Assessing moth migration and population structuring in Helicoverpa annigera (Lepidoptera : Noctuidae) at the regional scale: Example from the Darling Downs, Australia

Analysis of gene flow and migration of Helicoverpa armigera (Hubner) in a major cropping region of Australia identified substantial genetic structuring, migration events, and significant population genotype changes over the 38-mo sample period from November 1999 to January 2003. Five highly variable microsatellite markers were used to analyze 916 individuals from 77 collections across 10 localities in the Darling Downs. The molecular data indicate that in some years (e.g., April 2002-March 2003), low levels of H. armigera migration and high differentiation between populations occurred, whereas in other years (e.g., April 2001-March 2002), there were higher levels of adult moth movement resulting in little local structuring of populations. Analysis of populations in other Australian cropping regions provided insight into the quantity and direction of immigration of H. armigera adults into the Darling Downs growing region of Australia. These data provide evidence adult moth movement differs from season to season, highlighting the importance of studies in groups such as the Lepidoptera extending over consecutive years, because short-term sampling may be misleading when population dynamics and migration change so significantly. This research demonstrates the importance of maintaining a coordinated insecticide resistance management strategy, because in some years H. armigera populations may be independent within a region and thus significantly influenced by local management practices; however, periods with high migration will occur and resistance may rapidly spread.

Short root mutant of Lotus japonicus with a dramatically altered symbiotic phenotype

Legume plants carefully control the extent of nodulation in response to rhizobial infection. To examine the mechanism underlying this process we conducted a detailed analysis of the Lotus japonicus hypernodulating mutants, har1-1, 2 and 3 that define a new locus, HYPERNODULATION ABERRANT ROOT FORMATION (Har1), involved in root and symbiotic development. Mutations in the Har1 locus alter root architecture by inhibiting root elongation, diminishing root diameter and stimulating lateral root initiation. At the cellular level these developmental alterations are associated with changes in the position and duration of root cell growth and result in a premature differentiation of har1-1 mutant root. No significant differences between har1-1 mutant and wild-type plants were detected with respect to root growth responses to 1-aminocyclopropane1-carboxylic acid, the immediate precursor of ethylene, and auxin; however, cytokinin in the presence of AVG (aminoetoxyvinylglycine) was found to stimulate root elongation of the har1-1 mutant but not the wild-type. After inoculation with Mesorhizobium loti, the har1 mutant lines display an unusual hypernodulation (HNR) response, characterized by unrestricted nodulation (hypernodulation), and a concomitant drastic inhibition of root and shoot growth. These observations implicate a role for the Har1 locus in both symbiotic and non-symbiotic development of L. japonicus, and suggest that regulatory processes controlling nodule organogenesis and nodule number are integrated in an overall mechanism governing root growth and development.

Peanut farmers experience with FARMSCAPE in peninsular India

Researchers and extension officers collaborated with farmers in addressing peanut cropping and sowing decisions using on-farm experiments and cropping systems simulation in the Pollachi region of Tamil Nadu, India. The most influential variable affecting the peanut productivity in this irrigated region regard sowing date. During the 1998-1999 rabi (post rainy) season, three farmers fields in villages in Pollachi region were selected and monitored. The APSIM model was used to simulate the effect of sowing date. The APSIM-Peanut module simulation demonstrated close correspondence with the field observation in predicting yield. The model predicted that December sowing resulted in higher yield than January sowing due to longer pod filling period, and this was confirmed by farmer experience. The farmers and extension officers became comfortable with their role as owners of the collaborative experiments and custodians of the learning environment.