265 research outputs found
Characterising maize and intercropped maize spectral signatures for cropping pattern classification
Intercropping – the planting of more than one crop in the same plot of land – is a prevalent agricultural management practice which can be used for risk reduction. Despite its widespread use, intercropping is not commonly reported in agricultural statistics, resulting to very limited spatially disaggregated information about its prevalence. Remote sensing-based approaches to detect and estimate the area of cropping patterns like intercropping require good understanding of the spectral response of (intercropped) crops at different crop growth phases. This study integrates field surveys, farmer interviews and temporal Sentinel-2 data from four crop growth phases and the post-harvest period of maize and intercropped maize (imaize). The goal is to identify the optimal crop growth phases, spectral regions and vegetation indices (VIs) that can accurately discriminate the two cropping patterns. We computed p-values for the spectral bands using Mann-Whitney U test and identified critical crop growth phases. Classification of maize and imaize cropping patterns was performed using random forest classifier. Our spectral analysis revealed effective discrimination between maize and imaize cropping patterns during the vegetative (in all spectral bands) and flowering-yield phases (in Blue, Green, Red, RE704, RE783, NIR833, NIR865). The most suitable VIs contained red-edge and near-infrared spectal bands. Utilizing spectral data and VIs from vegetative and flowering-yield phases, we achieved optimal discrimination during the vegetative phase (user’s accuracy of 100 % and producer’s accuracy of 100 %). However, accuracy decreased during the flowering yield phase (overall accuracy of 87 % for all spectral bands). The highest classification results using all spectral bands at the flowering yield phase resulted in 80 % producer’s accuracy for maize and 100 % for imaize. This study illustrates the utility of temporal Sentinel-2 spectral data for identifying the critical crop growth phase, spectral regions and VIs for cropping patterns classification, particularly for intercropping
Prediction of leaf area index using hyperspectral thermal infrared imagery over the mixed temperate forest
Hyperspectral Assessment of Ecophysiological Functioning for Diagnostics of Crops and Vegetation
Prediction of leaf area index using integration of the thermal infrared and optical data over the mixed temperate forest
Tolerance to freezing stress in Cicer accessions under controlled and field conditions
Freezing tolerance was determined in 5 annual wild Cicer and 225 Cicer arietinum L. accessions, grown both in field and controlled conditions. In controlled conditions, the temperature was decreased 5°C daily to achieve -20°C. Field trial was conducted at Urmia, Iran. In general, 'kabuli' chickpeas were more susceptible to freezing stress than 'desi' chickpeas. Some 'kabuli' types such as FLIP 93-261C and x03TH21 which presented high freezing tolerance during early seedling stage, withstood -15.6°Cwithout snow cover. Based on severity score data, the highest freezing tolerance sources were all accessions of Cicer echinospermum and Cicer reticulatum and 15 lines from C. arietinum germplasm. The results obtained in controlled conditions were approximately confirmed in the field conditions. The most resistant genotypes to freezing stress were wild accessions of ILWC 81, ILWC 106, ILWC 139, ILWC 181, ILWC 235, and cultivated lines, Sel 96 TH 11404, Sel 96 TH 11439, Sel 96 TH 11488, Sel 98 TH 11518, x03TH21 and FLIP 93-261C. Our results indicated the possibility of autumn sowing of chickpea in the high plateaus of Iran
Correlation and path-cofficient analysis of seed yield and yield related trait in Iranian confectionery sunflower populations
This study was undertaken in order to determine the association among yield components and their direct and indirect effects on the seed yield of confectionery sunflower. 36 confectionery sunflower populations originated from different regions of Northwest Iran were characterized using 11 agromorphological traits including: Days to 50% flowering, plant height, stem diameter, head diameter, number of leaves, leaf length, leaf width, petiole length, number of seeds per head, 100-seed weight and seed yield. Phenotypic correlations results show that seed yield per plant was positively and significantly associated with 100-seed weight, head diameter, number of seeds per head, stem diameter and plant height. Path coefficient analysis revealed that number of seed per head, 100-seed weight, and head diameter has positive direct effect on seed yield. Therefore, selection based on these characters would be more effective to improving seed yield in confectionery sunflower in breeding programs.Key words: Helianthus annuus L., direct effect, phenotypic correlation, indirect selection
Understanding of crop lodging induced changes in scattering mechanisms using RADERSAT-2 and Sentinel-1 derived metrics
Abstract. Crop lodging – the bending of crop stems from the vertical – is a major yield-reducing factor in cereal crops and causes deterioration in grain quality. Accurate assessment of crop lodging is important for improving estimates of crop yield losses, informing insurance loss adjusters and influencing management decisions for subsequent seasons. The role of remote sensing data, particularly synthetic aperture radar (SAR) data has been emphasized in the recent literature for crop lodging assessment. However, the effect of lodging on SAR scattering mechanisms is still unknown. Therefore, this research aims to understand the possible change in scattering mechanisms due to lodging by investigating SAR image pairs before and after lodging. We conducted the study in 26 wheat fields in the Bonifiche Ferraresi farm, located in Jolanda di Savoia, Ferrara, Italy. We measured temporal crop biophysical (e.g. crop angle) parameters and acquired multi-incidence angle RADARSAT-2 (R-2 FQ8-27° and R-2 FQ21-41°) and Sentinel-1 (S-1 40°) images corresponding to the time of field observations. We extracted metrics of SAR scattering mechanisms from RADARSAT-2 and Sentinel-1 image pairs in different zones using the unsupervised H/α decomposition algorithm and Wishart classifier. Contrasting results were obtained at different incidence angles. Bragg surface scattering increased in the case of S-1 (6.8%), R-2 FQ8 (1.8%) while at R-2 FQ21, it decreased (8%) after lodging. The change in double bounce scattering was more prominent at low incidence angle. These observations can guide future use of SAR-based information for operational crop lodging assessment in particular, and sustainable agriculture in general
- …