Sowing density effect on common bean leaf area development

Sowing density is a major management factor that affects growth and development of grain crops by modifying the canopy light environment and interplant competition for water and nutrients. While the effects of sowing density and plant architecture on static vegetative and reproductive growth traits have been explored previously in the common bean, few studies have focused on the impacts of sowing density on the dynamics of node addition and leaf area development. We present the results from two sites of field experiments where the effects of sowing densities (5, 10, 15, 20, 25 and 35 plants m-2) and genotypes with contrasting plant architectures (two each from growth habits I through III) on the dynamics of node addition and leaf area were assessed. Analysis of the phyllochron (°C node-1) indicated genotype and density effects (but no interaction) on the rate of node addition. While significant, these differences amounted to less than two days of growth at either site. In terms of leaf area development, analysis using a power function reflected large differences in the dynamics and final size of individual plant leaf area between the lower density (20 plants m-2) at the growth habit, but not genotype level. These differences in node addition and leaf development dynamics translated to marked differences between growth habits and sowing densities in estimated leaf area indices, and consequently, in the estimated fraction of intercepted light at lower densities

Influence of plant density and growth habit of common bean on leaf area development and N accumulation

Crop yield requires leaf area to intercept solar radiation and to undertake photosynthesis, both of which depend on nitrogen (N) accumulation. Further, the amount of accumulated plant N at the beginning of seed fill serves as the reservoir for N required in synthesizing the proteins in developing seeds. For common bean (Phaseolus vulgaris L.), resolution of the basic characteristics limiting production is challenging because of variation in plant growth-habit and in wide-ranging plant spacing. Field experiments were undertaken at two low-latitude locations with three plant growth-habit types and six plant densities to measure canopy leaf area and leaf N accumulation at the beginning of seed fill. Plant spacing of 20 plants m−2 or more was sufficient to result in equal leaf area and N accumulation for all six plant genotypes at each location. However, the low-altitude, higher-temperature location had lower accumulated leaf N and yield than the high-altitude, cooler-temperature location. These results indicate attention needs to be given to physiological or agronomic approaches to overcome the negative impact of high temperature on N accumulation by common bean

Is nitrogen accumulation in grain legumes responsive to growth or ontogeny?

Peer Revie

Development of a QTL-environment-based predictive model for node addition rate in common bean

To select a plant genotype that will thrive in targeted environments it is critical to understand the genotype by environment interaction (GEI). In this study, multi-environment QTL analysis was used to characterize node addition rate (NAR, node day− 1) on the main stem of the common bean (Phaseolus vulgaris L). This analysis was carried out with field data of 171 recombinant inbred lines that were grown at five sites (Florida, Puerto Rico, 2 sites in Colombia, and North Dakota). Four QTLs (Nar1, Nar2, Nar3 and Nar4) were identified, one of which had significant QTL by environment interactions (QEI), that is, Nar2 with temperature. Temperature was identified as the main environmental factor affecting NAR while day length and solar radiation played a minor role. Integration of sites as covariates into a QTL mixed site-effect model, and further replacing the site component with explanatory environmental covariates (i.e., temperature, day length and solar radiation) yielded a model that explained 73% of the phenotypic variation for NAR with root mean square error of 16.25% of the mean. The QTL consistency and stability was examined through a tenfold cross validation with different sets of genotypes and these four QTLs were always detected with 50–90% probability. The final model was evaluated using leave-one-site-out method to assess the influence of site on node addition rate. These analyses provided a quantitative measure of the effects on NAR of common beans exerted by the genetic makeup, the environment and their interactions

Household agrobiodiversity management on Amazonian Dark Earths, Oxisols, and floodplain soils on the Lower Madeira River, Brazil

