Unoccupied aerial system (UAS; i.e., drone equipped with sensors) field-based high-throughput phenotyping (HTP) platforms are used to collect high quality images of plant nurseries to screen genetic materials (e.g., hybrids and inbreds) throughout plant growth at relatively low cost. In this study, a set of 100 advanced breeding maize (Zea mays L.) hybrids were planted at optimal (OHOT trial) and delayed planting dates (DHOT trial). Twelve UAS surveys were conducted over the trials throughout the growing season. Fifteen vegetative indices (VIs) and the 99th percentile canopy height measurement (CHMs) were extracted from processed UAS imagery (orthomosaics and point clouds) which were used to predict plot-level grain yield, days to anthesis (DTA), and silking (DTS). A novel statistical approach utilizing a nested design was fit to predict temporal best linear unbiased predictors (TBLUP) for the combined temporal UAS data. Our results demonstrated machine learning-based regressions (ridge, lasso, and elastic net) had from 4- to 9-fold increases in the prediction accuracies and from 13- to 73-fold reductions in root mean squared error (RMSE) compared to classical linear regression in prediction of grain yield or flowering time. Ridge regression performed best in predicting grain yield (prediction accuracy = ~0.6), while lasso and elastic net regressions performed best in predicting DTA and DTS (prediction accuracy = ~0.8) consistently in both trials. We demonstrated that predictor variable importance descended towards the terminal stages of growth, signifying the importance of phenotype collection beyond classical terminal growth stages. This study is among the first to demonstrate an ability to predict yield in elite hybrid maize breeding trials using temporal UAS image-based phenotypes and supports the potential benefit of phenomic selection approaches in estimating breeding values before harvest.
A total of 13 maize populations from the drought-tolerant mini core collection from Maize Research Institute gene bank were evaluated for oil, protein, and tryptophan contents, fatty acid (FA) composition, and kernel characteristics. All accessions are high oil (5.8-7.9%) and protein (10.58-12.45%) genotypes. Most of the accessions showed high contents of tryptophan (0.070-0.081%) and saturated (12.65-17.91%) and monounsaturated (24.19-45.52%) FAs. Significant positive correlations were found between oil and protein and between oil and tryptophan contents (p < 0.01). Correlations between oil and principal FA were non-significant. Several accessions showed multiple nutritional advantages. For example, IP6428 had high oil (7.3%), tryptophan (0.081%), and saturated FA (17.9%) contents. Moreover, a positive correlation (p < 0.01) between palmitic (13.68%) and oleic (34.74%) acids enables the use of IP6428 for developing lines high in these FAs. Because drought-tolerant accessions were selected in both subtropical and temperate zones, they could be used for breeding value-added maize adapted to both environments.
Phenotypic measurements under controlled cultivation conditions are essential to gain a mechanistic understanding of plant responses to environmental impacts and thus for knowledge-based improvement of their performance under natural field conditions. Twenty maize inbred lines (ILs) were phenotyped in response to two levels of water and nitrogen supply (control and stress) and combined nitrogen and water deficit. Over a course of 5 weeks (from about 4-leaf stage to the beginning of the reproductive stage), maize phenology and growth were monitored by using a high-throughput phenotyping platform for daily acquisition of images in different spectral ranges. The focus of the present study is on the measurements taken at the time of maximum water stress (for traits that reflect plant physiological properties) and at the end of the experiment (for traits that reflect plant architectural and biomass-related traits). Twenty-five phenotypic traits extracted from the digital image data that support biological interpretation of plant growth were selected for their predictive value for mid-season shoot biomass accumulation. Measured fresh and dry weights after harvest were used to calculate various indices (water-use efficiency, physiological nitrogen-use efficiency, specific plant weight) and to establish correlations with image-derived phenotypic features. Also, score indices based on dry weight were used to identify contrasting ILs in terms of productivity and tolerance to stress, and their means for image-derived and manually measured traits were compared. Color-related traits appear to be indicative of plant performance and photosystem II operating efficiency might be an importance physiological parameter of biomass accumulation, particularly under severe stress conditions. Also, genotypes showing greater leaf area may be better adapted to abiotic stress conditions.
Breeding program aimed at converting standard maize inbred lines to their quality protein maize (QPM) counterparts for growing in temperate climate is being conducted at Maize Research Institute (MRI). The objective of the research presented herein was to develop QPM versions of two commercial ZP inbreds through marker assisted selection (MAS) with opaque2 specific molecular markers, while maintaining their good agronomic performances and combining abilities. Donor line was a tropical QPM line CML 144. After two backcross and three selfing generations, six near isogenic lines (NILs) with 93% recovery of the recurrent parent genome were created from one cross. Average increments of 30% in tryptophan content and 36% in quality index were obtained, as well as kernels with less than 25% opaque endosperm. Grain yield was increased by 11–31% and combining abilities of the improved lines were on a par with the original line. Correlations between biochemical and agronomic parameters revealed that selection for plant height, ear length and kernel row number together with tryptophan content could be recommended for development of QPM with this material. However, several impediments emerged during selection. Major drawbacks in NIL development were small number of opaque2 recessive homozygotes (4.5% and 7.6% in BC2F2 of two crosses) and poor seed set throughout selection, which led to the loss of one cross. Moreover, in the other cross many plants in different generations had to be omitted from further selection due to the insufficient number of kernels. This phenomenon could be explained by incompatibility between pollen and style, possibly due to the exotic donor germplasm. Overall, it could be expected that the use of NILs, which are adapted to temperate climate and have high percentage of domestic germplasm, would outbalance the noted impediments and increase MAS efficiency in different breeding programs.
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