Active-optical sensor readings from an N non-limiting area standard established within a farm field are used to predict yield in the standard. Lower yield predictions from sensor readings obtained from other parts of the field outside of the N non-limiting standard area indicate a need for supplemental N. Active-optical sensor algorithms for predicting corn (Zea mays, L.) yield to direct in-season nitrogen (N) fertilization in corn utilize red NDVI (normalized differential vegetative index). Use of red edge NDVI might improve corn yield prediction at later growth stages when corn leaves cover the inter-row space resulting in “saturation” of red NDVI readings. The purpose of this study was to determine whether the use of red edge NDVI in two active-optical sensors (GreenSeeker™ and Holland Scientific Crop Circle™) improved corn yield prediction. Nitrogen rate experiments were established at 15 sites in North Dakota (ND). Sensor readings were conducted at V6 and V12 corn. Red NDVI and red edge NDVI were similar in the relationship of readings with yield at V6. At V12, the red edge NDVI was superior to the red NDVI in most comparisons, indicating that it would be most useful in developing late-season N application algorithms.

Background: Development of a high quality reference sequence is a daunting task in crops like wheat with large (~17Gb), highly repetitive (>80%) and polyploid genome. To achieve complete sequence assembly of such genomes, development of a high quality physical map is a necessary first step. However, due to the lack of recombination in certain regions of the chromosomes, genetic mapping, which uses recombination frequency to map marker loci, alone is not sufficient to develop high quality marker scaffolds for a sequence ready physical map. Radiation hybrid (RH) mapping, which uses radiation induced chromosomal breaks, has proven to be a successful approach for developing marker scaffolds for sequence assembly in animal systems. Here, the development and characterization of a RH panel for the mapping of D-genome of wheat progenitor Aegilops tauschii is reported. Results: Radiation dosages of 350 and 450 Gy were optimized for seed irradiation of a synthetic hexaploid (AABBDD) wheat with the D-genome of Ae. tauschii accession AL8/78. The surviving plants after irradiation were crossed to durum wheat (AABB), to produce pentaploid RH₁s (AABBD), which allows the simultaneous mapping of the whole D-genome. A panel of 1,510 RH₁ plants was obtained, of which 592 plants were generated from the mature RH₁ seeds, and 918 plants were rescued through embryo culture due to poor germination (<3%) of mature RH₁ seeds. This panel showed a homogenous marker loss (2.1%) after screening with SSR markers uniformly covering all the D-genome chromosomes. Different marker systems mostly detected different lines with deletions. Using markers covering known distances, the mapping resolution of this RH panel was estimated to be <140kb. Analysis of only 16 RH lines carrying deletions on chromosome 2D resulted in a physical map with cM/cR ratio of 1:5.2 and 15 distinct bins. Additionally, with this small set of lines, almost all the tested ESTs could be mapped. A set of 399 most informative RH lines with an average deletion frequency of ~10% were identified for developing high density marker scaffolds of the D-genome. Conclusions: The RH panel reported here is the first developed for any wild ancestor of a major cultivated plant species. The results provided insight into various aspects of RH mapping in plants, including the genetically effective cell number for wheat (for the first time) and the potential implementation of this technique in other plant species. This RH panel will be an invaluable resource for mapping gene based markers, developing a complete marker scaffold for the whole genome sequence assembly, fine mapping of markers and functional characterization of genes and gene networks present on the D-genome.

Background: The uneven distribution of recombination across the length of chromosomes results in inaccurate estimates of genetic to physical distances. In wheat (Triticum aestivum L.) chromosome 3B, it has been estimated that 90% of the cross over events occur in distal sub-telomeric regions representing 40% of the chromosome. Radiation hybrid (RH) mapping which does not rely on recombination is a strategy to map genomes and has been widely employed in animal species and more recently in some plants. RH maps have been proposed to provide i) higher and ii) more uniform resolution than genetic maps, and iii) to be independent of the distribution patterns observed for meiotic recombination. An in vivo RH panel was generated for mapping chromosome 3B of wheat in an attempt to provide a complete scaffold for this ~1 Gb segment of the genome and compare the resolution to previous genetic maps. Results: A high density RH map with 541 marker loci anchored to chromosome 3B spanning a total distance of 1871.9 cR was generated. Detailed comparisons with a genetic map of similar quality confirmed that i) the overall resolution of the RH map was 10.5 fold higher and ii) six fold more uniform. A significant interaction (r = 0.879 at p = 0.01) was observed between the DNA repair mechanism and the distribution of crossing-over events. This observation could be explained by accepting the possibility that the DNA repair mechanism in somatic cells is affected by the chromatin state in a way similar to the effect that chromatin state has on recombination frequencies in gametic cells. Conclusions: The RH data presented here support for the first time in vivo the hypothesis of non-casual interaction between recombination hot-spots and DNA repair. Further, two major hypotheses are presented on how chromatin compactness could affect the DNA repair mechanism. Since the initial RH application 37 years ago, we were able to show for the first time that the iii) third hypothesis of RH mapping might not be entirely correct.

Topographic features impact biomass and other agriculturally relevant observables. However, conventional tools for processing digital elevation model (DEM) data in geographic information systems have severe limitations. Typically, 3-by-3 window sizes are used for evaluating the slope, aspect and curvature. As a consequence, high resolution DEMs have to be resampled to match the size of typical topographic features, resulting in low accuracy and limiting the predictive ability of any model using such features. In this paper, we examined the usefulness of DEM-derived topographic features within Random Forest models that predict biomass. Our model utilized the derived topographic features and achieved 95.31% accuracy in predicting Normalized Difference Vegetation Index (NDVI) compared to a 51.89% accuracy obtained for window size 3-by-3 in the traditional resampling model. The efficacy of partial dependency plots (PDP) in terms of interpretability was also assessed.

Obtaining physiological insights from microarray experiments requires computational techniques that relate gene expression data to functional information. Traditionally, this has been done in two consecutive steps. The first step identifies important genes through clustering or statistical techniques, while the second step assigns biological functions to the identified groups. Recently, techniques have been developed that identify such relationships in a single step.