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  • Author or Editor: Arthur Villordon x
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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.

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The presence of copia-like retrotransposon sequences in sweetpotato [Ipomoea batatas (L.) Lam.] was investigated. PCR-based amplification using primers to highly conserved copia-like reverse transcriptase sequences produced several products corresponding to the expected target size (≈300 bp) that were subsequently isolated and cloned. A random sample of the clones were sequenced and all six reading frames were translated into their corresponding amino acid sequences. Sequence analysis revealed the presence of 22 copia-like reverse transcriptase sequences corresponding to various subfamilies. The presence of several sequence families in the genome is indicative of past or recent transposition activity. Southern blot analysis suggested that these copia-like sequences were present in several hundred copies in the sweetpotato genome. Data also showed retrotransposon insertion polymorphisms between a limited sample of virus-tested and virus-infected sweetpotato clones, indicating putative activity and mobility. This investigation documented the presence of copia-like retrotransposon sequences in the sweetpotato genome. This is an important step in clarifying the possible association between mobile genetic elements and the unusually high incidence of somatic mutations that may result in clonal decline in sweetpotato and other asexually propagated crops. Data presented provides information on the possible use of retrotransposons as genetic markers for sweetpotato crop improvement.

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Our research compared the extent of genomic variability between plants originating from adventitious sprouts and nodal cultures. Plant materials, derived from a single sprout and originating from a storage root each of `Jewel,' `Sumor,' and L87-95, were clonally propagated for seven generations nodally and through adventitious sprouts. PCR-based analysis using 15 random primers identified 58 scorable molecular markers, 37 (63.79%) of which were shared by all three genotypes represented by 60 samples (10 nodal and 10 adventitiously derived plants/genotype). Of 29 putatively polymorphic markers, 24 (82.75%) were putative polymorphisms across the entire data set. The remaining four (13.79%) represented putatively fixed genotypic differences that were monomorphic within genotypes. A multidimensional scaling analysis differentiated seven (23.33%) adventitiously derived phenotypic marker variants, compared to four (13.33%) among nodal materials. Our results support previous findings that, relative to nonmeristematic tissues, meristematic regions strictly control cell division and DNA synthesis that exclude DNA duplication and other irregularities.

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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.

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The primary objective of this work was to generate species-specific information about root architectural responses to variations in inorganic phosphate (Pi) availability at the onset of storage root formation among six sweetpotato (Ipomoea batatas) cultivars. Three Pi levels were used: 0 (low Pi); 0.17 (medium Pi); and 0.34 (high Pi) g/pot triple super phosphate (0N–46P–0K). The check cultivar ‘Bayou Belle’ (BB) consistently showed evidence of storage root formation at 15 days in adventitious roots (ARs) grown across three Pi levels and two planting dates (PDs). Storage root formation was also detected in ‘Orleans’ (OR) and ‘Beauregard’ (BX), but it was less consistent relative to BB. In general, BB had the lowest adventitious root (AR) number relative to the other cultivars, but the magnitudes of difference varied with Pi availability and PD. With the first PD, BX had a 45% higher AR number compared with BB in low Pi conditions; however, there were no differences in the second PD. Within cultivars, BX and Okinawa grown in low Pi showed combined 17% and 24% reductions in primary root length (PRL) relative to roots grown in high Pi. BB had a higher lateral root number (LRN) and lateral root density (LRD) across Pi levels, corroborating prior data regarding the association of these root architectural attributes with the onset of storage root formation. The experimental data support the hypothesis regarding the existence of genetic variation for Pi efficiency in sweetpotato and that some well-documented Pi-efficient root traits like high LRN and LRD are indirectly selected for in-breeding programs that focus on early storage root formation and stable yields across environments.

Open Access

Greenhouse and field culture systems were used to study the effect of drought conditions on the storage root (SR) formation in ‘Beauregard’ sweetpotato (Ipomoea batatas). In the greenhouse culture system, drought was simulated by withholding water for 5 and 10 days after transplanting (DAT) cuttings in dry sand. Control plants received water at planting and every 3 days thereafter. In the field studies, natural drought conditions and selective irrigation were used to impose water deprivation during the critical SR formation period. Greenhouse drought for 5 and 10 DAT reduced the number of SRs by 42% and 66%, respectively, compared with the controls. Field drought resulted in a 49% reduction in U.S. #1 SR yield compared with the irrigated condition. Quantitative real-time polymerase chain reaction (PCR) analysis showed differential expression of a set of sweetpotato transcription factors and protein kinases among greenhouse-grown plants subjected to well-watered conditions and water deficit during 5 DAT. A significant enhancement of expression was observed for known drought stress-associated genes such as an abscisic acid-responsive elements-binding factor, dehydration-responsive element-binding factor, and homeo-domain-zip proteins. Members of calcium-binding proteins showed differential expression under drought stress. For the first time it is reported that knotted1-like homeobox and BEL1-like genes showed altered expression in response to drought stress under a greenhouse condition. In summary, the results suggest that water deprivation during the SR formation period influences root development and expression patterns of stress-responsive genes and those previously found associated with SR formation in sweetpotato.

