Precision agricultural technology for advanced monitoring of maize yield under different fertilization and irrigation regimes: A case study in Eastern Hungary (Debrecen)

Széles, Adrienn; Huzsvai, László; Mohammed, Safwan; Nyéki, Anikó; Zagyi, Péter; Horváth, Éva; Simon, Károly; Arshad, Sana; Tamás, András

doi:10.1016/j.jafr.2024.100967

Cited by 4 publications

(2 citation statements)

References 78 publications

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“…Remote sensing, through electromagnetic radiation-plant-sensor interaction, has a high potential for identifying crop conditions because it allows non-destructive assessment quickly and at a relatively low cost [1][2][3]. This tool can be used to define areas for specific management, manage crop fertilization and irrigation [4], control weeds, and estimate crop productivity [5,6], presenting high practical importance, helping producers manage their production and define the price of agricultural products [7].…”

Section: Introductionmentioning

confidence: 99%

Geotechnologies in Biophysical Analysis through the Applicability of the UAV and Sentinel-2A/MSI in Irrigated Area of Common Beans: Accuracy and Spatial Dynamics

de Oliveira,

de Castro,

Sousa

et al. 2024

Remote Sensing

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The applicability of remote sensing enables the prediction of nutritional value, phytosanitary conditions, and productivity of crops in a non-destructive manner, with greater efficiency than conventional techniques. By identifying problems early and providing specific management recommendations in bean cultivation, farmers can reduce crop losses, provide more accurate and adequate diagnoses, and increase the efficiency of agricultural resources. The aim was to analyze the efficiency of vegetation indices using remote sensing techniques from UAV multispectral images and Sentinel-2A/MSI to evaluate the spectral response of common bean (Phaseolus vulgaris L.) cultivation in different phenological stages (V4 = 32 DAS; R5 = 47 DAS; R6 = 60 DAS; R8 = 74 DAS; and R9 = 89 DAS, in 99 days after sowing—DAS) with the application of doses of magnesium (0, 250, 500, and 1000 g ha−1). The field characteristics analyzed were mainly chlorophyll content, productivity, and plant height in an experimental area by central pivot in the midwest region of Brazil. Data from UAV vegetation indices served as variables for the treatments implemented in the field and were statistically correlated with the crop’s biophysical parameters. The spectral response of the bean crop was also detected through spectral indices (NDVI, NDMI_GAO, and NDWI_GAO) from Sentinel-2A/MSI, with spectral resolutions of 10 and 20 m. The quantitative values of NDVI from UAV and Sentinel-2A/MSI were evaluated by multivariate statistical analysis, such as principal components (PC), and cophenetic correlation coefficient (CCC), in the different phenological stages. The NDVI and MCARI vegetation indices stood out for productivity prediction, with r = 0.82 and RMSE of 330 and 329 kg ha−1, respectively. The TGI had the best performance in terms of plant height (r = 0.73 and RMSE = 7.4 cm). The best index for detecting the relative chlorophyll SPAD content was MCARI (r = 0.81; R2 = 0.66 and RMSE = 10.14 SPAD), followed by NDVI (r = 0.81; R2 = 0.65 and RMSE = 10.19 SPAD). The phenological stage with the highest accuracy in estimating productive variables was R9 (Physiological maturation). GNDVI in stages R6 and R9 and VARI in stage R9 were significant at 5% for magnesium doses, with quadratic regression adjustments and a maximum point at 500 g ha−1. Vegetation indices based on multispectral bands of Sentinel-2A/MSI exhibited a spectral dynamic capable of aiding in the management of bean crops throughout their cycle. PCA (PC1 = 48.83% and PC2 = 39.25%) of the satellite multiple regression model from UAV vs. Sentinel-2A/MSI presented a good coefficient of determination (R2 = 0.667) and low RMSE = 0.12. UAV data for the NDVI showed that the Sentinel-2A/MSI samples were more homogeneous, while the UAV samples detected a more heterogeneous quantitative pattern, depending on the development of the crop and the application of doses of magnesium. Results shown denote the potential of using geotechnologies, especially the spectral response of vegetation indices in monitoring common bean crops. Although UAV and Sentinel-2A/MSI technologies are effective in evaluating standards of the common bean crop cycle, more studies are needed to better understand the relationship between field variables and spectral responses.

