Fakultät Agrarwissenschaften

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Die Fakultät entwickelt in Lehre und Forschung nachhaltige Produktionstechniken der Agrar- und Ernährungswirtschaft. Sie erarbeitet Beiträge für den ländlichen Raum und zum Verbraucher-, Tier- und Umweltschutz.

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The active core microbiota of two high-yielding laying hen breeds fed with different levels of calcium and phosphorus
(2022) Roth, Christoph; Sims, Tanja; Rodehutscord, Markus; Seifert, Jana; Camarinha-Silva, Amélia
The nutrient availability and supplementation of dietary phosphorus (P) and calcium (Ca) in avian feed, especially in laying hens, plays a vital role in phytase degradation and mineral utilization during the laying phase. The required concentration of P and Ca peaks during the laying phase, and the direct interaction between Ca and P concentration shrinks the availability of both supplements in the feed. Our goal was to characterize the active microbiota of the entire gastrointestinal tract (GIT) (crop, gizzard, duodenum, ileum, caeca), including digesta- and mucosa-associated communities of two contrasting high-yielding breeds of laying hens (Lohmann Brown Classic, LB; Lohmann LSL-Classic, LSL) under different P and Ca supplementation levels. Statistical significances were observed for breed, GIT section, Ca, and the interaction of GIT section x breed, P x Ca, Ca x breed and P x Ca x breed (p < 0.05). A core microbiota of five species was detected in more than 97% of all samples. They were represented by an uncl. Lactobacillus (average relative abundance (av. abu.) 12.1%), Lactobacillus helveticus (av. abu. 10.8%), Megamonas funiformis (av. abu. 6.8%), Ligilactobacillus salivarius (av. abu. 4.5%), and an uncl. Fusicatenibacter (av. abu. 1.1%). Our findings indicated that Ca and P supplementation levels 20% below the recommendation have a minor effect on the microbiota compared to the strong impact of the bird’s genetic background. Moreover, a core active microbiota across the GIT of two high-yielding laying hen breeds was revealed for the first time.
Biomonitoring via DNA metabarcoding and light microscopy of bee pollen in rainforest transformation landscapes of Sumatra
(2022) Carneiro de Melo Moura, Carina; Setyaningsih, Christina A.; Li, Kevin; Merk, Miryam Sarah; Schulze, Sonja; Raffiudin, Rika; Grass, Ingo; Behling, Hermann; Tscharntke, Teja; Westphal, Catrin; Gailing, Oliver; Carneiro de Melo Moura, Carina; Department of Forest Genetics and Forest Tree Breeding, University of Göttingen, Göttingen, Germany; Setyaningsih, Christina A.; Department of Palynology and Climate Dynamics, Albrecht-von-Haller-Institute for Plant Sciences, University of Göttingen, Göttingen, Germany; Li, Kevin; Agroecology, Department of Crop Sciences, University of Göttingen, Göttingen, Germany; Merk, Miryam Sarah; Statistics and Econometrics, University of Göttingen, Göttingen, Germany; Schulze, Sonja; Agroecology, Department of Crop Sciences, University of Göttingen, Göttingen, Germany; Raffiudin, Rika; Department of Biology, IPB University ID, Bogor, Indonesia; Grass, Ingo; Department of Ecology of Tropical Agricultural Systems, University of Hohenheim, Stuttgart, Germany; Behling, Hermann; Department of Palynology and Climate Dynamics, Albrecht-von-Haller-Institute for Plant Sciences, University of Göttingen, Göttingen, Germany; Tscharntke, Teja; Agroecology, Department of Crop Sciences, University of Göttingen, Göttingen, Germany; Westphal, Catrin; Functional Agrobiodiversity, Department of Crop Sciences, University of Göttingen, Göttingen, Germany; Gailing, Oliver; Centre of Biodiversity and Sustainable Land Use, University of Göttingen, Göttingen, Germany
Background: Intense conversion of tropical forests into agricultural systems contributes to habitat loss and the decline of ecosystem functions. Plant-pollinator interactions buffer the process of forest fragmentation, ensuring gene flow across isolated patches of forests by pollen transfer. In this study, we identified the composition of pollen grains stored in pot-pollen of stingless bees, Tetragonula laeviceps , via dual-locus DNA metabarcoding (ITS2 and rbcL ) and light microscopy, and compared the taxonomic coverage of pollen sampled in distinct land-use systems categorized in four levels of management intensity (forest, shrub, rubber, and oil palm) for landscape characterization. Results: Plant composition differed significantly between DNA metabarcoding and light microscopy. The overlap in the plant families identified via light microscopy and DNA metabarcoding techniques was low and ranged from 22.6 to 27.8%. Taxonomic assignments showed a dominance of pollen