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

Discriminant analysis for lodging severity classification in wheat using RADARSAT-2 and Sentinel-1 data

Crop lodging - the bending of crop stems from their upright position or the failure of root-soil anchorage systems - is a major yield-reducing factor in wheat and causes deterioration of grain quality. The severity of lodging can be measured by a lodging score (LS)- an index calculated from the crop angle of inclination (CAI) and crop lodged area (LA). LS is difficult and time consuming to measure manually meaning that information on lodging occurrence and severity is limited and sparse. Remote sensing-based estimates of LS can provide more timely, synoptic and reliable information on crop lodging across vast areas. This information could improve estimates of crop yield losses, inform insurance loss adjusters and influence management decisions for subsequent seasons.This research - conducted in the 600 ha wheat sown area in the Bonifiche Ferraresi farm, located in Jolanda di Savoia, Ferrara, Italy - evaluated the performance of RADARSAT-2 and Sentinel-1 data to discriminate and classify lodging severity based on field measured LS. We measured temporal crop status characteristics related to lodging (e.g. lodged area, CAI, crop height) and collected relevant meteorological data (wind speed and rainfall) throughout May-June 2018. These field measurements were used to distinguish healthy (He) wheat from lodged wheat with different degrees of lodging severity (moderate, severe and very severe). We acquired multi-incidence angle (FQ8-27° and FQ21-41°) RADARSAT-2 and Sentinel-1 (40°) images and derived multiple metrics from them to discriminate and classify lodging severity. As a part of our data exploration, we performed a correlation analysis between the image-based metrics and LS. Next, a multi-temporal discriminant analysis approach, including a partial least squares (PLS-DA) method, was developed to classify lodging severities. We used the area under the curve-receiver operating characteristics (AUC-ROC) and confusion matrices to evaluate the accuracy of the PLS-DA classification models.Results show that (1) volume scattering components were highly correlated with LS at low incidence angles while double and surface scattering was more prevalent at high incidence angles; (2) lodging severity was best classified using low incidence angle R-FQ8 data (overall accuracy 72%) and (3) the Sentinel-1 data-based classification model was able to correctly identify 60% of the lodging severity cases in the study site. The results from this first study on classifying lodging severity using satellite-based SAR platforms suggests that SAR-based metrics can capture a substantial proportion of the observed variation in lodging severity, which is important in the context of operational crop lodging assessment in particular, and sustainable agriculture in general

Diabetic striatopathy: an updated overview of current knowledge and future perspectives

Purpose: Diabetic striatopathy (DS) is a rare complication of poorly controlled diabetes mellitus (DM), characterized by hyperglycemia associated with chorea/ballism and characteristic reversible basal ganglia abnormalities on computed tomography (CT) and/or magnetic resonance imaging (MRI). We propose a narrative review of the literature on this topic, currently unknown to most, and about which physicians should be aware. We intend to summarize, critically review, and take to mean the evidence on this disorder, describing its typical features. Methods: We searched Pubmed for English-language sources using the following keywords in the title and the abstract: diabetic striatopathy, hyperglycemic non-ketotic hemichorea/hemiballism, chorea/hemichorea associated with non-ketotic hyperglycemia, diabetic hemiballism/hemichorea, chorea, hyperglycemia, and basal ganglia syndrome. We collected scientific articles, including case reports, reviews, systematic reviews, and meta-analyses from the years 1975 to 2023. We eliminated duplicate, non-English language or non-related articles. Results: Older Asian women are more frequently affected. Suddenly or insidiously hemichorea/hemiballism, mainly in the limbs, and high blood glucose with elevated HbA1c in the absence of ketone bodies have been observed. Furthermore, CT striatal hyperdensity and T1-weighted MRI hyperintensity have been observed. DS is often a treatable disease following proper hydration and insulin administration. Histopathological findings are variable, and no comprehensive hypothesis explains the atypical cases reported. Conclusion: DS is a rare neurological manifestation of DM. If adequately treated, although treatment guidelines are lacking, the prognosis is good and life-threatening complications may occur occasionally. During chorea/hemiballism, we recommend blood glucose and HbA1c evaluation. Further studies are needed to understand the pathogenesis

