High-Throughput Canopy and Belowground Phenotyping of a Set of Peanut CSSLs Detects Lines with Increased Pod Weight and Foliar Disease Tolerance

Abstract

We deployed field-based high-throughput phenotyping (HTP) techniques to acquire trait data for a subset of a peanut chromosome segment substitution line (CSSL) population. Sensors mounted on an unmanned aerial vehicle (UAV) were used to derive various vegetative indices as well as canopy temperatures. A combination of aerial imaging and manual scoring showed that CSSL 100, CSSL 84, CSSL 111, and CSSL 15 had remarkably low tomato spotted wilt virus (TSWV) incidence, a devastating disease in South Georgia, USA. The four lines also performed well under leaf spot pressure. The vegetative indices showed strong correlations of up to 0.94 with visual disease scores, indicating that aerial phenotyping is a reliable way of selecting under disease pressure. Since the yield components of peanut are below the soil surface, we deployed ground penetrating radar (GPR) technology to detect pods non-destructively. Moderate correlations of up to 0.5 between pod weight and data acquired from GPR signals were observed. Both the manually acquired pod data and GPR variables highlighted the three lines, CSSL 84, CSSL 100, and CSSL 111, as the best-performing lines, with pod weights comparable to the cultivated check Tifguard. Through the combined application of manual and HTP techniques, this study reinforces the premise that chromosome segments from peanut wild relatives may be a potential source of valuable agronomic traits.

Wavelet Analysis of GPR Data for Belowground Mass Assessment of Sorghum Hybrid for Soil Carbon Sequestration

“…The latter utilizes a unique air-launched resistively loaded vee dipole antenna design, which had been developed as a means to detect buried objects without the necessity of ground contact [30][31][32]. The antenna array unit has been used in other published research [15,16,23,33] and is pictured in Figure 2. An air-launched antenna was used because of its greater suitability for scanning uneven agricultural surfaces with the accepted trade-offs of a strong ground return and less energy being transmitted into the soil subsurface than with a ground-coupled unit [34].…”

“…An alternative to an image analysis approach is a frequency-based analysis where the GPR signal is decomposed into its component frequencies, which are then evaluated as features predictive of biomass. Observed root biomass of cassava and peanut has been predicted using this method [16,23]. An additional alternative for GPR feature extraction is the use of wavelet methodologies.…”

‘Omics’ Approaches for Crop Improvement

“…Overall, throughout this Special Issue, the works by Pandit et al [13], Gimode et al [20], and Burbano-Erazo et al [19], respectively illustrated in rice, peanuts, and beans, the feasibility and power to update classical introgression breeding [35] with modern 'omics' approaches, such as genomics and phenomics. This integration enables guiding more rapidly and with better precision the pyramiding of exotic variation into elite commercial backgrounds.…”

“…Fortunately, in this collection, two studies have harnessed cropwild diversity through phenomics. First, Gimode et al [20] studied the morphological consequences of a chromosome segment in peanuts (Arachis hypogaea) inherited from a wild relative. The authors demonstrated that this chromosome segment sources valuable trait variation from the exotic gene pool into the cultivated background.…”

“…Data Availability Statement: Raw datasets were made available by each of the ten published articles [11][12][13][14][15][16][17][18][19][20] from the Special Issue on "Omics Approaches for Crop Improvement" (https://www. mdpi.com/journal/agronomy/special_issues/crop_omics_genetic (revised 18 May 2023).…”