from bee-pollinated plants, including oil-bearing crops such as the introduced species Elaeis guineensis (Arecaceae) as one of the predominant taxa in the pollen samples across all four land-use types. Native plant families Moraceae, Euphorbiaceae, and Cannabaceae appeared in high proportion in the analyzed pollen material. One-way ANOVA (p > 0.05), PERMANOVA (R² values range from 0.14003 to 0.17684, for all tests p-value > 0.5), and NMDS (stress values ranging from 0.1515 to 0.1859) indicated a lack of differentiation between the species composition and diversity of pollen type in the four distinct land-use types, supporting the influx of pollen from adjacent areas. Conclusions: Stingless bees collected pollen from a variety of agricultural crops, weeds, and wild plants. Plant composition detected at the family level from the pollen samples likely reflects the plant composition at the landscape level rather than the plot level. In our study, the plant diversity in pollen from colonies installed in land-use systems with distinct levels of forest transformation was highly homogeneous, reflecting a large influx of pollen transported by stingless bees through distinct land-use types. Dual-locus approach applied in metabarcoding studies and visual pollen identification showed great differences in the detection of the plant community, therefore a combination of both methods is recommended for performing biodiversity assessments via pollen identification.
Combining improved mungbean cultivars with plant growth promoting rhizobacteria inoculation and regulated deficit irrigation to increase crop productivity
(2024) Pataczek, Lisa; Cadisch, Georg
The cultivation of legumes provides an approach to sustainably intensify agricultural production, since short-duration legumes can fit into existing cereal-based cropping systems, diversifying farm incomes and farmers diets, as well as providing environmental benefits through the fixation of atmospheric N2 and, thus, enhancing yields of following crops. Mungbean is a legume, which plays already an important role in the traditional nutrition of people in the Global South. Its nutritious seeds can improve food security and the short growing duration facilitates the diversification of mainly cereal-based crop rotations. However, yields are low and may even become lower in future in the face of climate change. Main constraints of mungbean cultivation include pest and diseases, as well as heat, drought and soil salinity due to inappropriate irrigation techniques or saline ground water. The main aim of this thesis was therefore to analyse the effects of more advanced cultivation techniques, i.e. the use of plant growth promoting rhizobacteria (PGPR) and regulated deficit irrigation (RDI), on the productivity and nitrogen (N) fixation capacity of improved mungbean (Vigna radiata L.) cultivars, resistant and/or tolerant to pests, diseases, heat and soil salinity. An extended literature review was conducted to summarize the current understanding of the use of PGPRs and the effect on crop productivity, especially on marginal land (Chapter 2). The use of PGPRs can on the one hand side increase plant growth through direct and indirect mechanisms, such as BNF, hormone production and nutrient solubilization or the production of antibiotics to suppress phytodiseases. Especially 1-aminocyclopropane-1-carboxylic acid (ACC) deaminase activity plays a significant role to reduce the negative impact of stress environments. On the other side PGPRs can be used to remediate decontaminated sites, through metabolic capabilities, transforming for instance aromatic compounds into less toxic compounds, or the biodegradation of pesticides and organic pollutants. Since ACC deaminase-producing bacteria are also supposed to enhance root growth, it is assumed that they can potentially increase soil N uptake and/or infection sites for rhizobia to biologically fix atmospheric N2 (BNF). In order to test the effect of ACC deaminase-producing PGPRs on mungbean productivity and N accumulation, three strains were tested as single- or multistrain inoculation in the field: Rhizobium phaseoli, Bacillus subtilis and Pseudomonas fluorescens (Chapter 3). Their effect on one improved mungbean cultivar (NM11, resistant to the Mungbean Yellow Mosaic Disease) was assessed on two research sites in Faisalabad, Pakistan. The impact of the strains differed significantly, with no effect on productivity (total biomass, seed yield) or total N accumulation (BNF and soil-N uptake) with multi-strain inoculation of all strains and single-strain inoculation of P. fluorescens. Inoculation with B. subtilis did, however, result in significantly increased dry matter (roots: +211 kg ha-1, total