Participatory agro-climate information services: A key component in climate resilient agriculture

The brief promotes participatory agro-climate information services as a key component in achieving climate-smart agriculture. The brief emphasizes that actionable agro-climate information starts with—and responds to—gender-based needs of farmers, integrated at all stages of the value chain. Timely forecasts and accurate agroclimate advisories have been proven to provide farmers with production, adaptation, and mitigation benefits

An efficient finite element formulation of dynamics for a flexible robot with different type of joints

If two adjacent links of a flexible robot are connected via a revolute joint or a fixed prismatic joint, the relative motion of the next link will depend on both the joint motion and the elastic displacement of the distal end of the previous link. However, if the two adjacent links are connected via a sliding prismatic joint, the relative motion of the next link will depend additionally on the elastic deformation distributed along the previous link. Therefore, formulation of the motion equations for a multi-link flexible robot consisting of the revolute joints, the fixed prismatic joints and the sliding prismatic joints is challenging. In this study, the finite element kinematic and dynamic formulation was successfully developed and validated for the flexible robot, in which a transformation matrix is proposed to describe the kinematics of both the joint motion and the link deformation. Additionally, a new recursive formulation of the dynamic equations is introduced. As compared with the previous methods, the time complexity of the formulation is reduced by O(2η), where η is the number of finite elements on all links. The numerical examples and experiments were implemented to validate the proposed kinematic and dynamic modelling method

Inverse kinematic control algorithm for a welding robot - positioner system to trace a 3D complex curve

The welding robots equipped with rotary positioners have been widely used in several manufacturing industries. However, for welding a 3D complex weld seam, a great deal of points should be created to ensure the weld path smooth. This is a boring job and is a great challenge - rotary positioner system since the robot and the positioner must move simultaneously at the same time. Therefore, in this article, a new inverse kinematics solution is proposed to generate the movement codes for a six DOFs welding robot incorporated with a rotary positioner. In the algorithm, the kinematic error is minimized, and the actual welding error is controlled so that it is always less than an allowable limit. It has shown that the proposed algorithm is useful in developing an offline CAD-based programming tool for robots when welding complex 3D paths. The use of the algorithm increases the accuracy of the end-effector positioning and orientation, and reduces the time for teaching a welding robot - positioner system. Simulation scenarios demonstrate the potency of the suggested method

Women’s involvement in coffee agroforestry value-chains: Financial training, Village Savings and Loans Associations, and Decision power in Northwest Vietnam

Globally, in the coffee sector and smallholder agriculture in developing countries, there is a distinct gender gap in key factors that enable women’s active participation in and contribution to the coffee value chain and in farm and domestic decisions, such as decisions over credit, agricultural inputs, and training opportunities and division of labor and time. This study assesses Village Savings and Loans Associations (VSLA) impacts and related training on gender equality and women’s access to coffee markets in an ongoing coffee- project in northwest Vietnam. All 169 women in this survey received gender equality and finance training, with one group being members of a VSLA and taking out small loans. With Women’s Empowerment in Agriculture Index (WEAI), women rated their perception of their decision-making power over a range of 18 tasks related to household and agricultural responsibilities and use of income and social activities over 18 months. There were significant improvements in decision-making power in categories with previously low participation and increased sharing of domestic responsibilities. The categories with the biggest gains were decision-making over large purchases and use of income, especially for VSLA-members who sought out market information before engaging with potential coffee buyers and enhanced their negotiating abilities to arrange more favorable outcomes successfully. These results indicate that active gender and finance training translated to real changes in gender dynamics, and membership of a VSLA also helped women improve their financial literacy and improve their negotiating abilities. Husbands to women in the study also began to reconsider gender roles and shift towards equal sharing of responsibility and decision- making with their wives. Based on this study, we recommend (1) implementing gender and finance training and enabling access to loans for women as a means for their inclusion in agriculture value chains, and (2) engaging the whole household in gender training in order for all family members to be receptive to adjustments in the gender division of responsibility, labor and decision-making. The results indicate the conditions under which women can benefit from activities involving agroforestry systems that also enhance carbon sequestration for climate change mitigation compared to coffee monoculture

Effects of salinity and alkalinity on growth and survival of all-male giant freshwater prawn (Macrobrachium rosenbergii De Man, 1879) juveniles

All-male giant freshwater prawns (AMGFPs) have been a popular crop cultivated in the Mekong Delta, Vietnam, due to their proven production efficiency compared to all-female or mixed-sex prawn cultures. However, the crucial water quality factors impacting AMGFP aquaculture efficiency have yet to be elaborately investigated. Two separate experiments were randomly arranged with three replicates to evaluate the effects of salinity or alkalinity on the growth and survival of AMGFP juveniles during the grow-out period. The results show that the prawn survival rate in the salinity range of 0–15‰ varied from 66.1 to 74.8％ and in a salinity range of 0–5‰ was relatively low compared to the range of 10-15‰; however, the difference was not significant among salinities after 90 days of culture (p > 0.05). All the prawn growth performance parameters significantly decreased with increasing salinities of 0, 5, 10, and 15‰ after 30, 60, and 90 days of culture (p 0.05), and both were significantly higher than those at salinities of 10 and 15‰ (p < 0.05) after 90 days of culture. In addition, the survival rate reached 82.5–84.4％ and did not significantly differ among alkalinities of 80, 100, 120, 140, and 160 mgCaCO3 L−1. However, the growth performance parameters and yield of AMGFPs at an alkalinity of 160 mg L−1 were significantly higher than those at lower alkalinities (80, 100, 120, and 140 mg CaCO3 L−1) after 90 days of culture. Therefore, it is recommended that a salinity range of 0–5‰ and alkalinity of 160 mgCaCO3 L−1 is optimal for the growth-out culture of AMGFP juveniles

The Power of CRISPR-Cas9-Induced Genome Editing to Speed Up Plant Breeding

Genome editing with engineered nucleases enabling site-directed sequence modifications bears a great potential for advanced plant breeding and crop protection. Remarkably, the RNA-guided endonuclease technology (RGEN) based on the clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated protein 9 (Cas9) is an extremely powerful and easy tool that revolutionizes both basic research and plant breeding. Here, we review the major technical advances and recent applications of the CRISPR-Cas9 system for manipulation of model and crop plant genomes. We also discuss the future prospects of this technology in molecular plant breeding

A review on application of artificial neural network (ANN) for performance and emission characteristics of diesel engine fueled with biodiesel-based fuels

Biodiesel has been emerging as a potential and promising biofuel for the strategy of reducing toxic emissions and improving engine performance. Computational methods aiming to offer numerical solutions were inevitable as a study methodology which was sometimes considered the only practical method. Artificial neural networks (ANN) were data-processing systems, which were used to tackle many issues in engineering and science, especially in some fields where there was a failure of the conventional modeling approaches. Thus, it was believed that the best choice was the development of a novel approach like the ANN model to anticipate engine performance and exhaust emissions with high accuracy. In this review paper, the structure and applicability of the ANN model were comprehensively evaluated. More importantly, the use of ANN with trained, tested, and validated data was introduced to determine the performance and emission characteristics of a diesel engine fueled with biodiesel-based fuel. In general, the ANN model could supply a relatively high determination coefficient as compared between predicted results and experimental data, showing that the ANN model could have a good ability to predict the engine behaviors with an accuracy higher than 95%