Novel high-throughput phenotyping (HTP) approaches are needed to advance the understanding of genotype-to-phenotype and accelerate plant breeding. The first generation of HTP has examined simple spectral reflectance traits from images and sensors but is limited in advancing our understanding of crop development and architecture. Lodging is a complex trait that significantly impacts yield and quality in many crops including wheat. Conventional visual assessment methods for lodging are time-consuming, relatively low-throughput, and subjective, limiting phenotyping accuracy and population sizes in breeding and genetics studies. Here, we demonstrate the considerable power of unmanned aerial systems (UAS) or drone-based phenotyping as a high-throughput alternative to visual assessments for the complex phenological trait of lodging, which significantly impacts yield and quality in many crops including wheat. We tested and validated quantitative assessment of lodging on 2,640 wheat breeding plots over the course of 2 years using differential digital elevation models from UAS. High correlations of digital measures of lodging to visual estimates and equivalent broad-sense heritability demonstrate this approach is amenable for reproducible assessment of lodging in large breeding nurseries. Using these high-throughput measures to assess the underlying genetic architecture of lodging in wheat, we applied genome-wide association analysis and identified a key genomic region on chromosome 2A, consistent across digital and visual scores of lodging. However, these associations accounted for a very minor portion of the total phenotypic variance. We therefore investigated whole genome prediction models and found high prediction accuracies across populations and environments. This adequately accounted for the highly polygenic genetic architecture of numerous small effect loci, consistent with the previously described complex genetic architecture of lodging in wheat. Our study provides a proof-of-concept application of UAS-based phenomics that is scalable to tens-of-thousands of plots in breeding and genetic studies as will be needed to uncover the genetic factors and increase the rate of gain for complex traits in crop breeding.

BackgroundDifferent species of animals are being utilized in traditional therapies by various cultures for a long time and such uses still exist in folk medicine. The present study aimed to document animal-based traditional therapies used by the local communities of Jhelum and Lahore districts of the Punjab province, Pakistan.MethodsField surveys were conducted in 2015–2016 in six different sites of the study areas. Data were collected through semi-structured interviews and face to face conversation with local informants.ResultsThe ethnomedicinal uses of 57 species of animals including mammals, birds, fish, reptiles, amphibian, and invertebrates (30, 25, 25, 7, 3.5, and 3.5%, respectively) were documented. Meat, oil, brain, fats, milk, eggs, and skin were the most utilized body parts. Ovis orientalis punjabiensis, Francolinus francolinus, Sperata sarwari, Channa punctata, Oreochromis niloticus, Ctenopharyngodon idella, Cyprinus carpio, Labeo rohita, and Carassius auratus were reported for the first time to treat human diseases, i.e., allergy, epilepsy, fever, joint pain, and backache, to act as aphrodisiac, and to enhance memory. Streptopelia decaocto and S. tranquebarica were the most frequently utilized species with highest frequency of citation (32 for each). Columba livia depicted highest fidelity level and used value of 92.86% and 0.89, respectively.ConclusionsBeing agro-pastoralists, the inhabitants of Jhelum possess more traditional knowledge compared to Lahore. The present study could be important for conservation and sustainable use of animal biodiversity in this region. Additionally, detailed study on chemical profiling and bioactivities may lead to animal-based novel drug discovery.

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Increasing soil organic matter (SOM) contents improve the resilience of productive soil for future sustainability particularly in poor soil (<1% SOM). This study sought to elucidate how tillage and N fertilizer sources affect soil bulk density, soil organic carbon (SOC) and soil total N (TN) in 0‐ to 20‐cm soil depth. Treatments included minimum till (MT), conventional till (CT), deep till (DT), and twelve N treatments (60 and 120 kg urea N ha−1, 10 and 20 Mg farmyard manure [FYM] ha−1, 10 Mg soybean residue [SR] ha−1 and their combinations along with a control). The experiment was designed in randomized complete block design with split plot arrangement. Soil bulk density increased for DT toward the end of the experiment than CT or MT. The sequestration rates of SOC of MT was 22% higher than DT. The FYM retuned more SOC than SR, however SR returned more TN than FYM. Application of FYM as well as SR sequestered more C than urea or control. Conclusively, SOC returned was increased with 10 Mg FYM ha−1 along with 30 kg urea N ha−1 but TN with 10 Mg SR ha−1 in CT plots. This practice can therefore increase soil quality and productivity, and thus is considered a sustainable approach for soils deficient in organic matter. Core Ideas Minimum tillage improved C stock than shallow or deep tillage. The addition of urea increased SOC contents in SR plots than FYM. C Stocks in FYM and SR fertilized plots was about 3‐ to 4‐fold greater than control. Soybean residue build N stock principally in less plowed plots.

Genetic diversity and relationships among 100 genotypes of Rhynchosia minima collected from four districts of Malakand Division was assessed using 16 morphological characteristics and total seed protein profile. Based on qualitative characteristics, inter-district trait similarity index among genotypes of Swat-Dir Lower and Swat-Buner was 100%, while for Dir Lower-Buner, Dir Lower-Dir Upper, and Buner-Dir Upper, it was 85.71%, 28.57%, and 42.85%, respectively. Total seed protein profile resulted in 8 reproducible bands/loci, where inter-district locus contribution to the genetic disagreement was 75%. Among the 8 loci, B-6 and B-7 were monomorphic and could be R. minima specific, whereas loci B-1, B-4, B-5 and B-8 were observed only in genotypes collected from Buner. All but locus B-1 were present in genotypes of Dir Upper; locus B-8 was missing in genotypes from Dir Lower; loci B-1 and B-4 were absent in genotypes collected from Swat. Two-way cluster analysis resolved genotypes of District Buner and Dir Upper into discrete clusters, highlighting the role of habitat-specific adaptation. Genotypes of Dir Lower and Swat formed mosaic cluster, indicating to the transfer of genes and/or their coevolutionary descent. To the best of our understanding, this is the first ever report addressing genetic variability in R. minima.