dry matter: +1.7 t ha-1), and total plant-N (+36 kg ha-1), while R. phaseoli inoculation enhanced BNF (+24%). The results suggested that only the single strain inoculation of B. subtilis and R. phaseoli was promising in terms of productivity increase, however, the choice of the strain should be made according to the soil-N status: low soil-N favors R. phaseoli inoculation, while medium to high soil-N would rather point towards the use of B. subtilis. The improved mungbean cultivar NM11 was additionally tested together with three other improved cultivars (AVMU 1604, AVMU 1635 and KPS2, resistant/tolerant to powdery mildew, bruchids and heat and salt, respectively), in combination with RDI in a greenhouse trial at the University of Hohenheim (Chapter 4). The aim was to identify differences in drought adaptation strategies between the cultivars in terms of dry matter partitioning, yield, harvest index, pod harvest index, water use efficiency and carbon-13 isotope discrimination. Levels of water deficit as depletion fractions (%) of total available soil water were set to 0.45, 0.65 and 0.8, corresponding to recommended irrigation, moderate and severe water deficit, respectively. The cultivars differed in their drought resistance strategies, exhibiting either drought escape, avoidance, tolerance or a combination of several strategies. The cultivar KPS2 showed mainly a drought escape mechanism through faster development, stable yields and greatest harvest index/pod harvest index (36%/69%) across all RDI treatments and cultivars. The cultivar AVMU 1604 displayed mainly a mixture of drought avoidance and escape through increased remobilization of assimilates from vegetative plant parts to pods/seeds, resulting in greater yield under water deficit by 52%. The choice of a cultivar for the field should be based, thus, on the prevailing climatic conditions (season and region): KPS2 can grow in areas with terminate drought conditions, whereas AVMU 1604 can tolerate intermittent drought conditions. The results of this thesis showed that ACC deaminase-producing PGPRs can substantially affect N uptake, although this effect is barely discussed in literature. Moreover, improved mungbean cultivars, exhibiting already a range of tolerances and resistances to certain pests and diseases, showed a great potential in adapting to drought conditions, representing a viable option for cultivation under increasing abiotic and biotic stress factors in the face of climate change.
Effects of different ground segmentation methods on the accuracy of UAV-based canopy volume measurements
(2024) Han, Leng; Wang, Zhichong; He, Miao; He, Xiongkui; Han, Leng; College of Science, China Agricultural University, Beijing, China; Wang, Zhichong; Tropics and Subtropics Group, Institute of Agricultural Engineering, University of Hohenheim, Stuttgart, Germany; He, Miao; College of Science, China Agricultural University, Beijing, China; He, Xiongkui; College of Science, China Agricultural University, Beijing, China
The nonuniform distribution of fruit tree canopies in space poses a challenge for precision management. In recent years, with the development of Structure from Motion (SFM) technology, unmanned aerial vehicle (UAV) remote sensing has been widely used to measure canopy features in orchards to balance efficiency and accuracy. A pipeline of canopy volume measurement based on UAV remote sensing was developed, in which RGB and digital surface model (DSM) orthophotos were constructed from captured RGB images, and then the canopy was segmented using U-Net, OTSU, and RANSAC methods, and the volume was calculated. The accuracy of the segmentation and the canopy volume measurement were compared. The results show that the U-Net trained with RGB and DSM achieves the best accuracy in the segmentation task, with mean intersection of concatenation (MIoU) of 84.75% and mean pixel accuracy (MPA) of 92.58%. However, in the canopy volume estimation task, the U-Net trained with DSM only achieved the best accuracy with Root mean square error (RMSE) of 0.410 m 3 , relative root mean square error (rRMSE) of 6.40%, and mean absolute percentage error (MAPE) of 4.74%. The deep learning-based segmentation method achieved higher accuracy in both the segmentation task and the canopy volume measurement task. For canopy volumes up to 7.50 m 3 , OTSU and RANSAC achieve an RMSE of 0.521 m 3 and 0.580 m 3 , respectively. Therefore, in the case of manually labeled datasets, the use of U-Net to segment the canopy region can achieve higher accuracy of canopy volume measurement. If it is difficult to cover the cost of data labeling, ground segmentation using partitioned OTSU can yield more accurate canopy volumes than RANSAC.
