarity, ALNE.

Open Access: Yes

DOI: 10.1556/446.2022.00053

Developed rapid and simple RP-HPLC method for simultaneous separation and quantification of bovine milk protein fractions and their genetic variants

G. Szafner Solveig Bukovics Judit Süle A. J. Kovács Székelyhidi Rita Katalin Szabó Henrietta Buzás

Publication Name: Analytical Biochemistry

Publication Date: 2022-12-01

Volume: 658

Issue: Unknown

Page Range: Unknown

Description:

The aim was to develop a reliable rapid reversed-phase high-performance liquid chromatography (RP-HPLC) method to simultaneously determine the main bovine milk protein fractions, including their genetic variants. Compared to the previous studies, our method is able to separate the main protein fractions within 20 min of total run time. The method validation consisted of testing repeatability, reproducibility linearity, repeatability, and accuracy. The procedure was developed using raw individual, bulk, and commercially available heat-treated cow milk samples. The RSD of peak areas ranged from 1.43 to 3.16% within analytical day and from 3.29 to 6.70% across analytical days. The method can be applied to investigate both raw and heat-treated milk samples.

Open Access: Yes

DOI: 10.1016/j.ab.2022.114939

Spatial Variability of Soil Properties and Its Effect on Maize Yields within Field—A Case Study in Hungary

Bálint Daróczy C. Kerepesi A. J. Kovács A. Nyéki M. Neményi

Publication Name: Agronomy

Publication Date: 2022-02-01

Volume: 12

Issue: 2

Page Range: Unknown

Description:

To better understand the potential of soils, understanding how soil properties vary over time and in-field is essential to optimize the cultivation and site-specific technologies in crop pro-duction. This article aimed at determining the within-field mapping of soil chemical and physical properties, vegetation index, and yield of maize in 2002, 2006, 2010, 2013, and 2017, respectively. The objectives of this five-year field study were: (i) to assess the spatial and temporal variability of attributes related to the maize yield; and (ii) to analyse the temporal stability of management zones. The experiment was carried out in a 15.3 ha research field in Hungary. The soil measurements in-cluded sand, silt, clay content (%), pH, phosphorous (P2O5), potassium (K2O), and zinc (Zn) in the topsoil (30 cm). The apparent soil electrical conductivity was measured in two layers (0–30 cm and 30–90 cm, mS/m) in 2010, in 2013, and in 2017. The soil properties and maize yields were evaluated in 62 management zones, covering the whole research area. The properties were characterized as the spatial-temporal variability of these parameters and crop yields. Classic statistics and geostatis-tics were used to analyze the results. The maize yields were significantly positively correlated (r = 0.62–0.73) with the apparent electrical conductivity (Veris_N3, Veris_N4) in 2013 and 2017, and with clay content (r = 0.56–0.81) in 2002, 2013, and 2017.

Open Access: Yes

DOI: 10.3390/agronomy12020395

Comparing Different Phosphorus Extraction Methods: Effects of Influencing Parameters

Csaba Centeri Renato Kalocsai G. Milics Márton Vona Zsolt Biró Viktoria Vona A. J. Kovács J. Kauser István Mihály Kulmány Gergely Jakab

Publication Name: Sustainability Switzerland

Publication Date: 2022-02-01

Volume: 14

Issue: 4

Page Range: Unknown

Description:

The current study compares the phosphorus (P) analysis methods of ammonium lactate (AL), Mehlich 3 (M3); water extraction (P-WA(P)&P-WA(PO4 )), cobalt hexamine (CoHex) and X-ray fluorescence (XRF) as an estimate of total soil P. The ratio of the P-content/XRF was first calculated and compared with the whole dataset. Based on the comparison of all the data, there were significant differences between the results of P-WA(P) and P-WA(PO4 ) vs. M3 and AL, CoHex vs. M3 and CoHex vs. AL methods (p < 0.001). The second step was the analysis of the influencing factors based on their categories for a more in-depth understanding of their role (CaCO3-content, pH, soil texture and clay content). The results showed that higher CaCO3 content (>1%) resulted in lower correlations (6/10 cases). The extraction methods, the soil, the classification method of the soil properties and the statistical analyses affect the evaluation. The dataset covers a good range of the analysed factors for the evaluation of phosphorus in the majority of Hungarian soil types in arable use. There were two methods that detected the largest amount of P from the total P in the soil: AL and M3.

