Patterns of participation in farmers’ research groups: Lessons from the highlands of southwestern Uganda

There is increasing interest in farmers’ organizations as an effective approach to farmer participatory research (FPR). Using data from an empirical study of farmers’ research groups (FRGs) in Uganda, this paper examines the patterns of participation in groups and answers questions such as: Who participates? What types of participation? How does participation occur? What are the factors determining participation? Results show that there is no single type of participation, but rather that FPR is a dynamic process with types of participation varying at different stages of the process. Farmers’ participation does not follow the normal adoption curve. Rather, it is characterized by high participation at the initial stages, followed by dramatic decrease and dropping-out, and slow increases toward the end. There is usually significantly higher participation among male farmers at the beginning of the process. However, as FRGs evolve, the proportion of men decreases sharply while the relative proportion of women continues to increase until it dominates the group. The findings do not support the common assumption that groups usually exclude women and the poor. On the contrary, we argue that FRGs are an effective mechanism to provide women and the poor with opportunities to participate in research. However, to be effective, this requires moving beyond head counting to promote more proactive gender and equity perspectives for amplifying the benefits of agricultural research to those who tend to be marginalized or excluded by mainstream development initiatives. This will be critical for making agricultural research more client-oriented and demand-driven.     

Independently evolved virulence effectors converge onto hubs in a plant immune system network

Plants generate effective responses to infection by recognizing both conserved and variable pathogen-encoded molecules. Pathogens deploy virulence effector proteins into host cells, where they interact physically with host proteins to modulate defense. We generated an interaction network of plant-pathogen effectors from two pathogens spanning the eukaryote-eubacteria divergence, three classes of Arabidopsis immune system proteins, and ~8000 other Arabidopsis proteins. We noted convergence of effectors onto highly interconnected host proteins and indirect, rather than direct, connections between effectors and plant immune receptors. We demonstrated plant immune system functions for 15 of 17 tested host proteins that interact with effectors from both pathogens. Thus, pathogens from different kingdoms deploy independently evolved virulence proteins that interact with a limited set of highly connected cellular hubs to facilitate their diverse life-cycle strategies.     

Extrapolating regional soil landscapes from an existing soil map: Sampling intensity,validation procedures,and integration of spatial context

This paper aims to investigate the potential of using soil-landscape pattern extracted from a soil map to predict soil distribution at unvisited location. Recent machine learning advances used in previous studies showed that the knowledge embedded within soil units delineated by experts can be retrieved and explicitly formulated from environmental data layers However, the extent to which the models can yield valid prediction has been little studied. Our approach is based on a classification tree analysis which has underwent a recent statistics advance, namely, stochastic gradient boosting. We used an existing soil-landscape map to test our methodology. Explanatory variables included classical terrain factors (elevation, slope, curvature plan and profile, wetness index, etc.), various channels and combinations of channels from LANDSAT ETM imagery, land cover and lithology maps. Overall classification accuracy indexes were calculated under two validation schemes, either taken within the training area or from a separated validation area. We focused our study on the accuracy assessment and testing of two modelling parameters: sampling intensity and spatial context integration. First, we observed strong differences in accuracy between the training area and the extrapolated area. Second, sampling intensity, in proportion to the class extent, did not largely influence the classification accuracy. Spatial context integration by the use of a mean filtering algorithm on explanatory variables increased the Kappa index on the extrapolated area by more than ten points. The best accuracy measurements were obtained for a combination of the raw explanatory dataset with the filtered dataset representing regional trend. However, the predictive capacity of models remained quite low when extrapolated to an independent validation area. Nevertheless, this study offers encouragement for the success of extrapolating soil patterns from existing soil maps to fill the gaps in present soil map coverage and to increase efficiency of ongoing soil survey.     