Efficacy of various mechanical weeding methods - single and in combination - in terms of different field conditions and weed densities
(2021) Naruhn, Georg-Peter; Peteinatos, Gerassimos G.; Butz, Andreas F.; Möller, Kurt; Gerhards, Roland
Public awareness and environmental policies have increased interest in applying non-herbicide weed control methods in conventional farming systems. Even though mechanical weed control has been used for centuries in agricultural practice, continuous developments—both in terms of implements and automation technologies—are continuously improving the potential outcomes. Current mechanical weed control methods were evaluated for their weed control efficacy and effects on yield potential against their equivalent herbicide methods. Furthermore, not much is known about the correlation between weed control efficacy (WCE) of different mechanical methods at varying weed density levels. A total of six experiments in winter wheat (2), peas (2), and soybean (2) were carried out in the years 2018, 2019, and 2020 in southwestern Germany. Harrowing and hoeing treatments at different speeds were carried out and compared to the herbicide treatments and untreated control plots. Regarding the average WCE, the combination of harrowing and hoeing was both the strongest (82%) and the most stable (74–100%) mechanical treatment in the different weed density levels. Whereas, in average, hoeing (72%) and harrowing (71%) were on the same WCE level, but harrowing (49–82%) was more stable than hoeing (40–99%). The grain yields in winter wheat varied between 4.1 Mg∙ha−1 (control) and 6.3 Mg∙ha−1 (harrow), in pea between 2.8 Mg∙ha−1 (hoe slow) and 5.7 Mg∙ha−1 (hoe fast) and in soybean between 1.7 Mg∙ha−1 (control) and 4 Mg∙ha−1 (herbicide). However, there were no significant differences in most cases. The results have shown that it is not possible to pinpoint a specific type of treatment as the most appropriate method for this cultivation, across all of the different circumstances. Different field and weather conditions can heavily affect and impact the expected outcome, giving, each time, an advantage for a specific type of treatment.
Food informatics - Review of the current state-of-the-art, revised definition, and classification into the research landscape
(2021) Krupitzer, Christian; Stein, Anthony
Background: The increasing population of humans, changing food consumption behavior, as well as the recent developments in the awareness for food sustainability, lead to new challenges for the production of food. Advances in the Internet of Things (IoT) and Artificial Intelligence (AI) technology, including Machine Learning and data analytics, might help to account for these challenges. Scope and Approach: Several research perspectives, among them Precision Agriculture, Industrial IoT, Internet of Food, or Smart Health, already provide new opportunities through digitalization. In this paper, we review the current state-of-the-art of the mentioned concepts. An additional concept is Food Informatics, which so far is mostly recognized as a mainly data-driven approach to support the production of food. In this review paper, we propose and discuss a new perspective for the concept of Food Informatics as a supportive discipline that subsumes the incorporation of information technology, mainly IoT and AI, in order to support the variety of aspects tangent to the food production process and delineate it from other, existing research streams in the domain. Key Findings and Conclusions: Many different concepts related to the digitalization in food science overlap. Further, Food Informatics is vaguely defined. In this paper, we provide a clear definition of Food Informatics and delineate it from related concepts. We corroborate our new perspective on Food Informatics by presenting several case studies about how it can support the food production as well as the intermediate steps until its consumption, and further describe its integration with related concepts.
Genetics and breeding for humoral immunity and feed efficiency in indigenous chicken population in Kenya
(2024) Miyumo, Sophie; Chagunda, Mizeck G. G.