Open Access: Yes

DOI: 10.3390/su14042158

Digital Twin of Drone-based Protection of Agricultural Areas

Á Ballagi Csaba Hajdu A. J. Kovács János Hollósi Gergely Teschner Norbert Boros

Publication Name: 2022 IEEE 1st International Conference on Internet of Digital Reality Iod 2022

Publication Date: 2022-01-01

Volume: Unknown

Issue: Unknown

Page Range: 99-104

Description:

Protecting agricultural fields, like crops, vineyards, and husbandry areas, has been a difficult challenge since historical times. Classical methods to prevent intrusion are often destructive to wild and domestic animals alike. Even more current nondestructive systems, like camera-based systems are attributed to specific problems related to environmental or technological issues. Furthermore, verifying the effectiveness of installed systems is difficult, as the triggering situations are unmanageable and typically occur unsupervised. This paper presents a complex vision-based intrusion detection system to overcome these problems and further proposes more extensive control and flexibility on the development process. The solution provides a workflow integrating Digital Reality methods into the system development by creating a digital twin of the drone and its surrounding environment in a general-purpose robotic simulator. With this simulation, the triggering events and environmental effects can be easily emulated, such as a wild animal entering the area of interest. The solution also focuses on incorporating new 5G info-communication networks on handling communication between the intrusion detection system and the base station in a distributed manner.

Open Access: Yes

DOI: 10.1109/IoD55468.2022.9986763

Conference report from 13th European Conference on Precision Agriculture (ECPA)

G. Milics A. J. Kovács A. Nyéki M. Neményi

Publication Name: Environmental Sciences Europe

Publication Date: 2021-12-01

Volume: 33

Issue: 1

Page Range: Unknown

Description:

This is a report on the 13th European Conference on Precision Agriculture (ECPA) that took place between 18 and 22, July at the location of the University of Public Service in Budapest, Hungary. The theme of the Conference was the “Adoption of innovative precision agriculture technologies and solutions”. Due to the pandemic, the conference was a hybrid event. The two societies—the International Society of Precision Agriculture and the Hungarian Society of Precision Agriculture—had contributed to the event. The international conference was mainly attended by academic researchers, university instructors, company executives and farmers. The event comprised five plenary and 22 scientific sessions.

Open Access: Yes

DOI: 10.1186/s12302-021-00559-y

Application of spatio-temporal data in site-specific maize yield prediction with machine learning methods

E. Harsányi G. Milics Bálint Daróczy C. Kerepesi A. J. Kovács J. Nagy A. Nyéki M. Neményi András Benczúr

Publication Name: Precision Agriculture

Publication Date: 2021-10-01

Volume: 22

Issue: 5

Page Range: 1397-1415

Description:

In order to meet the requirements of sustainability and to determine yield drivers and limiting factors, it is now more likely that traditional yield modelling will be carried out using artificial intelligence (AI). The aim of this study was to predict maize yields using AI that uses spatio-temporal training data. The paper has advanced a new method of maize yield prediction, which is based on spatio-temporal data mining. To find the best solution, various models were used: counter-propagation artificial neural networks (CP-ANNs), XY-fused Querynetworks (XY-Fs), supervised Kohonen networks (SKNs), neural networks with Rectangular Linear Activations (ReLU), extreme gradient boosting (XGBoost), support-vector machine (SVM), and different subsets of the independent variables in five vegetation periods. Input variables for modelling included: soil parameters (pH, P2O5, K2O, Zn, clay content, ECa, draught force, Cone index), micro-relief averages, and meteorological parameters for the 63 treatment units in a 15.3 ha research field. The best performing method (XGBoost) reached 92.1% and 95.3% accuracy on the training and the test sets. Additionally, a novel method was introduced to treat individual units in a lattice system. The lattice-based smoothing performed an additional increase in Area under the curve (AUC) to 97.5% over the individual predictions of the XGBoost model. The models were developed using 48 different subsets of variables to determine which variables consistently contributed to prediction accuracy. By comparing the resulting models, it was shown that the best regression model was Extreme Gradient Boosting Trees, with 92.1% accuracy (on the training set). In addition, the method calculates the influence of the spatial distribution of site-specific soil fertility on maize grain yields. This paper provides a new method of spatio-temporal data analyses, taking the most important influencing factors on maize yields into account.