Susceptibility of phaseolin to in vitro proteolysis is highly variable across common bean varieties (Phaseolus vulgaris)

A study was conducted to investigate the amino acid (AA) composition and the susceptibility to in vitro proteolysis (pepsin, 120 min and pancreatin, 240 min) of a collection of purified phaseolins ( n = 43) in unheated or heat-treated form. The AA composition of phaseolin varied little across bean varieties. At 360 min of in vitro proteolysis, the degree of hydrolysis varied from 11 to 27% for unheated and from 57 to 96% for heated phaseolins ( P < 0.001). Heat treatment markedly increased the susceptibility of phaseolin to proteolysis ( P < 0.001). The AA scores (AAS) and the protein digestibility corrected for AAS indicated S-containing AA as the limiting AA (39 +/- 3 and 30 +/- 5%, respectively). In conclusion, susceptibility to proteolysis of heat-treated phaseolin rather than its AA composition affects the nutritional value of phaseolin estimated in vitro. Therefore, it should be the criterion of choice in breeding programs aimed at improving the nutritional value of common beans for humans.     

Aggregation of a proline-rich protein induced by epigallocatechin gallate and condensed tannins: effect of protein glycosylation

Astringency is one of the most important organoleptic qualities of numerous beverages, including red wines. It is generally thought to originate from interactions between tannins and salivary proline-rich proteins (PRPs). In this work interactions between a glycosylated PRP, called II-1, and flavan-3-ols were studied in aqueous solutions and at a colloidal level, by dynamic light scattering (DLS) and small-angle X-ray scattering (SAXS). The flavan-3-ols were a monomer, epigallocatechin gallate (EGCG), and polymerized flavan-3-ol fractions extracted from grape seeds. In aqueous solutions containing EGCG and protein II-1, protein aggregation took place when protein concentration and the EGCG/protein ratio exceeded a threshold. The aggregates had a small size, comparable with the dimensions of protein monomers, and formed stable dispersions (no phase separation). Most proteins remained free in solution. This behavior is in sharp contrast with the phase separation observed for nonglycoslated PRP in the same conditions. Moreover, this slight aggregation of II-I in the presence of EGCG was disrupted by the addition of 12% ethanol. Increasing the flavan-3-ol molecular weight strongly enhanced II-I/tannin aggregation: the threshold was at a lower protein concentration (0.2 mg/mL) and a lower tannin/protein ratio. Still, in most cases, and in contrast with that observed with a nonglycosylated PRP, the aggregates remained of discrete size and stable. Only at low ethanol content (2%) did the addition of tannin polymers finally lead to phase separation, which occurred when the molar ratio of tannins to proteins exceeded 12. This systematic effect of ethanol confirmed the strong effect of cosolvents on protein/tannin interactions.     

Influence of DCD and DMPP on soil N dynamics after incorporation of vegetable crop residues

We have investigated the effect of two nitrification inhibitors, 3,4-dimethylpyrazole phosphate (DMPP) and dicyandiamide (DCD), on the accumulation of and after incorporation of cauliflower residues in incubation experiments. Cauliflower leaves were incubated with soil and DCD or DMPP at two application rates [8.93 and 17.9 mg active component (ac) kg⁻¹ for DCD; 0.89 and 1.79 mg ac kg⁻¹ for DMPP]. Both doses of DCD and DMPP increased on average by 18.9 and 26.0 mg N kg⁻¹ for DCD1 (during 30 days) and DCD2 (during 45 days), respectively, and on average by 14.4 mg N kg⁻¹ for DMPP1 and DMPP2 during a period of at least 95 days. In DCD-treated soils, data followed an S-shaped curve, indicating that nitrification restarted during the experiment: inhibition was on average 24% during 35 days for DCD1 and on average 45% during 49 days for DCD2. Thereafter, amount in DCD-treated soils exceeded that of the cauliflower-only treatment by 31% for DCD1 and 78% for DCD2, probably due to a nitrogen release from DCD itself and a priming effect induced by DCD. In DMPP-treated soils, data followed a linear pattern since nitrification was inhibited during the complete incubation (95 days): inhibition was on average 56 and 64% for DMPP1 and DMPP2, respectively. DMPP did not affect the N mineralization of the crop residues. Under favourable conditions, DCD is able to inhibit the nitrification from crop residues for 50 days and DMPP for at least 95 days. Hence, especially DMPP shows a potential to reduce leaching after incorporation of crop residues.     