Indigenous chicken (IC) population contribute to food, nutrition, livelihood and economic security in many rural households in developing countries in the tropical regions. Despite their contribution, IC are predominantly raised under challenging free-range systems which limit their optimal production potential and utilization. Of significance, are disease morbidity and scarcity of feed resources. Indigenous chicken are exposed to a myriad of pathogens that cause various poultry diseases which result to massive production and economic losses. Among these diseases is Newcastle disease (NCD) which is endemic in the tropics and is considered important because of high prevalence and mortality rates. Seasonal variation in availability and quality of feed resources have a negative impact on production costs and performance of chicken. Furthermore, with climate change effects, environmental conditions are expected to significantly impact feed availability and pathogen epidemiology. Selective breeding for disease resistance and feed efficiency traits is an avenue through which individuals that are adaptative to disease-prone production environments, with ability to efficiently convert available feed resources into products and support their maintenance requirements can be sustainably produced. Therefore, this thesis aimed to generate information that can guide breeding decisions on selection for improved health and efficient production to enhance the overall performance of the indigenous chicken population in Kenya. Chapter 1 presented an overview on the relevance of indigenous chicken genetic resources in developing countries with respect to their proportion among chicken population, contribution at household and national levels, and adaptive capacity to local environments. The challenges experienced in IC production systems in developing countries and their impacts on productivity and profitability, with a focus on diseases and scarcity in feed resources were addressed in this chapter. Management strategies practiced on-farm to control diseases and cope with seasonal availability of feed resources and the limitations of these strategies were also discussed. Proposed alternative strategies related to selective breeding for traits that can be utilized to manage diseases and scarcity in feed resources in IC production systems were presented in this chapter. Finally, the chapter gave a justification for this study, and objective and outline of the thesis. Literature estimates of genetic parameters are considered resourceful in instances where estimates for traits of interest are not available or insufficient. Estimates obtained from different studies, however, may vary due to differences in population among other factors. The choice of which estimate from sampled studies to use, is in most cases subjective and this may lead to either underestimation or overestimation of potential genetic progress. Chapter 2 assessed the robustness of literature estimates of genetic parameters for traits of economic importance in chicken performing in the tropical and sub-tropical environments using meta-analysis. Additive genetic, maternal environment and residual variances, and heritability estimates for traits related to immunity, reproduction, survival, growth, egg production and feed efficiency from 70 studies were considered. Heterogeneity index showed that published estimates of the genetic parameters sampled from different studies significantly varied in each of the traits. Based on total variance, a higher proportion of the variation in genetic parameters were more due to random effect of study than sampling error. Reliability estimates (relative standard error) of the genetic parameters varied across the traits considered in this study, in which, traits well represented in terms of number of published estimated had lower levels of variation compared to traits with low published estimated. Study characteristics related to population, production system, estimation methods, sex, age and antigen (only for immune traits) significantly influenced variation in the sampled genetic parameters across the traits. Pooled genetic parameters estimated in this study using the inverse of sampling variance as a weighting factor indicate that the weighted averages of genetic parameters can be utilized where estimates are not available or insufficient. The significant variation among sampled studies and low reliability estimated in some of the traits imply that genetic parameter estimates from literature should be applied with caution to prevent negative impacts on breeding decisions and genetic progress. In addition, differences in study characteristics should be considered in order to use estimates from studies with population and production conditions characteristics that closely resemble the intended population and production system. Antibody response to challenging conditions is suggested a suitable indicator trait that can be utilized for indirect improvement of disease resistance. However, prior to selection, understanding the genetic background of antibody response in the population of interest is a prerequisite in setting up an effective selection strategy. Chapter 3 investigated non-genetic and genetic sources of variation in natural antibodies binding to keyhole limpet hemocyanin antigen (KLH-NAbs) and