Īccelerating genetic gain can be achieved by increasing selection intensity, accuracy and genetic variation, and/or reducing cycle time (see also Chap. Alternative ways to dissect the role of phenotypic on genetic gain have been assessed elsewhere. Continuing on, the potential contribution of phenotyping to wheat breeding is placed in context by taking the genetic-advance determinants as a framework of reference. 7), usually referred to the increase after one generation (or cycle) has passed. 27.1), which is defined as the amount of increase in performance achieved per unit time through artificial selection (see Chap. The aim of an efficient phenotyping method is to enhance genetic gain (Fig. In that sense we will introduce the term high throughput field phenotyping (HTFP) Literature and examples included will refer as much as possible to wheat or other small grain cereals under field conditions. In what follows, this chapter will address crop phenotyping within the context of its implementation under real growing (i.e., field) conditions. A recent paper has defined the high throughput phenotyping as “relatively new for most breeders and requiring significantly greater investment with technical hurdles for implementation and a steeper learning curve than the minimum data set,” where visual assessments are often the preferred choice. Moreover, in case phenotyping is conducted visually this results in an inflation of measuring error, which might be further increased by fatigue setting, and is prone to subjective appreciation of each person. Another important point to consider is that phenotyping of the large genotype sets is generally only feasible if conducted by several persons. However, manual phenotyping of complex traits, which is often the case when focusing on drought or heat tolerance, requires experienced professionals and is time intensive. Phenotyping of simple traits (e.g., plant height) can be achieved even by untrained personnel within a manageable time frame. While this chapter will focus on the general aspects concerning wheat phenotyping, specific information about special setups is very abundant. This is the case of phenotyping arrangements aimed to evaluate resilience to particular stressors (e.g., diseases, pests, waterlogging…) or the performance of hidden plant parts (i.e., roots) or non-laminar photosynthetic organs (e.g., ears, culms). This does not exclude for example the interest of indoors (i.e., fully controlled) platforms for specific studies or traits to be evaluated, or even the need to developing special outdoor (i.e., near field) but still controlled facilities. In that sense, a basic concern for many breeders is still the controlled nature of many of the phenotyping platforms developed in recent years and the perception that most of these platforms are unable to fully replicate environmental variables influencing complex traits at the scale of climate variability nor handle the elevated numbers of phenotypes required by breeding programs. However, for many breeders, the adoption of new phenotyping traits and methodologies only makes sense if they provide added value relative to current phenotyping practices. 28 and 29) and prediction models (see Chap. In fact, high throughput precision phenotyping is becoming more accepted as viable way to capitalize on recent developments in crop genomics (see Chaps. Phenotyping is nowadays considered a major bottleneck limiting the breeding efforts. This choice of traits and phenotyping techniques is based on results from a large set of retrospective and other physiological studies that have proven the value of these traits together with the highlighted phenotypical approaches. In that sense and considering the physiological determinants of wheat yield that are amenable for indirect selection, we highlight stomatal conductance and stay green as key observations. Finally, data integration and its implementation in practice is discussed. Different remote sensing techniques and platforms are presented, while concerning lab techniques only a well proven trait, such as carbon isotope composition, is included. Emphasis will be given to field high throughput phenotyping, including affordable solutions, together with the need for environmental and spatial characterization. The chapter aims to provide guidance on how phenotyping may contribute to the genetic advance of wheat in terms of yield potential and resilience to adverse conditions.
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