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Novel soil quality indicators for the evaluation of agricultural management practices: a biological perspective
No full textDevelopments in soil biology and methods to characterize soil organic carbon have the potential to deliver novel soil quality indicators that can help to identify soil management practices that sustain soil productivity and environmental resilience. This thesis aimed at investigating the suitability of a range of soil biological and biochemical parameters as novel soil quality indicators for agricultural management. The soil parameters, selected through a literature review, comprised different labile organic carbon fractions (hydrophilic dissolved organic carbon (Hy-DOC), dissolved organic carbon (DOC), permanganate oxidizable carbon (POXC), hot water extractable carbon (HWEC) and particulate organic matter carbon (POMC), ordered here from the smallest to the largest proportion of the total organic carbon), soil disease suppressiveness measured with a Pythium-Cress bioassay, nematode communities characterized with amplicon sequencing and qPCR, and microbial community level physiological profiling (CLPP) measured with MicroRespTM. We tested the sensitivity of the novel indicators to tillage and organic matter addition in 10 European long-term field experiments, and assessed their relationship with already existing soil quality indicators linked to soil functioning. Lastly, the results of these experimental chapters are interpreted relative to each other and to the broader body of literature on soil quality assessments. Moreover, pros and cons of the novel indicators are discussed, and possibilities and needs for future research are outlined. Reduced tillage increased carbon availability, disease suppressiveness, nematode richness and diversity, the stability and maturity of the food web, and microbial activity and functional diversity. Organic matter addition had a weaker role in sustaining soil quality, possibly due to the different compositions of the organic matter inputs in the long-term field experiments that were sampled. Random forest analysis showed that POXC was the indicator that discriminates soil management most, and structural equation modelling showed its central role in nutrient cycling, carbon sequestration, biodiversity conservation, erosion control and disease regulation/suppression. The novel indicators proposed here have great potential to improve existing soil quality assessment schemes, but their usefulness is still to be validated and optimized
Genomic Breeding Programs Realize Larger Benefits by Cooperation in the Presence of Genotype × Environment Interaction Than Conventional Breeding Programs
No full textGenotype × environment interaction (G × E) is of increasing importance for dairy cattle breeders due to international multiple-environment selection of animals as well as the differentiation of production environments within countries. This theoretical simulation study tested the hypothesis that genomic selection (GS) breeding programs realize larger genetic benefits by cooperation in the presence of G × E than conventional pedigree-based selection (PS) breeding programs. We simulated two breeding programs each with their own cattle population and environment. Two populations had either equal or unequal population sizes. Selection of sires was done either across environments (cooperative) or within their own environment (independent). Four scenarios, (GS/PS) × (cooperative/independent), were performed. The genetic correlation (rg) between the single breeding goal trait expressed in two environments was varied between 0.5 and 0.9. We compared scenarios for genetic gain, rate of inbreeding, proportion of selected external sires, and the split-point rg that is the lowest value of rg for long-term cooperation. Between two equal-sized populations, cooperative GS breeding programs achieved a maximum increase of 19.3% in genetic gain and a maximum reduction of 24.4% in rate of inbreeding compared to independent GS breeding programs. The increase in genetic gain and the reduction in rate of inbreeding realized by GS breeding programs with cooperation were respectively at maximum 9.7% and 24.7% higher than those realized by PS breeding programs with cooperation. Secondly, cooperative GS breeding programs allowed a slightly lower split-point rg than cooperative PS breeding programs (0.85∼0.875 vs ≥ 0.9). Between two unequal-sized populations, cooperative GS breeding programs realized higher increase in genetic gain and showed greater probability for long-term cooperation than cooperative PS breeding programs. Secondly, cooperation using GS were more beneficial to the small population while also beneficial but much less to the large population. In summary, by cooperation in the presence of G × E, GS breeding programs realize larger improvements in terms of the genetic gain and rate of inbreeding, and have greater possibility of long-term cooperation than conventional PS breeding programs. Therefore, we recommend cooperative GS breeding programs in situations with mild to moderate G × E, depending on the sizes of two populations.</p
Characterization of sporulation dynamics of Pseudoclostridium thermosuccinogenes using flow cytometry
Get PDFSingle-cell analysis of microbial population heterogeneity is a fast growing research area in microbiology due to its potential to identify and quantify the impact of subpopulations on microbial performance in, for example, industrial biotechnology, environmental biology, and pathogenesis. Although several tools have been developed, determination of population heterogenity in anaerobic bacteria, especially spore-forming clostridia species has been amply studied. In this study we applied single cell analysis techniques such as flow cytometry (FCM) and fluorescence-assisted cell sorting (FACS) on the spore-forming succinate producer Pseudoclostridium thermosuccinogenes. By combining FCM and FACS with fluorescent staining, we differentiated and enriched all sporulation-related morphologies of P. thermosuccinogenes. To evaluate the presence of metabolically active vegetative cells, a blend of the dyes propidium iodide (PI) and carboxy fluorescein diacetate (cFDA) tested best. Side scatter (SSC-H) in combination with metabolic indicator cFDA dye provided the best separation of sporulation populations. Based on this protocol, we successfully determined culture heterogeneity of P. thermosuccinogenes by discriminating between mature spores, forespores, dark and bright phase endospores, and vegetative cells populations. Henceforth, this methodology can be applied to further study sporulation dynamics and its impact on fermentation performance and product formation by P. thermosuccinogenes.</p