specific antibodies binding to NCD virus (NDV-IgG). Non-genetic factors related to sex, population, phylogenetic cluster, generation, line, genotype and age significantly influenced the antibody traits, and should therefore be accounted for in genetic evaluations to reduce bias and improve accuracy of selection. Considerable amount of additive genetic variation was observed in the KLH-NAbs and NDV-IgG traits, implying possibilities of improvement of the antibody traits through selective breeding. However, the low to moderate heritability estimated in the antibody traits indicate that relatively low accuracy levels would be expected and hence, reduced rate of genetic gains if mass selection would be used. Positive genetic correlations observed among KLH-NAb isotypes (KLH-IgM, KLH-IgG and KLH-IgA) suggest that the isotypes can be improved simultaneously. In contrast, KLH-NAbs were negatively correlated with NDV-IgG implying that genetic improvement of natural antibodies would be associated with low specific antibodies binding NDV. These findings provide a better understanding of factors affecting antibody traits in a heterogeneous chicken population and may enable effective decisions prior to inclusion of immune parameters in breeding programs intended for tropically adapted chicken. Considering that an effective immune system is heavily dependent on metabolic resources for maintenance and deployment of various immune responses, improved antibody levels is expected to compete for nutrients and energy with other functions, such as production. Besides, given the scarcity in feed resources in production systems in Kenya, competition for nutrients and energy among biological functions is likely to influence the efficiency of feed utilization. Therefore, it is pertinent to also determine the pleiotropic nature between the immunity, production and feed efficiency traits. Chapter 4 estimated genetic and phenotypic correlations among antibody, feed efficiency and production traits measured pre- (nine to 20 weeks of age) and post- (12 weeks from on-set of lay) maturity. Results revealed that improved feed efficiency would be associated with high growth rates, early maturing chicken, high egg mass and reduced feed intake. In contrast, improved general (KLH-IgM) and specific (NDV-IgG) immunity would result in lower growth rates and egg mass but associated with early sexual maturation and high feed intake. Negative genetic correlations estimated between feed efficiency and antibody traits imply that chicken of higher productivity and antibody levels will consume more feed to support both functions. These associations indicate that selective breeding for feed efficiency and immune competence may have genetic consequences on production traits and should therefore be accounted for in IC improvement programs. Based on marketable end products, a breeding goal targeting simultaneous improvement of meat and egg production to develop a dual-purpose (ICD) breed that can perform in low to medium input systems is recommended for the IC population. However, due to the dynamics in market forces over time, goals targeting specialized production to develop a meat (ICM) and a layer (ICL) breed that can perform in medium to high input systems are also recommended as alternatives. Prior to defining the selection criteria across the goals, it is necessary to determine optimal combination of traits in an index because this has an impact on the overall genetic merit of an individual and total index response. Chapter 5 evaluated various selection strategies for adoption in ICD and ICL and ICM goals in indigenous chicken breeding with respect to total index response, accuracy of selection, rate of inbreeding and number of generations of selection required to achieve pre-defined genetic gains. Selection strategy targeting only production traits in a goal had the highest total index response, highest index accuracy (only ICM goal) and lowest inbreeding rate per generation, and least number of generations of selection required to achieve pre-defined gains. The index was, however, associated with unfavorable correlated responses in feed efficiency and antibody traits. Addition of both feed efficiency and antibody response in a goal indicated favorable genetic gains could be achieved in these traits. Conversely, this strategy reduced total index response and increased the rate of inbreeding per generation and required additional number of generations of selection to achieve desired gains pre-defined in each of the goals. Inclusion of either feed-related traits or antibody traits in a goal showed that feed-related traits had a more negative impact on the total index response per generation but improved selection accuracy in the ICD and ICL goals compared to antibody traits. Based on these results, choice of whether to include feed efficiency or/and antibody response in the ICD, ICM and ICL goals should depend on targeted production system, resource availability to support additional number of generations of selection and magnitude of correlated responses on these traits when not included in the goals. Lastly, a synthesis of the thesis is presented in Chapter 6 where practical relevance and utilization of findings of the thesis in designing a breeding program for indigenous chicken population is demonstrated.