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Section: Introductionmentioning

confidence: 99%

Geotechnologies in Biophysical Analysis through the Applicability of the UAV and Sentinel-2A/MSI in Irrigated Area of Common Beans: Accuracy and Spatial Dynamics

de Oliveira,

de Castro,

Sousa

et al. 2024

Remote Sensing

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“…The amount and timing of nitrogen fertiliser application has a significant impact on maize productivity. The effect of nitrogen is not only influenced by the cropping year and genotype, but also by the nutrient application technology used [26,27]. Spring basal fertilisation followed by top-dressing in the early vegetative stages (V6, V12) has a significant effect on yield [13,28,29].…”

Section: Introductionmentioning

confidence: 99%

Effect of Split Basal Fertilisation and Top-Dressing on Relative Chlorophyll Content and Yield of Maize Hybrids

Zagyi,

Horváth,

Vasvári

et al. 2024

Agriculture

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The aim of this study was to determine the nitrogen requirement of maize, the optimal timing and amount of nutrient application, based on long time series data. An additional objective was to examine the response of the relative chlorophyll content of maize to nitrogen fertilisation. The examinations were carried out in a long-term field experiment at the University of Debrecen between 2016 and 2022, using two maize hybrids with different genotypes. Spatial and temporal changes in the N status of maize leaves were monitored using the Soil and Plant Analysis Development (SPAD) instrument. In addition to the non-fertilised (A0) treatment, six fertiliser treatments were applied (spring basal fertilisation: 60 and 120 kg N ha−1, A60; A120). Basal fertilisation was followed by two occasions of top-dressing at phenological stages V6 and V12, at rates of +30–30 kg N ha−1 (V690 and V6150, and V12120 and V12180). The CMR (Chlorophyll Meter Reading), averaged over the examined years, genotypes and fertiliser treatments, were lowest in the V6 phenological phase (40.23 ± 5.57, p < 0.05) and highest in R1 (49.91 ± 8.41, p < 0.05). A120 fertiliser treatment increased the relative chlorophyll content by 5.11 compared to the non-fertilised treatment, 1.67 more than A60 treatment. The basal fertilisation treatment substantially increased the yield (A60: +30.75%; A120: +66.68%) compared to the A0 treatment averaged over years and genotypes. Based on the obtained research results, a basal treatment of 120 kg N ha−1 is recommended and it can be concluded that, under appropriate water supply conditions (rainfall, irrigation), nitrogen top-dressing applied in V6 phenophase results in a significant yield increase compared to basal fertilisation.

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Integrating Maize Yield and Agricultural Drought Analysis for Sustainable Food Security: A Provincial Study in South Africa (1993–2022)

Letswamotse,

Arshad,

Bashir

et al. 2024

Food and Energy Security

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Extreme climatic events, such as droughts, hinder progress toward achieving the sustainable development goal of food security. South Africa is vulnerable to drought‐related agricultural losses, which have led to food insecurity. However, few studies have focused on the long‐term impacts of drought on crop production at a regional scale. Therefore, we aimed to examine the intensity, magnitude, and trend of rainfall‐based short‐term agricultural drought at the provincial scale in South Africa based on the Standardized Precipitation Index (SPI). Additionally, we analyzed the impact of agricultural drought on maize yield by calculating the Standardized Yield Residual Series (SYRS) and Crop Drought‐Resilience Factor (CDRF). To this end, we collected rainfall data from 29 stations across nine provinces along with maize yield data for the period of 1993–2022. Agricultural drought analyses based on the three‐month (SPI‐3) and six‐month (SPI‐6) SPIs demonstrated dynamic variations in occurrence, with Sen's slope indicating that 10 stations exhibited a significant increase in drought events across South Africa. Notably, SPI‐6 analysis showed that Gauteng, Free State, and North West provinces experienced the highest percentages of severe to extreme drought events during the study period, at 4.17%, 3.89%, and 3.61%, respectively. Furthermore, the majority of provinces in South Africa experienced an extreme SPI‐6 magnitude ranging from −46.03 in Western Cape Province to −61.6 in Free State Province. The dynamic effects of agricultural drought on maize yield revealed that the maximum yield loss of 13% occurred in 1993 in Eastern Cape Province, while some provinces experienced no yield loss during certain years. However, CDRF analyses identified Western Cape (CDRF [SPI‐3] = 0.52, CDRF [SPI‐6] = 0.62) and Mpumalanga (CDRF [SPI‐6] = 0.7) provinces as the most vulnerable to food insecurity due to the severe non‐resilience of maize to drought in these regions. This study reveals the complex interplay between climatic extremes and maize yield variability, providing valuable insights for managing regional food production systems and ensuring future food security in South Africa.

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Precision agricultural technology for advanced monitoring of maize yield under different fertilization and irrigation regimes: A case study in Eastern Hungary (Debrecen)

Cited by 4 publications

References 78 publications

Geotechnologies in Biophysical Analysis through the Applicability of the UAV and Sentinel-2A/MSI in Irrigated Area of Common Beans: Accuracy and Spatial Dynamics

Geotechnologies in Biophysical Analysis through the Applicability of the UAV and Sentinel-2A/MSI in Irrigated Area of Common Beans: Accuracy and Spatial Dynamics

Effect of Split Basal Fertilisation and Top-Dressing on Relative Chlorophyll Content and Yield of Maize Hybrids

Integrating Maize Yield and Agricultural Drought Analysis for Sustainable Food Security: A Provincial Study in South Africa (1993–2022)

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