Open Access: Yes

DOI: 10.1007/s11119-021-09833-8

The effect of soil physicochemical characteristics on zinc analysis methods

Csaba Centeri Renato Kalocsai G. Milics Zsolt Biró Viktoria Vona A. J. Kovács Endre Andor Tóth István Mihály Kulmány Gergely Jakab Zsolt Giczi

Publication Name: Soil and Water Research

Publication Date: 2021-01-01

Volume: 16

Issue: 3

Page Range: 180-190

Description:

Zn is an essential micronutrient involved in a wide variety of physiological processes. Soils are tested for zinc in many countries with several extractants. Each country has its validated methods, best-suited for its soils. The current study was designed to compare different zinc content measuring methods with seventy-one samples from Hungary. The data were first compared for the whole dataset and then in certain categories such as CaCO3-content, pH, texture and clay content. The zinc content was determined by the water extraction, KCl-EDTA (ethylenediaminetetraacetic acid), Mehlich 3, CoHex (cobalt hexamine trichloride), and XRF (X-ray fluorescence) methods. Based on the analyses of all the data, we can conclude that all the methods are different. However, further analyses during the comparison of the methods based on the influencing factors, such as the pH, lime content, texture class, and clay content proved that, in some of the cases, there are similarities among the methods and, this way, we can get more knowledge on the measurements and the results provided. Farmers can gain extra knowledge from the comparison of the influencing factors to know where intervention is needed to use extra Zn for the proper fertilisation of their plants.

Open Access: Yes

DOI: 10.17221/53/2020-SWR

Comparison of magnesium determination methods on Hungarian soils

Csaba Centeri Renato Kalocsai G. Milics Zsolt Biró Viktoria Vona A. J. Kovács Gergely Jakab Zsolt Giczi

Publication Name: Soil and Water Research

Publication Date: 2020-01-01

Volume: 15

Issue: 3

Page Range: 173-180

Description:

Magnesium is one of the most important nutrient elements. Soils are tested for magnesium in many countries with several extractants. Each country has its own validated methods, best-suited for its soils. The current study was designed to compare different magnesium content measuring methods with 80 Hungarian samples. The magnesium content was determined by the potassium chloride (1 M KCl 1:10), Mehlich 3 and CoHex (cobalt hexamine trichloride) methods. The maximum, mean and median values resulting from all the Mg determination methods showed the following order of measured magnitude: KCl < CoHex < M3.

Open Access: Yes

DOI: 10.17221/92/2019-SWR

Emerging macroscopic pretreatment

Ching Lik Hii Henry Jaeger Francisco J. Barba Julia Schmidt A. J. Kovács N. N. Misra Hiroshi Yoshida Patrick J. Cullen

Publication Name: Food Waste Recovery Processing Technologies Industrial Techniques and Applications

Publication Date: 2020-01-01

Volume: Unknown

Issue: Unknown

Page Range: 173-193

Description:

Macroscopic pretreatment of food waste aims at the preparation of the food matrix for subsequent processing and recovery steps. The preparatory steps involve the adjustment of the phase content and properties (water, solid, and fats content), the moderation of enzyme activity as well as prevention and control of any microbial growth In recent times, several emerging technologies have been researched, developed, and/or adapted from other fields for drying, sterilization, enzyme inactivation, and enhancing mass transfer in food and biomaterials. This chapter focuses on these upcoming technologies with potential applications to food waste recovery and includes foam-mat drying, electro-osmotic drying, radio-frequency drying, cold plasma technology, and high-pressure processing. The content lays emphasis on discussing the successful applications and identification of future prospects, from both a technology and an economic point of view.