Probing the solvent-assisted nucleation pathway in chemical self-assembly

Hierarchical self-assembly offers a powerful strategy for producing molecular nanostructures. Although widely used, the mechanistic details of self-assembly processes are poorly understood. We spectroscopically monitored a nucleation process in the self-assembly of p-conjugated molecules into helical supramolecular fibrillar structures. The data support a nucleation-growth pathway that gives rise to a remarkably high degree of cooperativity. Furthermore, we characterize a helical transition in the nucleating species before growth. The self-assembly process depends strongly on solvent structure, suggesting that an organized shell of solvent molecules plays an explicit role in rigidifying the aggregates and guiding them toward further assembly into bundles and/or gels.     

Inhaled fluticasone reduces bronchial responsiveness and airway inflammation in cats with mild chronic bronchitis

This study investigated the effect of inhaled fluticasone on lower airway inflammation and bronchial responsiveness (BR) to inhaled carbachol in cats with very mild, chronic bronchitis (n = 5) that were compared with healthy cats serving as controls (n = 6). Chest radiographs, BR tests performed non-invasively by barometric whole body plethysmography (BWBP) and bronchoalveolar lavage (BAL) were performed before and after treatment. BR was quantified by calculating the concentration of carbachol inducing bronchoconstriction (C-Penh300%), defined as a 300% increase of baseline Penh, an index of bronchoconstriction obtained by BWBP. BAL fluid was analyzed cytologically and the oxidant marker 8-iso-PGF2alpha was determined. At test 1, healthy cats and cats with bronchitis were untreated, whereas for test 2 inhalant fluticasone (250 microg once daily) was administrated for 2 consecutive weeks to cats with bronchitis. Control cats remained untreated. Inhaled fluticasone induced a significant increase in C-Penh300% and a significant decrease of BAL fluid total cells, macrophages, neutrophils and 8-iso-PGF2alpha in cats with bronchitis, whilst untreated control cats did not show significant changes over time. This study shows that a 2-week fluticasone treatment significantly reduced lower airway inflammation in very mild bronchitis. BR could be successfully monitored in cats using BWPB and decreased significantly in response to inhaled fluticasone. 8-Iso-PGF2alpha in BAL fluid was responsive to treatment and appeared as a sensitive biomarker of lower airway inflammation in cats.     

高浓度CO2处理后土壤N2O排放特征

土壤被认为是大气氧化亚氮(N2O)的重要生物排放源.随着大气CO2浓度升高,土壤N2O排放规律可能发生改变.无锡FACE(Free-air CO2 Enrichment)基地至2003年已运行2年,分别采集Ambient(背景大气CO2浓度处理)和FACE(背景大气CO2浓度 200 mmol·mol-1处理)农田土壤,调节含水量至40%WFPS,在25℃室内有氧预培养7 d后,按250 μgN·-1添加NH4NO3,将含水量调节至80%WFPS,在25℃进行有氧培养7 d.在此培养期间,定期测定施肥后土壤N2O和CO2排放速率,探讨来自田间Ambient和FACE土壤N,2O排放差异及其可能的影响因素.结果表明,所有土壤N2O和CO,2排放速率均随培养时间延长而迅速递减,来自Ambient处理的土壤N,2O和CO,2排放速率均高于来自FACE处理的土壤相应排放量,且土壤N,2O与CO,2排放速率存在显著正相关.通过比较培养前后土壤交换态NH,4 和NO,3-含量的变化,显示培养过程中可能存在相当量的微生物氮固持,有必要加强相关研究.