Beyond conservation agriculture.

ABSTRACT: Global support for Conservation Agriculture (CA) as a pathway to Sustainable Intensification is strong. CA revolves around three principles: no-till (or minimal soil disturbance), soil cover, and crop rotation. The benefits arising from the ease of crop management, energy/cost/time savings, and soil and water conservation led to widespread adoption of CA, particularly on large farms in the Americas and Australia, where farmers harness the tools of modern science: highly-sophisticated machines, potent agrochemicals, and biotechnology. Over the past 10 years CA has been promoted among smallholder farmers in the (sub-) tropics, often with disappointing results. Growing evidence challenges the claims that CA increases crop yields and builds-up soil carbon although increased stability of crop yields in dry climates is evident. Our analyses suggest pragmatic adoption on larger mechanized farms, and limited uptake of CA by smallholder farmers in developing countries. We propose a rigorous, context-sensitive approach based on Systems Agronomy to analyze and explore sustainable intensification options, including the potential of CA. There is an urgent need to move beyond dogma and prescriptive approaches to provide soil and crop management options for farmers to enable the Sustainable Intensification of agriculture.

Productivity and chemical composition of food-type soybeans sown on different dates.

ABSTRACT. The objective of this study was to investigate the effect of different sowing dates on the yield, 100-grain weight, oil, protein and isoflavone contents of food-type soybean breeding lines UEL 110, UEL 115 and UEL 123 and a cultivar BRS 257. The materials were seeded on four sowing dates, and the experiment was conducted in a randomized block design with four replications. The productivity and 100- grain weight varied with the sowing dates and soybean genotypes. The protein content ranged from 36.40 to 42.44%, and the oil content ranged from 18.29 to 22.71%. No significant interaction was found between the genotype and sowing dates for the protein content. The isoflavone content also varied with the sowing dates and soybean genotypes. The cultivar BRS 257 had the highest isoflavone content, including the β- glucoside, malonyl glucoside and aglycones forms. The different sowing dates influenced the productivity, 100-grain weight, oil and protein content and isoflavone levels. Higher temperatures and lower rainfall during the grain filling decreased the productivity and isoflavone content and increased the protein content. For all sowing dates, the BRS 257 soybean food-type cultivar showed the highest isoflavone content, indicating that the effect of genotype is more important. Keywords: soybean, oil, protein, isoflavones. RESUMO. O objetivo deste trabalho foi investigar o efeito das diferentes épocas de semeadura na produtividade, massa de 100 grãos, teor de proteínas, óleo e isoflavonas de linhagens de soja tipo alimento UEL 110, UEL 115 e UEL 123 e cultivar BRS 257. O material foi semeado em quatro épocas de semeadura e o experimento foi conduzido em blocos casualizados com quatro repetições. A produtividade e a massa de 100 grãos variaram com a época de semeadura e com os diferentes genótipos. O teor de proteínas variou de 36,40 a 42,44% e o de óleo de 18,29 a 22,71%. Não foi encontrada interação entre genótipo e épocas de semeadura para o teor de proteínas. O teor de isoflavonas variou com as épocas de semeadura e com os genótipos. A cultivar BRS 257 apresentou maior teor de β-glicosídeos, malonil-glicosídeos e agliconas. As diferentes épocas de semeadura influenciam a produtividade, massa de 100 grãos, conteúdo de óleo, proteínas e isoflavonas. Altas temperaturas e baixas precipitações durante o enchimento dos grãos reduzem a produtividade e teor de isoflavonas e aumentam o teor de proteínas. A cultivar BRS 257 apresenta o maior teor de isoflavonas indicando que o efeito genético é mais importante.

Effects of row spacing and nitrogen topdressing fertilization on the yield of upland rice in a no-tillage system.

This study aimed to evaluate the effect of row spacing and nitrogen topdressing fertilization of two materials (genotype 07SEQCL441 CL and cultivar BRS Esmeralda) on the plant height, yield components, grain yield, and quality of an upland rice crop grown in a no-tillage system. Trials were conducted for two growing seasons under field conditions in a 3 x 4 factorial, randomized, complete block design, with four replications. For each material, treatments consisted of the combination of row spacing (0.225, 0.35, and 0.45 m) with nitrogen (N) applied as topdressing (0, 50, 100, and 150 kg ha-1). The lowest row spacing (0.225 m) for genotypes 07SEQCL441 CL and BRS Esmeralda provided a higher number of tillers, number of panicles m-2, and grain yield of rice. Increasing rates of N in the topdressing improved the rice grain yield for both cultivars, but for 07SEQCL441 CL, the grain yield was positively affected only to applications up to 50 kg N ha-1. Row spacing and N rates did not affect the rice grain quality. Therefore, these results indicate that the narrowest row spacing used (0.225 m) with N fertilization as topdressing increased the rice grain yield most in the no-tillage system.

Viability assessment of Genipa americana L. (Rubiaceae) embryonic axes after cryopreservation using In Vitro culture.

2016

Genetic parameters for carcass traits and body weight using a Bayesian approach in the Canchim cattle.

Correlation between genetic parameters and factors such as backfat thickness (BFT), rib eye area (REA), and body weight (BW) were estimated for Canchim beef cattle raised in natural pastures of Brazil. Data from 1648 animals were analyzed using multi-trait (BFT, REA, and BW) animal models by the Bayesian approach. This model included the effects of contemporary group, age, and individual heterozygosity as covariates. In addition, direct additive genetic and random residual effects were also analyzed. Heritability estimated for BFT (0.16), REA (0.50), and BW (0.44) indicated their potential for genetic improvements and response to selection processes. Furthermore, genetic correlations between BW and the remaining traits were high (P > 0.50), suggesting that selection for BW could improve REA and BFT. On the other hand, genetic correlation between BFT and REA was low (P = 0.39 ± 0.17), and included considerable variations, suggesting that these traits can be jointly included as selection criteria without influencing each other. We found that REA and BFT responded to the selection processes, as measured by ultrasound. Therefore, selection for yearling weight results in changes in REA and BFT.

Biochemical characterization of systemic bacteria in bananas, sensitivity to antibiotics and plant phytotoxicity during shoot proliferation.

2016

MAGGnet: an international network to foster mitigation of agricultural greenhouse gases.

Research networks provide a framework for review, synthesis and systematic testing of theories by multiple scientists across international borders critical for addressing global-scale issues. In 2012, a GHG research network referred to as MAGGnet (Managing Agricultural Greenhouse Gases Network) was established within the Croplands Research Group of the Global Research Alliance on Agricultural Greenhouse Gases (GRA). With involvement from 46 alliance member countries, MAGGnet seeks to provide a platform for the inventory and analysis of agricultural GHG mitigation research throughout the world. To date, metadata from 315 experimental studies in 20 countries have been compiled using a standardized spreadsheet. Most studies were completed (74%) and conducted within a 1-3-year duration (68%). Soil carbon and nitrous oxide emissions were measured in over 80% of the studies. Among plant variables, grain yield was assessed across studies most frequently (56%), followed by stover (35%) and root (9%) biomass. MAGGnet has contributed to modeling efforts and has spurred other research groups in the GRA to collect experimental site metadata using an adapted spreadsheet. With continued growth and investment, MAGGnet will leverage limited-resource investments by any one country to produce an inclusive, globally shared meta-database focused on the science of GHG mitigation.