A multi-objective optimization model for dairy feeding management
No full textThe allocation of feedstuff to intensively managed dairy cows to achieve different objectives is challenging due to the inherent complexity of the system and the combinatorial problem that has to be solved. Pareto-based multi-objective optimization approaches using evolutionary algorithms can help to address these challenges and show the trade-offs and synergies among various objectives. Here we present a framework for multi-objective optimization with the Differential Evolution (DE) algorithm applied to dairy feeding systems with grazing and concentrate supply to generate an approximation of the Pareto front. The available feed resources are located in different feeding areas, and the number of animals and groups of animals with similar feeding requirements are distributed across these areas for feeding purposes. To evaluate the DE algorithm, we performed two in-silico experiments to: (1) compare the solutions quality of single-objective DE with exact Linear Programming (LP) solutions, and (2) assess the influence of different stocking rates (number of cows/ha) on milk production, feed allocation and economic performance indicators. The DE solutions that minimize the feeding costs for different stocking rates (1.1–2.6 cows/ha) closely approached the solutions derived with LP, confirming the quality of the heuristic algorithm. The multi-objective model scenarios demonstrated that increasing stocking density would enhance milk production and gross margin per unit of area at largely unchanged productivity per animal by shifting the feed ration from roughage to a large proportion of supplementary concentrate feed. At low stocking rates solutions with high productivity and gross margin and a large proportion of roughage in the ration and limited supplementary feeding were identified. We conclude that the multi-objective optimization with a Pareto-based DE algorithm is highly effective to explore the interrelations among conflicting objectives and to find suitable solutions.</p
Effects of nitrogen addition on soil methane uptake in global forest biomes
No full textNitrogen (N) deposition has been conventionally thought to decrease forest soil methane (CH4) uptake, while the biome specific and dose dependent effect is poorly understood. Based on a meta-analysis of 63 N addition trials from 7 boreal forests, 8 temperate forests, 13 subtropical and 4 tropical forests, we evaluated the effects of N addition on soil CH4 uptake fluxes across global forest biomes. When combining all N addition levels, soil CH4 uptake was insignificantly decreased by 7% in boreal forests, while N addition significantly decreased soil CH4 uptake by 39% in temperate forests and by 21% in subtropical and tropical forests, respectively. Meta-regression analyses, however, indicated a shift from a positive to a negative effect on soil CH4 uptake with increasing N additions both in boreal forests (threshold = 48 kg N ha−1 yr−1) and temperate forests (threshold = 27 kg N ha−1 yr−1), while no such shift was found in subtropical and tropical forests. Considering that current N deposition to most boreal and temperate forests is below the abovementioned thresholds, N deposition likely exerts a positive to neutral effect on soil CH4 uptake in both forest biomes. Our results provide new insights on the biome specific and dose dependent effect of N addition on soil CH4 sink in global forests and suggest that the current understanding that N deposition decreases forest soil CH4 uptake is flawed by high levels of experimental N addition.</p
A DMP-triggered in vivo maternal haploid induction system in the dicotyledonous Arabidopsis
No full textDoubled haploid technology using inducer lines carrying mutations in ZmPLA1/MTL/NLD and ZmDMP1–4 has revolutionized traditional maize breeding. ZmPLA1/MTL/NLD is conserved in monocots and has been used to extend the system from maize to other monocots5–7, but no functional orthologue has been identified in dicots, while ZmDMP-like genes exist in both monocots and dicots4,8,9. Here, we report that loss-of-function mutations in the Arabidopsis thaliana ZmDMP-like genes AtDMP8 and AtDMP9 induce maternal haploids, with an average haploid induction rate of 2.1 ± 1.1%. In addition, to facilitate haploid seed identification in dicots, we established an efficient FAST-Red fluorescent marker-based haploid identification system that enables the identification of haploid seeds with >90% accuracy. These results show that mutations in DMP genes also trigger haploid induction in dicots. The conserved expression patterns and amino acid sequences of ZmDMP-like genes in dicots suggest that DMP mutations could be used to develop in vivo haploid induction systems in dicots
Gendered species preferences link tree diversity and carbon stocks in Cacao agroforest in Southeast Sulawesi, Indonesia
Get PDFThe degree to which the maintenance of carbon (C) stocks and tree diversity can be jointly achieved in production landscapes is debated. C stocks in forests are decreased by logging before tree diversity is affected, while C stocks in monoculture tree plantations increase, but diversity does not. Agroforestry can break this hysteresis pattern, relevant for policies in search of synergy. We compared total C stocks and tree diversity among degraded forest, complex cacao/fruit tree agroforests, simple shade-tree cacao agroforestry, monoculture cacao, and annual crops in the Konawe District, Southeast Sulawesi, Indonesia. We evaluated farmer tree preferences and the utility value of the system for 40 farmers (male and female). The highest tree diversity (Shannon-Wiener H index 2.36) and C stocks (282 Mg C ha-1) were found in degraded forest, followed by cacao-based agroforestry systems (H index ranged from 0.58-0.93 with C stocks of 75-89 Mg ha-1). Male farmers selected timber and fruit tree species with economic benefits as shade trees, while female farmers preferred production for household needs (fruit trees and vegetables). Carbon stocks and tree diversity were positively related (R2 = 0.72). Adding data from across Indonesia (n = 102), agroforestry systems had an intermediate position between forest decline and reforestation responses. Maintaining agroforestry in the landscape allows aboveground C stocks up to 50 Mg ha-1 and reduces biodiversity loss. Agroforestry facilitates climate change mitigation and biodiversity goals to be addressed simultaneously in sustainable production landscapes.</p