Open Access: Yes

DOI: 10.1016/B978-0-12-820563-1.00016-0

Maize yield prediction based on artificial intelligence using spatio-temporal data

G. Milics Bálint Daróczy C. Kerepesi A. J. Kovács A. Nyéki M. Neményi András Benczúr

Publication Name: Precision Agriculture 2019 Papers Presented at the 12th European Conference on Precision Agriculture Ecpa 2019

Publication Date: 2019-01-01

Volume: Unknown

Issue: Unknown

Page Range: 1011-1017

Description:

The aim of this study was to predict maize yield by artificial intelligence using spatio-temporal training data. Counter-propagation artificial neural networks (CP-ANNs), XY-fused networks (XY-Fs), supervised Kohonen networks (SKNs), extreme gradient boosting (XGBoost) and support-vector machine (SVM) were used for predicting maize yield in 5 vegetation periods. Input variables for modelling were: soil parameters (pH, P2O5, K2O, Zn, Clay content, ECa, draught force, Cone index), and micro-relief averages and meteorological parameters for the 63 treatment units. The best performing method (XGBoost) attained 92.1 and 95.3% of accuracy on the training and the test set.

Open Access: Yes

DOI: 10.3920/978-90-8686-888-9_124

Weed species composition of small-scale farmlands bears a strong crop-related and environmental signature

A. M. Csergő D. Türei Gy Pinke A. J. Kovács K. Nagy A. Lengyel

Publication Name: Weed Research

Publication Date: 2018-02-01

Volume: 58

Issue: 1

Page Range: 46-56

Description:

Weed species loss due to intensive agricultural land use has raised the need to understand how traditional cropland management has sustained a diverse weed flora. We evaluated to what extent cultivation practices and environmental conditions affect the weed species composition of a small-scale farmland mosaic in Central Transylvania (Romania). We recorded the abundance of weed species and 28 environmental, management and site context variables in 299 fields of maize, cereal and stubble. Using redundancy analysis, we revealed 22 variables with significant net effects, which explained 19.2% of the total variation in species composition. Cropland type had the most pronounced effect on weed composition with a clear distinction between cereal crops, cereal stubble and maize crops. Beyond these differences, the environmental context of croplands was a major driver of weed composition, with significant effects of geographic position, altitude, soil parameters (soil pH, texture, salt and humus content, CaCO3, P2O5, K2O, Na and Mg), as well as plot location (edge vs. core position) and surrounding habitat types (arable field, road margin, meadow, fallow, ditch). Performing a variation partitioning for the cropland types one by one, the environmental variables explained most of the variance compared with crop management. In contrast, when all sites were combined across different cropland types, the crop-specific factors were more important in explaining variance in weed community composition.

Open Access: Yes

DOI: 10.1111/wre.12281

Soil moisture distribution mapping in topsoil and its effect on maize yield

Viliam Nagy G. Milics Zoltán Varga A. J. Kovács Attila Pörneczi Gábor Baranyai A. Nyéki Lubomír Lichner M. Neményi Tamás Németh

Publication Name: Biologia Poland

Publication Date: 2017-08-28

Volume: 72

Issue: 8

Page Range: 847-853

Description:

Soil moisture content directly influences yield. Mapping within field soil moisture content differences provides information for agricultural management practices. In this study we aimed to find a cost-effective method for mapping within field soil moisture content differences. Spatial coverage of the field sampling or TDR method is still not dense enough for site-specific soil management. Soil moisture content can be calculated by measuring the apparent soil electrical conductivity (ECa) using the Veris Soil EC-3100 on-the-go soil mapping tool. ECa is temperature dependent; therefore values collected in different circumstances were standardized to 25°C temperature (EC25). Constants for Archie's adjusted law were calculated separately, using soil temperature data. According to our results, volumetric moisture content can be mapped by applying ECa measurements in our particular field with high spatial accuracy. Even though within-field differences occure in the raw ECa map standardization to EC25 is recommended. Soil moisture map was also compared to yield map showing correlation (R2 = 0.5947) between the two datasets.

