Discrimination of filled and unfilled grains of rice panicles using thermal and RGB images

In recent days, the agricultural research community is focusing on the development of different varieties of aerobic rice, as it consumes less water for its growth. In general, the yield of a crop is considered as a critical performance metric to evaluate different varieties of rice. The count of filled grains in panicles provides a measure for the yield of a crop. The evaluation of yield is a laborious, tedious process and requires human intervention. Hence, this study aims to automate the process for differentiating filled and unfilled grains of rice across different genotypes/varieties and also to help agricultural scientists in the rapid evaluation of different varieties. More precisely, this paper proposes two novel methods that involve RGB and thermal images: (a) Discrimination based on RGB Images (DRI) (b) Discrimination based on Thermal Images (DTI). The study of proposed methods on 15 rice-panicles of different genotypes indicates that DRI method, which involves colour of grains, is found to be challenging to discriminate between filled and unfilled grains. Whereas, DTI method, which makes use of thermal images in differentiating filled and unfilled grains, is found to be profoundly convenient. The performance analysis demonstrates that the proposed DTI method, with averaged absolute errors (AAEs) in discriminating filled grains (2.66%) and unfilled grains (11.389%), outperforms the proposed DRI method with an AAEs in discriminating filled grains (10.664%) and unfilled grains (34.296%). The present investigation resulted in the development of DTI method to discriminate against the filled and unfilled grains across genotypes, and it can be used in rice improvement programs in the future

Combining High Oleic Acid Trait and Resistance to Late Leaf Spot and Rust Diseases in Groundnut (Arachis hypogaea L.)

High oleic trait, resistance to rust and late leaf spot (LLS) are important breeding objectives in groundnut. Rust and LLS cause significant economic loss, and high oleic trait is an industry preferred trait that enhances economic returns. This study reports marker-assisted selection to introgress high oleic content, resistance to LLS and rust into Kadiri 6 (K 6), a popular cultivar. The alleles for target traits were selected using linked allele-specific, simple sequence repeats and single nucleotide polymorphic markers. The F1s (384), intercrossed F1s (441), BC1F1s (380), BC1F2s (195), and BC1F3s (343) were genotyped to obtain desired allelic combination. Sixteen plants were identified with homozygous high oleic, LLS and rust resistance alleles in BC1F2, which were advanced to BC1F3 and evaluated for disease resistance, yield governing and nutritional quality traits. Phenotyping with Near-Infrared Reflectance Spectroscopy identified three lines (BC1F3-76, BC1F3-278, and BC1F3-296) with >80% oleic acid. The identified lines exhibit high levels of resistance to LLS and rust diseases (score of 3.0–4.0) with preferred pod and kernel features. The selected lines are under yield testing trials in multi-locations for release and commercialization. The lines reported here demonstrated combining high oleic trait with resistance to LLS and rust diseases

African and Asian origin pearl millet populations: Genetic diversity pattern and its association with yield heterosis

Pearl millet [Pennisetum glaucum (L.) R. Br.] is a staple food crop of arid and semi-arid regions of Asia and Africa. Forty-five pearl millet populations of Asian and African origin were assessed for genetic diversity using 29 simple sequence repeat (SSR) markers. The SSR-based clustering and structure analyses showed that Asian origin–Asian bred (As-As) and African origin–African bred (Af-Af) populations were distributed across seven clusters, indicating no strong relationship among populations with their geographical origin. Most of the African origin–Asian bred (Af-As) populations had a higher average number of alleles per locus than As-As or Af-Af populations, and the majority of them clustered separately from As-As or Af-Af populations, indicating that introgression of African origin breeding materials led to the development of new gene pools adapted to the Asian region. Fourteen populations representing seven clusters were crossed according to a diallel mating design to generate 91 population hybrids (seeds of direct and reciprocal crossesweremixed) and evaluated at three locations in 2016. All the 91 hybrids when partitioned into three groups based on genetic distance (GD) between parental combinations (low,moderate, and high), revealed no correlation between GD and panmictic midparent heterosis in any of the groups, indicating that grain yield heterosis cannot be predicted based on GD. Two population hybrids (GB 8735 × ICMP 87307 and Sudan I × Ugandi) exhibited high levels of yield heterosis over standard checks and can be further utilized using different breeding schemes to develop high-yielding pearl millet cultivars

31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two

Background The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd. Methods We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background. Results First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001). Conclusions In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival

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Not AvailableThe success of plant breeding for crop improvement is primarily dependent on effective utilization of coding and non-coding genetic elements. MicroRNAs are short non-coding RNAs transcribed from specific class of genes. These tiny RNAs regulate key biological processes in plants by targeting messenger RNAs for cleavage or translational inhibition. We herein describe the diverse functions of some of the well-studied miRNAs in different plant species and the possibility of using these miRNAs for crop improvement through genome editing. Some of the successful applications of genome editing of miRNAs are also described. This review presents key information on strategies and considerations to utilize miRNAs for genome editing with an example of rice. The major challenges of genome editing of miRNAs and the necessity of further studies to develop comprehensive knowledge of miRNA mediated gene regulatory networks and trait improvement, have been described in detail.Not Availabl

Molecular Analysis of Oryza latifolia Desv. (CCDD Genome)-Derived Introgression Lines and Identification of Value-Added Traits for Rice (O. sativa L.) Improvement

Oryza latifolia\ua0is a tetraploid wild\ua0Oryza\ua0species with a CCDD genome that has been reported to harbor resistance to bacterial blight (BB), brown planthopper, and whitebacked planthopper. Aside from these traits,\ua0O. latifolia\ua0is also being tapped as a new source of resistance to lodging and high biomass production. To explore the genetic potential of\ua0O. latifolia\ua0as a novel genetic resource for the improvement of existing\ua0O. sativa\ua0cultivars, 27 disomic derivatives of\ua0O. latifolia\ua0monosomic alien addition lines (MAAL) were characterized for alien chromosome segment introgressions and evaluated for yield components, BB resistance, and strong stem characteristics. A total of 167 simple sequence repeat, sequence tagged site, and single nucleotide polymorphism markers, along with newly developed indel markers that were specifically designed to detect\ua0O. latifolia\ua0chromosome segment introgressions in an\ua0O. sativa\ua0background, were used to define alien introgressions in 27 disomics derived from\ua0O. latifolia\ua0MAALs. Genotype data showed that 32 unique introgressions spanning 0.31–22.73Mb were introgressed in different combinations in each of the 27 disomic derivatives. Evaluation of the disomic derivatives for agronomic traits identified lines with putative QTLs for resistance to Philippine races 3A, 4, 9A, and 9D of BB. Putative quantitative trait loci (QTLs) conferring strong stem in 19 out of the 27 disomic derivatives studied were also identified from\ua0O. latifolia\ua0introgressions on chromosome 6

Identification of Water-Stressed Area in Maize Crop Using Uav Based Remote Sensing

Agronomic inputs such as water , nutrients and fertilisers play a vital role in the health, growth and yield of crops. The lack of each of these inputs induces biotic and abiotic stress in the crop. Farmers are relying on groundwater because of decreased rainfall. The irrigation method can be improved by acquiring awareness of the health of crops and soils. In general, crop and soil quality is controlled by means of manual observation, which is time-consuming, labour-intensive and contributes to incorrect choices and substantial waste of resources. There is also an immediate need to automate the inspection process that will finally benefit farmers and agricultural scientists. In this paper, the identification of the water-stressed areas in the crop(maize) field has been studied, and an Unmanned Aerial Vehicle (UAV) based remote sensing is used to automate the crop health-monitoring process. We proposed a framework (model) based on Convolutional Neural Networks (CNN) to identify the stressed and normal/healthy areas in the maize crop field. The performance of the proposed framework has been compared with different models of CNN, such as ResNet50, VGG-19, and Inception-v3. The results show that the proposed model outperforms the baseline models and successfully classify stressed and normal areas with 95 % accuracy on train data and 93 % accuracy with 0.9370 precision and 0.9403 F1 score on test data

CIG based Stress Identification Method for Maize Crop using UAV based Remote Sensing

The health and yield of crops depend on the use of water, nutrients, and fertilizers. Due to climatic changes and reduction in rainfall, farmers are relying on groundwater for irrigation, which should be used optimally. The use of water and other agronomic inputs can be optimized by monitoring the health of crops and soil. Usually, it is done by manual observation, which is labor-intensive and time-consuming. In this paper, we propose Chlorophyll Index Green (CIG) vegetative index-based method for monitoring the crop health using near-infrared, green, and red band images acquired using a multispectral camera mounted on Unmanned Ariel Vehicle (UAV). The proposed method clearly classifies the water-stressed area of the field and helps in optimizing the irrigation process and monitoring the crop-health