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Web-accessible germplasm databases allow stakeholders to interactively search and locate information in real time. These databases can also be configured to permit designated users to remotely add, delete, or update information. These resources assist in decision-making activities that are related to germplasm documentation, conservation, and management. We report the development of a web-accessible database of Kenyan sweetpotato (Ipomoea batatas) varieties using open source software. Kenya is located in eastern Africa, a region that is considered one of the centers of diversity for sweetpotato. We describe the software applications used in developing the germplasm database as well as the web interface for displaying and interactively searching records. This report demonstrates that open source software can be used in developing a web-enabled database with management features similar to those found in proprietary or commercial applications.

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Predictive models of optimum sweetpotato (Ipomoea batatas) harvest in relation to growing degree days (GDD) will benefit producers and researchers by ensuring maximum yields and high quality. A GDD system has not been previously characterized for sweetpotato grown in Louisiana. We used a data set of 116 planting dates and used a combination of minimum cv, linear regression (LR), and several algorithms in a data mining (DM) mode to identify candidate methods of estimating relationships between GDD and harvest dates. These DM algorithms included neural networks, support vector machine, multivariate adaptive regression splines, regression trees, and generalized linear models. We then used candidate GDD methods along with agrometeorological variables to model US#1 yield using LR and DM methodology. A multivariable LR model with the best adjusted r2 was based on GDD calculated using this method: maximum daily temperature (Tmax) – base temperature (B), where if Tmax > ceiling temperature [C (90 °F)], then Tmax = C, and where GDD = 0 if minimum daily temperature <60 °F. The following climate-related variables contributed to the improvement of adjusted r2 of the LR model: mean relative humidity 20 days after transplanting (DAT), maximum air temperature 20 DAT, and maximum soil temperature 10 DAT (log 10 transformed). In the DM mode, this GDD method and the LR model also demonstrated high predictive accuracy as quantified using mean square error. Using this model, we propose to schedule test harvests at GDD = 2600. The harvest date can further be optimized by predicting US#1 yield using GDD in combination with climate-based predictor variables measured within 20 DAT.

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A Bayesian belief network (BBN) model, which we named BxINROW/NET, was developed to represent the relationships among in-row spacing regimes, some agroclimatic variables known to influence storage root initiation, growing degree-days (GDDs) to harvest, and yield grades in ‘Beauregard’ sweetpotato grown in Louisiana. The model was developed from experimental data collected in a subset of years between 1990 and 2010 and assumed that soil moisture, weeds, and chemical injury were not limiting variables during the growing season. The BBN model error rates for storage root yields were 21%, 20%, and 13% for U.S. #1 (US1), canner, and jumbo grades, respectively, as estimated from repeated random partitioning of the modeling data set into training and testing partitions. In comparison, the error rates for a baseline logistic regression model were 56%, 54%, and 53% for US1, canner, and jumbo grades, respectively. The BBN model showed that GDDs to harvest (GDDH) as well as air and soil temperatures during the critical storage root initiation period [20 days after transplanting (DAT)] interacted with in-row spacing regimes to help determine the yield outcomes. Under a uniform irrigation management and minimum to intermediate GDDH (980 to 1495 GDDs), narrow (20 to 22 cm) to intermediate in-row spacing regimes (30 cm) were associated with higher probabilities (56% to 71% of cases) for attaining a high US1 yield (22 to 45 t·ha−1). These outcomes were associated with minimum to intermediate soil and air heat units 20 DAT, representing early to intermediate planting dates. Under similar conditions, wide in-row spacing treatments (38 to 40 cm) were associated with increased probabilities (100% of cases) for achieving a high yield of jumbo or oversized roots if GDDH (1495 to 1710 GDDs) was maximized. BxINROW/NET was also used as the foundation model to construct Bayesian decision networks (BDNs) for fresh market and processing scenarios. The BDNs were constructed by adding a value or gain node associated with each yield grade. Nodes representing price per box and stand deficiency were also added. These nodes allowed the prediction of estimated net return associated with a specific in-row regime given some agroclimatic variables and GDDH. As a result of its reliance on conditions observed in the study, BxINROW/NET is only applicable to a local Louisiana growing area. Further study is necessary to determine the model's applicability in other regions and growing conditions.

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Africa represents a unique secondary site of genetic diversity for the sweetpotato [Ipomoea batatas (L.) Lam.]. Despite the genetic resources available for sweetpotato breeding and cultivar selection, regional conflicts and adverse weather in the last two decades have accelerated the risk of germplasm loss, particularly in East and Central Africa. A cooperative research project is currently underway to assess genetic diversity as well as help conserve sweetpotato germplasm in East Africa. One of the tools that are currently being used is a web-accessible GIS database that enables access to spatial and temporal data by project investigators and other stakeholders. Although proprietary methods are available for delivering GIS data through web interfaces, these methods often require expensive licensing agreements. The use of ALOV Map, a freely available Java® application for publishing vector and raster maps, along with basemaps and other thematic maps downloaded from publicly accessible web sites, helped provide the framework for a web-accessible GIS database. DIVA-GIS, a free desktop based GIS software was used to generate shapefiles as well as preview files prior to uploading. This demonstrates that the availability of publicly available software requiring minimal or flexible licensing costs provide a cost-effective alternative to institutions that are considering access to GIS databases via a web-accessible interface. We describe procedures, software, and other applications that we used to develop a publicly accessible web interface to a GIS database of sweetpotato germplasm collections in Kenya and Tanzania.

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