PhenoRice:A method for automatic extraction of spatio-temporal information on rice crops using satellite data time series

Agricultural monitoring systems require spatio-temporal information on widely cultivated staple crops like rice. More emphasis has been made on area estimation and crop detection than on the temporal aspects of crop cultivation, but seasonal and temporal information such as i) crop duration, ii) date of crop establishment and iii) cropping intensity are as important as area for understanding crop production. Rice cropping systems are diverse because genetic, environmental and management factors (G × E × M combinations) influence the spatio-temporal patterns of cultivation. We present a rule based algorithm called PhenoRice for automatic extraction of temporal information on the rice crop using moderate resolution hypertemporal optical imagery from MODIS. Performance of PhenoRice against spatially and temporally explicit reference information was tested in three diverse sites: rice-fallow (Italy), rice-other crop (India) and rice-rice (Philippines) systems. Regional product accuracy assessments showed that PhenoRice made a conservative, spatially representative and robust detection of rice cultivation in all sites (r2 between 0.75 and 0.92) and crop establishment dates were in close agreement with the reference data (r2 = 0.98, Mean Error = 4.07 days, Mean Absolute Error = 9.95 days, p < 0.01). Variability in algorithm performance in different conditions in each site (irrigated vs rainfed, direct seeding vs transplanting, fragmented vs clustered rice landscapes and the impact of cloud contamination) was analysed and discussed. Analysis of the maps revealed that cropping intensity and season length per site matched well with local information on agro-practices and cultivated varieties. The results show that PhenoRice is robust for deriving essential temporal descriptions of rice systems in both temperate and tropical regions at a level of spatial and temporal detail that is suitable for regional crop monitoring on a seasonal basis

The intermediate-age open cluster NGC 2112

We report on $BVI$ CCD photometry of a field centered on the region of the intermediate-age open cluster NGC 2112 down to V=21. Due to the smaller field coverage, we are able to limit the effect of field star contamination which hampered in the past precise determinations of the cluster age and distance. This way, we provide updated estimates of NGC 2112 fundamental parameters. Having extended the photometry to the $I$ pass-band, we are able to construct a colour-colour diagram, from which we infer a reddening $E_{B-V}= 0.63\pm0.14$ mag. The comparison of the Colour-Magnitude Diagram (CMD) with theoretical isochrones leads to a distance of $850 \pm 100$ pc, and an age of $2.0 \pm 0.3$ Gyr. While the distance is in agreement with previous determinations, the age turns out to be much better constrained and significantly lower than previous estimates.Comment: 7 pages, 7 eps figures, in press in MNRA

Versatile and non-cytotoxic GelMA-xanthan gum biomaterial ink for extrusion-based 3D bioprinting

Extrusion-based 3D bioprinting allows the 3D printing of bioinks, composed of cells and biomaterials, to mimic the complex 3D hierarchical structure of native tissues. Successful 3D bioprinting requires bioinks with specific properties, such as biocompatibility, printability, and biodegradability according to the desired application. In the present work, we aimed at developing a new versatile blend of gelatin methacryloyl-xanthan gum (GelMA-XG) suitable for extrusion-based 3D bioprinting with a straightforward process. To this end, we first optimized the process of gelatin methacryloyl (GelMA) synthesis by investigating the impact of different buffer solutions on the degree of functionalization, swelling degree, and degradation rate. The addition of xanthan gum (XG) enabled further tuning of biodegradability and an improvement of GelMA printability. Specifically, an optimal concentration of XG was found through rheological characterization and printability tests. The optimized blend showed enhanced printability and improved shape fidelity as well as its degradation products turned out to be non-cytotoxic, thus laying the foundation for cell-based applications. In conclusion, our newly developed biomaterial ink is a promising candidate for extrusion-based 3D bioprinting