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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 fromexperimental 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 themodel's applicability in other regions and growing conditions.

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.

Villordon A.,nter Sweet Potato Research Station | Clark C.,02 Life science Building | Firon N.,Israel Agricultural Research Organization
HortScience | Year: 2012

This study aimed to investigate the effect of 1-methylcyclopropene (1-MCP) on adventitious rooting in two sweetpotato cultivars. Experiments with 'Beauregard' and 'Evangeline' sweetpotato cuttings revealed differential adventitious root (AR) emergence responsesto1-MCP application. 'Beauregard'AR count and length decreased with 1-MCP application in two of four experiments. In contrast, 1-MCP did not influence 'Evangeline' root count. However, 'Evangeline' root length decreased in three of four experiments. Trypan blue staining of 'Beauregard' nodal tissue with delayed AR primordia emergence showed localized dead tissue in the general area where ARs emerge. The degree of staining appeared to correspond with the stage of AR emergence with the staining becoming more intense around the time an AR primordium eventually emerged through a crack in the epidermis. This response agrees with reported results of ethylene-mediated AR emergence in other plant species. These results also appear to suggest that 'Beauregard' and 'Evangeline' cuttings differ in ethylene sensitivity. This represents the first evidence of genotype-specific ethylene involvement in adventitious rooting of sweetpotato cuttings.

Villordon A.,nter Sweet Potato Research Station | Firon N.,Israel Agricultural Research Organization | Carey E.,International Potato Center
HortScience | Year: 2013

This study characterized the influence of nitrogen (N) rates and variation in local availability on root architecture as measured by lateral root (LR) development attributes during the onset of the storage root (SR) initiation stage in 'Beauregard' sweetpotato adventitious roots (ARs). In N rate experiments, plants grown without fertilizer N showed significantly lower values for all measured LR attributes compared with fertilized plants. Total first- (1LR) and second-order LR (2LR) length increased by 78% and 2873%, respectively, as N was increased from 0 to 50 kg·ha-1. Total 1LR and 2LR number increased by 32% and 1465%, respectively. Increasing the N rates to 100 and 200 kg·ha-1 did not result in further increases for all LR attributes measured. There were no differences in AR number between untreated controls and plants fertilized with 50 kg N/ha. However, the number of ARs increased by 65% when fertilizer N was increased from 50 to 100 kg·ha-1. Increasing the rate to 200 kg·ha-1 did not result in further increases in AR number. In split-root experiments, roots grown in the compartment with 50 kg N/ha had 135% and 2916% increase in total 1LR and 2LR length, respectively, compared with roots grown in the compartment without fertilizer N. Total 1LR and 2LR number increased by 110% and 2114%, respectively. There were 111% more ARs in the fertilized compartment relative to the unfertilized compartment. There were no differences in LR attributes and AR number between compartments that received similar fertilizer N rates. In fertilizer placement experiments, there were no differences in LR attributes between pre-mixing fertilizer N and placement of fertilizer ~4 cm below the surface of the growth substrate. There were also no differences between the unfertilized control and placement of fertilizer ~4 cm from the bottom of the pot. Plants grown in substrate with pre-mixed N showed 38% and 342% increase in 1LR and 2LR length, respectively, relative to the bottom placement of N. Total number of 1LR and 2LR in the growth substrate with pre-mixed N increased by 30% and 312%, respectively, relative to the bottom placement of N. These results represent the first evidence for the association between sweetpotato root architectural attributes and variation in N rate and localized availability. These results are also consistent with findings in model systems in which local N presence is necessary for LR development. This information can be used to further optimize SR yield by helping to ensure the availability of N at the optimum rate across time and space.

Firon N.,Israel Agricultural Research Organization | Villordon A.,nter Sweet Potato Research Station | Kfir Y.,Israel Agricultural Research Organization | Lapis E.,Israel Agricultural Research Organization | And 5 more authors.
BMC Genomics | Year: 2013

Background: The number of fibrous roots that develop into storage roots determines sweetpotato yield. The aim of the present study was to identify the molecular mechanisms involved in the initiation of storage root formation, by performing a detailed transcriptomic analysis of initiating storage roots using next-generation sequencing platforms. A two-step approach was undertaken: (1) generating a database for the sweetpotato root transcriptome using 454-Roche sequencing of a cDNA library created from pooled samples of two root types: fibrous and initiating storage roots; (2) comparing the expression profiles of initiating storage roots and fibrous roots, using the Illumina Genome Analyzer to sequence cDNA libraries of the two root types and map the data onto the root transcriptome database.Results: Use of the 454-Roche platform generated a total of 524,607 reads, 85.6% of which were clustered into 55,296 contigs that matched 40,278 known genes. The reads, generated by the Illumina Genome Analyzer, were found to map to 31,284 contigs out of the 55,296 contigs serving as the database. A total of 8,353 contigs were found to exhibit differential expression between the two root types (at least 2.5-fold change). The Illumina-based differential expression results were validated for nine putative genes using quantitative real-time PCR. The differential expression profiles indicated down-regulation of classical root functions, such as transport, as well as down-regulation of lignin biosynthesis in initiating storage roots, and up-regulation of carbohydrate metabolism and starch biosynthesis. In addition, data indicated delicate control of regulators of meristematic tissue identity and maintenance, associated with the initiation of storage root formation.Conclusions: This study adds a valuable resource of sweetpotato root transcript sequences to available data, facilitating the identification of genes of interest. This resource enabled us to identify genes that are involved in the earliest stage of storage root formation, highlighting the reduction in carbon flow toward phenylpropanoid biosynthesis and its delivery into carbohydrate metabolism and starch biosynthesis, as major events involved in storage root initiation. The novel transcripts related to storage root initiation identified in this study provide a starting point for further investigation into the molecular mechanisms underlying this process. © 2013 Firon et al.; licensee BioMed Central Ltd.

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