Open Access: Yes

DOI: 10.1515/biolog-2017-0100

Effects of soil compaction on cereal yield: A review

G. Milics A. J. Kovács A. Nyéki M. Neményi

Publication Name: Cereal Research Communications

Publication Date: 2017-03-01

Volume: 45

Issue: 1

Page Range: 1-22

Description:

This paper reviews the works related to the effect of soil compaction on cereal yield and focuses on research of field experiments. The reasons for compaction formation are usually a combination of several types of interactions. Therefore one of the most researched topics all over the world is the changes in the soil's physical and chemical properties to achieve sustainable cereal production conditions. Whether we are talking about soil bulk density, physical soil properties, water conductivity or electrical conductivity, or based on the results of measurements of on-line or point of soil sampling resistance testing, the fact is more and more information is at our disposal to find answers to the challenges. Thanks to precision plant production technologies (PA) these challenges can be overcome in a much more efficient way than earlier as instruments are available (geospatial technologies such as GIS, remote sensing, GPS with integrated sensors and steering systems; plant physiological models, such Decision Support System for Agrotechnology Transfer (DSSAT), which includes models for cereals etc.). The tests were carried out first of all on alteration clay and sand content in loam, sandy loam and silt loam soils. In the study we examined especially the change in natural soil compaction conditions and its effect on cereal yields. Both the literature and our own investigations have shown that the soil moisture content changes have the opposite effect in natural compaction in clay and sand content related to cereal yield. These skills would contribute to the spreading of environmental, sustainable fertilizing devoid of nitrate leaching planning and cereal yield prediction within the framework of the PA to eliminate seasonal effects.

Open Access: Yes

DOI: 10.1556/0806.44.2016.056

Selective heating of different grain parts of wheat by microwave energy

E. Szijjártó A. J. Kovács E. Pallai-Varsányi M. Neményi

Publication Name: Advances in Microwave and Radio Frequency Processing Report from the 8th International Conference on Microwave and High Frequency Heating

Publication Date: 2006-01-01

Volume: Unknown

Issue: Unknown

Page Range: 312-320

Description:

The aim of author's research work was to investigate the effect of process parameters and microwave heat treatment condition on the inactivation of &-amylase enzyme being in wheat grains, responsible for decomposition of starch molecules without considerable damage of the gluten content. The task was furthermore to clear up the possibilities of selective moistening of the different wheat grain parts containing the &-amylase enzyme and the valuable gluten protein. For checking the results Magnetic Resonance Imaging method was used. © Springer-Verlag Berlin Heidelberg 2006.

Open Access: Yes

DOI: 10.1007/978-3-540-32944-2_33

First step from an arable weed to a honey crop: Breaking seed dormancy of Stachys annua

B. Czúcz Gy Pinke A. J. Kovács Zoltán Molnár L. Magyar Éva Dunai Sándor Zsebő Petra Amtmann Judit Fehér

Publication Name: Acta Agrobotanica

Publication Date: 2025-01-01

Volume: 78

Issue: Unknown

Page Range: Unknown

Description:

Stachys annua (L.) L.– a typical annual weed species in stubble fields – was the most important melliferous plant in the Carpathian Basin during the 19th century. The agricultural intensification led to a drastic decline in the species, and previous efforts for its cultivation were unsuccessful due to its unevenly germinating seeds. This study aims to identify an effective method for overcoming the primary seed dormancy of S. annua. In laboratory experiments, we evaluated the effects of moist stratification for 4 weeks (in cold/warm sand) as well as using a gibberellic acid (GA) solution (250 mg/L) on seed germination under two light-temperature regimes (a “constant” regime at 20°C in continuous darkness, and a “fluctuating” regime with 14 h light at 20°C followed by 10 h dark at 10°C). Our results indicate that freshly matured seeds were mostly dormant at maturity. Gibberellic acid has a substantial role in breaking seed dormancy and can help substitute for the cold requirement. The best combination consisted of a GA treatment following a short (4 weeks) warm stratification, which led to a high (98%) germination rate in darkness at 20°C. The results indicate that, under natural circumstances, the seeds of S. annua require a longer period for their primary dormancy to be released. Our findings can establish the basis for the development of a dormancy-breaking technology to achieve uniform germination allowing future cultivation of the plant in bee gardens and arable fields.

Open Access: Yes

DOI: 10.5586/aa/207013