Unpredictable pathogen pressures resulting from changing climatic patterns have required plant breeders to breed crop cultivars with durable resistance to multiple plant pathogens. The genetic basis of multiple disease resistance (MDR) is an important component in building durable resistance in crop plants. Maize (Zea mays L.) inbred NY22613, developed at Cornell University, has shown resistance to northern leaf blight (NLB), gray leaf spot (GLS), common rust, and Stewart's wilt (SW). In order to unravel the genetic basis of MDR in NY22613, quantitative trait locus (QTL) mapping and colocalization studies were conducted. A BC3S3 biparental mapping population (resistant inbred NY22613 and susceptible recurrent inbred Oh7B) was used to map the QTL responsible for disease resistance. The analysis revealed that 16 QTL were associated with NLB resistance, 17 QTL with GLS resistance, and 16 QTL with SW resistance. No QTL were colocalized for all three diseases. Three QTL were shared for NLB and GLS in chromosomes 7, 9, and 10 and one QTL was shared for GLS and SW in chromosome 2. These QTL contain the following genes that have been previously associated with disease resistance: Zm00001d002005 (lg1, liguleless1), Zm00001d024007, Zm00001d024008, LOC103642379, and LOC103641009. These regions also contain the following novel genes, which have not been associated with any function: LOC541757, Zm00001d044974, Zm00001d044975, and LOC109941121. To select individuals with MDR, a novel selection method was developed that combines phenotypic data, QTL data, and high‐density marker information in a cluster analysis designated as the high‐density marker phenotype (HEMP) QTL selection strategy.
Recent advances in high-throughput phenotyping allow breeders to collect phenotypic data with a level of accuracy that was impossible to achieve previously. However, many of these technologies depend on leveraging-controlled environments like green houses or growth chambers. While these controlled phenotypes can have strategic value for gene discovery, their relevance for breeding and understanding genotype x environment interactions to predict field performance is an active field of study and currently limited, at best. This chapter deals with various technologies that have empowered the collection of phenotypic data directly under field conditions and the relative advantages and disadvantages of using them to collect agronomic phenotypes. Important considerations to be aware of before planning a high-throughput phenotyping experiment that use technologies like field spectroscopy and remote sensing are also discussed including a review of various publically available and/or commercial aerial, ground-based and root phenotyping platforms.
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