<Emphasis Type="Italic">Pinus halepensis</Emphasis> somatic embryogenesis is affected by the physical and chemical conditions at the initial stages of the process

Pinus halepensis has been described as a drought-tolerant species with high plasticity to growth in different environments. Its eco-physiological characteristics could facilitate the use of this species in large afforestations in the future scenery of climate change. Somatic embryogenesis is a biotechnological tool with potential for large-scale clonal propagation. In order to establish an improved regeneration protocol for Pinus halepensis, the effects of different temperatures (18, 23, and 28 °C) and water availability conditions (2, 3, and 4 g L^?1 Gelrite^®), during initiation of embryonal masses on the rate of initiation, proliferation, maturation, and the number of embryos developed, were evaluated. It was found that environmental conditions during the initiation stage of Pinus halepensis somatic embryogenesis influence the success of initiation and proliferation. In contrast, there was no effect of these conditions on the maturation rates and the number of somatic embryos. Somatic embryos were obtained in all treatments tested, indicating that plants can be produced from extreme conditions of induction, such as high temperatures (28 °C) and low water availability conditions (4 g L^?1).     

A multi-method approach to delineate and validate migratory corridors

Context

Managers are faced with numerous methods for delineating wildlife movement corridors, and often must make decisions with limited data. Delineated corridors should be robust to different data and models.

Objectives

We present a multi-method approach for delineating and validating wildlife corridors using multiple data sources, which can be used conserve landscape connectivity. We used this approach to delineate and validate migration corridors for wildebeest (Connochaetes taurinus) in the Tarangire Ecosystem of northern Tanzania.

Methods

We used two types of locational data (distance sampling detections and GPS collar locations), and three modeling methods (negative binomial regression, logistic regression, and Maxent), to generate resource selection functions (RSFs) and define resistance surfaces. We compared two corridor detection algorithms (cost-distance and circuit theory), to delineate corridors. We validated corridors by comparing random and wildebeest locations that fell within corridors, and cross-validated by data type.

Results

Both data types produced similar RSFs. Wildebeest consistently selected migration habitat in flatter terrain farther from human settlements. Validation indicated three of the combinations of data type, modeling, and corridor detection algorithms (detection data with Maxent modeling, GPS collar data with logistic regression modeling, and GPS collar data with Maxent modeling, all using cost-distance) far outperformed the other seven. We merged the predictive corridors from these three data-method combinations to reveal habitat with highest probability of use.

Conclusions

The use of multiple methods ensures that planning is able to prioritize conservation of migration corridors based on all available information.

     

“WaterMan”: an on-farm water management game with heuristic capabilities

A modern computer-based simulation tool (WaterMan) in the form of a game for on-farm water management was developed for application in training events for farmers, students, and irrigators. The WaterMan game utilizes an interactive framework, thereby allowing the user to develop scenarios and test alternatives in a convenient, risk-free environment. It includes a comprehensive soil water and salt balance calculation algorithm. It also employs heuristic capabilities for modeling all of the important aspects of on-farm water management, and to provide quantitative performance evaluations and practical water management advice to the trainees. Random events (both favorable and unfavorable) and different strategic decisions are included in the game for more realism and to provide an appropriate level of challenge according to player performance. Thus, the ability to anticipate the player skill level, and to reply with random events appropriate to the anticipated level, is provided by the heuristic capabilities used in the software. These heuristic features were developed based on a combination of two artificial intelligence approaches: (1) a pattern recognition approach and (2) reinforcement learning based on a Markov decision processes approach, specifically the Q-learning method. These two approaches were combined in a new way to account for the difference in the effect of actions taken by the player and action taken by the system in the game world. The reward function for the Q-learning method was modified to reflect the suggested classification of the WaterMan game as what is referred to as a partially competitive and partially cooperative game.     

Promoting sustainable intensification in precision agriculture: review of decision support systems development and strategies

Precision agriculture provides important issues toward a more sustainable agriculture. Many farmers have the necessary technology to operate site-specifically, but they do not use it in practice, and thus available information and communications technology (ICT) systems are not used to their full potential. This paper addresses how to reduce the so-called “problem of implementation”, based on the knowledge that participatory approaches during the design and development process is one of the most important factors to frame technology adoption. The development of sustainable ICT systems through theories and methodologies from the fields of human computer interaction and user-centered design (UCD) is presented and an ongoing Swedish project for development of an agricultural decision support system (AgriDSS) for nitrogen fertilization is used as an example to frame the issue. The overreaching aim is to develop AgriDSSs that are sustainable in design as well as through design by stressing the importance of participatory approaches for the successful development of AgriDSSs. The Swedish project has the intention to apply a UCD approach, and some pitfalls on starting to use this way of working is identified as well as some suggestions on how to reduce them through co-learning processes. Despite the challenges presented in this paper, ICT can contribute significantly to long-term sustainable development. Thus, several competences and scientific disciplines need to act in concert to help develop a sustainable development of agriculture via a transdisciplinary approach that can make an impact on society at many levels.     

Inconspicuous restraint of rice seedling growth by root-infecting fungi in soil of a rice paddy field

 Rice seedling growth, estimated by plant height and root development and discoloration, was better in pasteurized soil than in unpasteurized soil obtained from a flooded rice field. Rice seedlings also grew better in sterilized soil modified by adding roots harvested from the pasteurized soil than in soil modified by adding roots harvested from the unpasteurized soil. The results demonstrate that seedling growth in the rice field soil was inhibited by soil microorganisms, even though no typical symptoms such as seedling blight or damping-off appeared. Pythium aristosporum is suggested to be involved in the inhibition. Thus, it appears that inconspicuous restraint of rice seedling growth could occur in soils of rice paddy fields. Received: May 20, 2002 / Accepted: October 16, 2002 Acknowledgments The authors thank Dr. T. Ichitani, former professor at Osaka Prefectural University, for providing an isolate of Pythium aristosporum for comparison, and Mr. Mitsuaki Sato of Akita Prefectural College of Agriculture for technical assistance.     

Soybean oil content QTL mapping and integrating with meta-analysis method for mining genes

Oil content of soybean was a valuable quantitative trait controlled by multiple genes. Eleven QTLs were detected by both CIM and MIM method with the population crossed between Charleston and Dong nong594 in recent 3 years (2007, 2008, 2009). Combining the QTLs collected over the past 20 years, an integrated map of oil-content major QTLs in soybean was established using soymap2, which was published in 2004, as a reference. Using the software BioMercator ver.2.1, QTLs were projected from their own maps onto the reference map. In total, ninety-eight QTLs were integrated into soymap2. A meta-analysis method was used to narrow down the confidence interval, and 20 consensus QTLs and their corresponding markers were obtained. Using a local version of GENSCAN, 10,137 sequences in the consensus QTL intervals were predicted. With BLAST, these predicted genes were compared to the International Protein Index database to mine the related genes. The results offer a basis for gene mining and molecular breeding in soybean.