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- Author or Editor: Julio Solis x
- HortScience x
A scanner-based minirhizotron (MR) system detected initial adventitious root (AR) development associated with transplant establishment. The system also documented the transition of ARs into pencil roots (PRs) and, in some cases, storage roots (SRs). In general, the MR system underestimated destructive sampling-based (DS) estimates of newly initiated AR (NAR), PR, and SR counts. Angled or vertical single sampling tubes underestimated NAR count by 85% and 79%, respectively. Regardless of installation position, single tube-based measurements underestimated PR and SR count by 83% and 95%, respectively. However, it was found that two vertically installed tubes underestimated NAR count by only 48%. The potential ability of paired sampling tubes to discriminate NAR count differences in response to experimental treatments was confirmed in a simple rain shelter experiment. The paired MR and DS systems detected 83% and 56% reduction in NAR count among plots with rain shelters, respectively. However, it appeared that the presence of tubes interfered with SR formation of monitored AR segments. Despite this limitation, the results show the potential for incorporating MR systems in ongoing and future studies that aim to qualitatively and quantitatively document sweetpotato AR system response to agroclimatic variables and management interventions during the initial SR bulking stage.
A prototype phenology-driven Bayesian belief network (BBN) model, named BxNET, was developed to represent the relationship between fresh market yield (U.S. #1 grade) and agroclimatic variables known to influence the critical storage root initiation stages in ‘Beauregard’ sweetpotato. This data-driven model was developed from experimental data collected over 3 years of field trials in which management variables were kept as uniform as possible. The BBN was developed assuming that soil moisture measured at the 15-cm depth was not a limiting variable during the first 20 days after transplanting, during which the onset of storage root initiation determined the majority of storage root yield at harvest. The absence of influence from weeds, disease, insect pests, and chemical injury was also assumed. Accuracy of the fully parameterized working prototype was estimated through leave-one-out cross-validation (14% error rate), validation on an independent test data set (20% error rate), and area under the receiving operator characteristic curve (0.59) analysis. As a result of its empirical nature, BxNET is only applicable to the cultivar, location, and the limited set of environmental (air temperature, soil temperature, relative humidity, solar radiation) and management variables as defined in the 3-year study. This beta-level model can serve as a foundation for the development of a final working model through further testing and validation. Additional validation data may require revision of the current model structure and conditional probabilities. These validation studies will also allow the model to be used in other locations. BxNET can be expanded to include other causal variables such as weed incidence, disease presence, insects, and chemical injury. Such an expansion can lead to the development of a model-based decision support system for sweetpotato production. Such a system can help model alternative management scenarios and determine the most reasonable management interventions to achieve optimum yield outcomes under different agroclimatic conditions.
This study characterized lateral root (LR) development attributes during the onset of storage root (SR) initiation stage in ‘Beauregard’ sweetpotato. SR initiation has been defined as the appearance of cambia around the protoxylem and secondary xylem elements. Our results showed that 20-day-old adventitious roots (ARs) classified as SRs had 53% and 85% greater mean LR count than pencil roots (PRs) and lignified roots (LGs), respectively. SRs had 53% and 78% greater mean LR density relative to PRs and LGs, respectively. SRs had 66% and 130% greater mean total LR length than PRs and LGs, respectively. SRs had lower mean main root (MR)/LR length ratio compared with PRs (–38%) and LGs (–60%). SRs had 70% and 134% greater mean surface area than PRs and LGs, respectively. SRs had lower mean MR/LR surface area ratio compared with PRs (–42%) and LGs (–62%). The plot of the first and second principal components revealed the presence of a gradient between extreme LG and SR clusters, suggesting a developmental transition between LGs and SRs with PRs representing an intermediate developmental stage. Although AR architecture is not the sole determinant of SR formation, our data help provide a basis for integrating AR architecture attributes with other factors that are known to influence SR initiation. Growth substrate moisture variability influenced LR development during the critical SR initiation period. Relative to the control treatments, water deprivation 10 to 20 days after transplanting (DAT) reduced mean LR count, length, and surface area by 49%, 103%, and 94%, respectively. Saturated conditions 10 to 20 DAT reduced mean LR count, length, and surface area by 75%, 81%, and 77%, respectively. These results represent the first evidence for the association between anatomical cues of SR initiation and root architecture and provide corroborating data that soil moisture variability 10 to 20 DAT directly influences SR yield potential through AR architecture modifications that are associated with diminished SR formation. This information can be used to further optimize SR yield by identifying agroclimatic and management variables that are associated with desirable LR development during the critical SR initiation stage.