- ItemOpen AccessImpact of carob (Ceratonia siliqua L.) pulp inclusion and warm season on gastrointestinal morphological parameters, immune-redox defences and coccidiosis in concentrate-fed light lambs(Elsevier, 2023-08-11) Pelegrin-Valls, Jonathan; Álvarez Rodríguez, Javier; Martín-Alonso, María José; Aquilué, Beatriz; Serrano, BeatrizThis study aimed to evaluate the effects of dietary carob (Ceratonia siliqua L.) pulp and warm season on gastrointestinal morphological parameters, immune-redox defences and coccidiosis in concentrate-fed light lambs. Weaned lambs were assigned to one of three concentrate-based diets: C0 (without carob pulp), C15 (150 g/kg of carob pulp) and C30 (300 g/kg of carob pulp) from 40 to 80 days of age in two consecutive cold and warm batches. Blood samples were collected at Day 80 to determine the metabolic status. Rectal faeces were sampled at Days 50, 65 and 80 to determine consistency and oocyst count per gram. Inclusion of carob pulp in lamb diets did not affect lamb growth but reduced coccidia oocyst excretion, improved faecal consistency and gastrointestinal morphological parameters, enhancing the ruminal thickness of the papilla living strata and reducing the darkness of the epithelium colour. Moreover, carob condensed tannins in the lambs' diet enhanced the expression of antioxidant SOD2 in rumen, while down-regulated NRF2, SOD1, CAT and PPARG in ileum. There was no interaction between the treatments and season in the evaluated variables. Lambs from the warm season exhibited reduced growth performance, altered ruminal epithelium, lower circulating iron levels, increased protein concentrations and higher coccidiosis susceptibility. In addition, regulatory immune and antioxidant mechanisms to counterbalance reactive oxygen species production in gastrointestinal tissues were evident. Dietary inclusion of carob pulp (150 and 300 g/kg) in lamb diets improved gastrointestinal health and homeostasis but did not ameliorate the deleterious effects of warm season.
- ItemOpen AccessMobile terrestrial laser scanner vs. UAV photogrammetry to estimate woody crop canopy parameters - Part 2: Comparison for different crops and training systems(Elsevier, 2023-07-26) Torres-Sánchez, Jorge; Escolà i Agustí, Alexandre; de Castro, Ana I.; López-Granados, Francisca; Rosell Polo, Joan Ramon; Sebé Feixas, Francesc; Jiménez-Brenes, Francisco M.; Sanz Cortiella, Ricardo; Gregorio López, Eduard; Peña, José M.The measurement of geometric canopy parameters in woody crops is an important task in Precision Agriculture because of their correlation with crop condition and productivity. In recent years, several technological approaches have been developed as an alternative to manual measurements, which are time- and labour-consuming. Two of the most commonly used 3D canopy characterization technologies are mobile terrestrial laser scanning (MTLS) based on light detection and ranging (LiDAR) sensors, and digital aerial photogrammetry (DAP) using imagery from uncrewed aerial vehicles (UAVs). Although both are state-of-the-art and have been fully tested and validated, a complete comparison between their geometric canopy parameter estimations in different woody crops and training systems has not been carried out. For this reason, a set of geometric parameters (canopy height, projected area, and volume) of a vineyard, an intensive peach orchard, and an intensive pear orchard were measured using UAV-DAP and MTLS-LiDAR. A comparison between both kinds of measurements was performed, accounting for the length of the sections in which the crop hedgerows were divided to extract the geometric parameters. Measurements from the UAV and the MTLS were highly correlated (R2 from 0.82 to 0.94) when considering the data from the three crops together, and the correlations were higher when analysing longer row sections. The canopy geometric parameters estimated using the MTLS-LiDAR always had higher values than those from the UAV-DAP. The results presented in this work provide useful data for a more informed selection of technological approaches for 3D crop characterization in Precision Fruticulture and high-throughput phenotyping.
- ItemOpen AccessMobile terrestrial laser scanner vs. UAV photogrammetry to estimate woody crop canopy parameters - Part 1: Methodology and comparison in vineyards(Elsevier, 2023-08-01) Escolà i Agustí, Alexandre; Peña, José M.; López-Granados, Francisca; Rosell Polo, Joan Ramon; de Castro, Ana I.; Gregorio López, Eduard; Jiménez-Brenes, Francisco M.; Sanz Cortiella, Ricardo; Sebé Feixas, Francesc; Llorens Calveras, Jordi; Torres-Sánchez, JorgeCharacterizing crop canopies is especially important in the management of woody crops. In this article, two systems were compared to characterise a 50 m long vineyard row section. One of the systems was a mobile terrestrial laser scanner based on a light detection and ranging (LiDAR) sensor (MTLS-LiDAR). The other was an uncrewed aerial vehicle (UAV) based system using digital aerial photogrammetry (UAV-DAP). The resulting 3D point clouds were assessed qualitatively and quantitatively. Canopy heights, widths and volumes were obtained in 0.1 m long sections along the studied row. All the parameters derived from the two systems presented statistically significant differences. The coefficients of determination between systems were 0.619 for canopy maximum heights above ground level (agl), 0.686 for 90th percentile (P90) heights agl, and 0.283 and 0.274 for maximum and P90 vegetated heights, respectively. Coefficients of determination between averaged maximum canopy width and P90 canopy width were 0.328 and 0.317, respectively. Coefficients of determination between cross-sectional areas determined from maximum widths, P90 widths and from the occupancy grid method were 0.423, 0.409 and 0.334, respectively. Total canopy volume for the entire row obtained from the three cross section estimation methods differed between 19 m3 and 25 m3. The reasons found were that the MTLS-LiDAR-derived point cloud captured the canopy top and side variability but could be affected by occlusions, mixed pixels and tall grass-like weeds present in the surveyed area. For its part, the UAV-DAP-derived point cloud tended to miss top and side shoots and somewhat smoothed canopy variability. As neither of the systems is optimal, a balance needs to be found according to the specific requirements of the survey. For this purpose, a list of pros and cons is presented to support the selection of one of the two systems for canopy monitoring. The MTLS-LiDAR system should be chosen when high detail is required but small areas are to be scanned. Alternatively, the UAV-DAP system should be chosen when large areas are to be monitored and when canopy detail is not so important. Further results are presented in Part 2 for a larger area and including pear and peach orchards with different training systems. Future research is to be conducted on how the compared systems affect variability detection and support variable-rate prescriptions.