Smallholder farmers play a critical role in the maintenance of global agrobiodiversity. However, the social and environmental factors that shape agrobiodiversity and its management in rural smallholder communities are still debated among scholars. This study examines variation in the diversity of useful plant species (i.e.; species richness) managed by households located in three distinct environments along the Lower Madeira River in the Central Brazilian Amazon: Amazonian Dark Earths (ADE), upland Oxisols (OX), and floodplain soils (FP). Among the 106 households studied, those located on ADE managed a significantly higher number of useful species than those on floodplain soils but not than those on Oxisols. A generalized linear mixed effects model indicates that the age of the household head, number of household members and adults, and area of land under cultivation are statistically significant factors that influence species richness across all households. Ethnographic data are employed to contextualize these findings and discuss other influences on agrobiodiversity management in rural Amazonian communities, including regional historical ecology and the life histories of individual farmers. © 2015 Springer Science+Business Media New York

Determination of coefficient defining leaf area development in different genotypes, plant types and planting densities in peanut (Arachis hypogeae L.)

AbstractRapid leaf area development may be attractive under a number of cropping conditions to enhance the vigor of crop establishment and allow rapid canopy closure for maximizing light interception and shading of weed competitors. This study was undertaken to determine (1) if parameters describing leaf area development varied among ten peanut (Arachis hypogeae L.) genotypes grown in field and pot experiments, (2) if these parameters were affected by the planting density, and (3) if these parameters varied between Spanish and Virginia genotypes. Leaf area development was described by two steps: prediction of main stem number of nodes based on phyllochron development and plant leaf area dependent based on main stem node number. There was no genetic variation in the phyllochron measured in the field. However, the phyllochron was much longer for plants grown in pots as compared to the field-grown plants. These results indicated a negative aspect of growing peanut plants in the pots used in this experiment. In contrast to phyllochron, there was no difference in the relationship between plant leaf area and main stem node number between the pot and field experiments. However, there was genetic variation in both the pot and field experiments in the exponential coefficient (PLAPOW) of the power function used to describe leaf area development from node number. This genetic variation was confirmed in another experiment with a larger number of genotypes, although possible G×E interaction for the PLAPOW was found. Sowing density did not affect the power function relating leaf area to main stem node number. There was also no difference in the power function coefficient between Spanish and Virginia genotypes. SSM (Simple Simulation model) reliably predicted leaf canopy development in groundnut. Indeed the leaf area showed a close agreement between predicted and observed values up to 60000cm2m−2. The slightly higher prediction in India and slightly lower prediction in Niger reflected GxE interactions. Until more understanding is obtained on the possible GxE interaction effects on the canopy development, a generic PLAPOW value of 2.71, no correction for sowing density, and a phyllochron on 53°C could be used to model canopy development in peanut

A Predictive Model for Time-to-Flowering in the Common Bean Based on QTL and Environmental Variables

The common bean is a tropical facultative short day legume that is now grown in tropical and temperate zones. This observation underscores how domestication and modern breeding can change the adaptive phenology of a species. A key adaptive trait is the optimal timing of the transition from the vegetative to the reproductive stage. This trait is responsive to genetically controlled signal transduction pathways and local climatic cues. A comprehensive characterization of this trait can be started by assessing the quantitative contribution of the genetic and environmental factors, and their interactions. This study aimed to locate significant QTL (G) and environmental (E) factors controlling time-to-flower in the common bean, and to identify and measure G x E interactions. Phenotypic data were collected from a bi-parental [Andean x Mesoamerican] recombinant inbred population (F11:14, 188 genotypes) grown at five environmentally distinct sites. QTL analysis using a dense linkage map revealed 12 QTL, five of which showed significant interactions with the environment. Dissection of G x E interactions using a linear mixed-effect model revealed that temperature, solar radiation, and photoperiod play major roles in controlling common bean flowering time directly, and indirectly by modifying the effect of certain QTLs. The model predicts flowering time across five sites with an adjusted r-square of 0.89 and root-mean square error of 2.52 days. The model provides the means to disentangle the environmental dependencies of complex traits, and presents an opportunity to identify in-silico QTL allele combinations that could yield desired phenotypes under different climatic conditions