- ItemOpen AccessDeterminants of grain number responding to environmental and genetic factors in two- and six-rowed barley types(Elsevier, 2023) Serrago, Román A.; García, Guillermo A.; Savin, Roxana; Miralles, Daniel J.; Slafer, Gustavo A.Context Barley is one of the most relevant crops worldwide and an essential component of agriculture in Europe in general, and in the Mediterranean region in particular. As cropping areas will hardly rise in the future, yield must be improved to enhance global crop production. Naturally, understanding how yield is affected by environmental and genetic factors in two- and six-rowed barley can help us to develop more efficient management and breeding strategies to increase current yield gains. Objective We aimed to determine the relative importance of genetic and environmental factors on numerical and physiological components of GN for two- and six-rowed barley types. Methods To generate a large and unbiased database, we compiled data of yield and its numerical and physiological components from crop-based experiments (i.e., excluding controlled-conditions experiments and/or approaches using isolated plants) reported in figures and tables in every single paper having the word "barley" in the title published over 25 years in four rigorous and prestigious international journals: Field Crop Research, European Journal of Agronomy, Crop Science and Crop and Pasture Science (formerly Australian Journal of Agricultural Research) between January 1996 and December 2021, both inclusive. Results Spike number (SN) was the most relevant numerical component explaining GN regardless of the source of variation. Regarding physiological components, it seemed that when the driving force was environmental factors, spike dry weight at flowering (SDWF) was more relevant than fruiting efficiency (FE); whilst when the differences were due to genotypic factors, clearly the FE was the component mostly responsible for the changes in GN. When the analysis was restricted to two- and six-rowed barley types, GN improvements were mainly explained by changes in SN for both two- and six-rowed barley types. However, when the physiological components were considered, the responsiveness of GN was more related to SDWF than to FE in two-rowed genotypes, while the opposite was true for the six-rowed type. Conclusions In barley, SN always explained the responses of GN better than grain number per spike (GNS), regardless the source of variation and the type of barley. Respect to the physiological components, environmental factors affected GN mainly through affecting SDWF, while genotypic factors affected GN through affecting FE. SDWF and FE were more relevant for explaining changes in GN two- and six-rowed barleys, respectively. Implications Breeders and agronomists can be aware that it will be more likely to achieve significant gains in yield through focusing more on SN than on GNS regardless of the barley type, whilst regarding the physiological components it would be more relevant to focus on SDWF in two-rowed barley, and on FE in six-rowed barley.
- ItemOpen AccessUsing pre‑selected variants from large‑scale whole‑genome sequence data for single‑step genomic predictions in pigs(BMC, 2023-07-26) Jang, Sungbong; Ros Freixedes, Roger; Hickey , John M.; Chen, Ching-Yi; Holl, Justin; Herring, William O.; Misztal, Ignacy; Lourenco, DanielaBackground Whole-genome sequence (WGS) data harbor causative variants that may not be present in standard single nucleotide polymorphism (SNP) chip data. The objective of this study was to investigate the impact of using preselected variants from WGS for single-step genomic predictions in maternal and terminal pig lines with up to 1.8k sequenced and 104k sequence imputed animals per line. Methods Two maternal and four terminal lines were investigated for eight and seven traits, respectively. The number of sequenced animals ranged from 1365 to 1491 for the maternal lines and 381 to 1865 for the terminal lines. Imputation to sequence occurred within each line for 66k to 76k animals for the maternal lines and 29k to 104k animals for the terminal lines. Two preselected SNP sets were generated based on a genome-wide association study (GWAS). Top40k included the SNPs with the lowest p-value in each of the 40k genomic windows, and ChipPlusSign included significant variants integrated into the porcine SNP chip used for routine genotyping. We compared the performance of single-step genomic predictions between using preselected SNP sets assuming equal or different variances and the standard porcine SNP chip. Results In the maternal lines, ChipPlusSign and Top40k showed an average increase in accuracy of 0.6 and 4.9%, respectively, compared to the regular porcine SNP chip. The greatest increase was obtained with Top40k, particularly for fertility traits, for which the initial accuracy based on the standard SNP chip was low. However, in the terminal lines, Top40k resulted in an average loss of accuracy of 1%. ChipPlusSign provided a positive, although small, gain in accuracy (0.9%). Assigning different variances for the SNPs slightly improved accuracies when using variances obtained from BayesR. However, increases were inconsistent across the lines and traits. Conclusions The benefit of using sequence data depends on the line, the size of the genotyped population, and how the WGS variants are preselected. When WGS data are available on hundreds of thousands of animals, using sequence data presents an advantage but this remains limited in pigs.