Is the system of rice intensification (SRI) pro poor? Labour, class and technological change in West Africa
(2021) Graf, Sarah Lena; Oya, Carlos
CONTEXT Increasing numbers of young people enter Sub-Saharan Africa's labour markets each year while industrial jobs only grow slowly. As 62% of Sub-Saharan Africans work in agriculture and as the rural population will continue to rise, agriculture will need to provide additional income- earning opportunities. In this context agricultural technologies should be promoted that can increase food production to answer rising demand and generate decent income-earning opportunities. The System of Rice Intensification (SRI) is widely promoted in West Africa and could address these needs – but recent findings from Asia present negative social impacts on workers. OBJECTIVE This paper explores the mechanisms that shape adoption patterns and impacts of SRI in different (West African) contexts through a labour lens. METHODS Our innovative theoretical framework integrates analytical and empirical categories from Farming Systems research and agrarian political economy. The mixed methods approach combines: (1) quantitative analysis of existing survey data from 857 agricultural households in Ghana, Benin and Mali; and (2) qualitative analysis of an in-depth case study in the Oti Region of Ghana. RESULTS AND CONCLUSION SRI increases yield and profitability in West African rice farming, especially when locally adapted. Farmers adjust SRI to fit lowland rice farming, where water cannot be controlled and to address labour constraints. Additional labour for transplanting (instead of broadcasting) – coinciding with an existing labour bottleneck – constrains SRI adoption. SRI is mainly practised by marginal and accumulating farmers and to a lesser extent by medium farmers. Accumulating farmers invest in agriculture, farm profit-oriented and overcome labour constraints by hiring. Thus, they can practise SRI on larger scale and their absolute benefits are higher. Nevertheless, they rely on hired labour to do so, which strengthens workers' bargaining position. Consequently, SRI benefits all: accumulating farmers who employ as well as marginal farmers and hired labourers. Contrary to findings from Asia, SRI seems to be relatively pro-poor in West Africa. SIGNIFICANCE While seasonal labour use remains a key constraint to technology adoption, labour intensive technologies can also contribute to increasing income-earning opportunities. The social outcomes of technological change will be shaped by both the existing agricultural practices and the social relations in which a new technology is adopted. Our theoretical framework can inform further research and the application of existing evidence to new contexts.
Phosphorus- and water- deficiency induced morpho-physiological and yield changes in maize (Zea mays L.)
(2024) Ning, Fangfang; Graeff-Hönninger, Simone
Phosphorus (P) is a nonrenewable and finite resource for all living things. It plays a crucial role as an essential nutrient in crop production. However, plants have low efficiency in utilizing P due to its immobility and low bioavailability. P deficiency can cause irreversible effects, particularly during the early stages of maize growth. Drought further exacerbates nutrient uptake challenges, especially for P, by limiting its diffusion in the soil. Therefore, the dual stress of drought and P deficiency restricts plants' shoot and root growth. It is necessary to investigate the interaction between P deficiency and drought and better understand the response mechanisms, as the effect of P deficiency on plant growth precedes the plant's own drought regulatory mechanisms. In Paper I, the effects of placed diammonium phosphate (DAP) and rock phosphate (RP) on the growth and development of two maize cultivars (Stabil and Ricardinio) were investigated combined with soil liming. Maize cultivars differed in their P utilization characteristics under low-P field conditions. The results showed that RP resulted in a lower leaf area index and light interception than DAP. This led to a 33% lower silage yield and a 29% lower P content at harvest. The PUE of RP was found to be 18%, which is 37% lower than that of DAP. Furthermore, soil liming reduced shoot biomass and caused a 35% decrease in shoot P content at the six-leaf stage. Maize cultivar ‘Stabil’ showed higher yield and P uptake. This paper demonstrated that placed RP could not be used as a substitute for DAP in silage maize production regardless of the application of lime to the soil. Paper II explored the impact of different types of P fertilizer (DAP and RP) on the root systems of maize. The results showed that P deficiency in the early stages of growth hindered root growth. However, in later stages, the roots exhibited enhanced lateral root growth in response to P deficiency. Although the differences in organic acids and phytohormones across different zones of the maize root system were not significant due to the delayed sampling, it is still feasible and necessary to conduct further investigations on organic acids and phytohormones in various root locations. Paper III tested deep P fertilizer placement as a strategy to alleviate combined drought and P deficiency stress in maize. It was tested under greenhouse conditions involving three factors: P fertilizer amount (low-P: LP, and high-P: HP), fertilizer placement (mixed (M, 0-18 cm), lower (L, 10-18 cm), and upper (U, 0-9 cm)), and soil water content (DS, 45% of soil water holding capacity (WHC)) and well-watered: WW, 75% WHC) and well-watered: WW). LP decreased shoot P content and both root and shoot biomass compared to HP. Under DS, root biomass increased by 50% and 95% in 0-18 and 10-18 cm depth at the fourth-leaf stage compared to WW treatment. However, root biomass decreased by at least 41% in different depths at the tenth leaf stage. Plants under DS consistently exhibited lower shoot biomass and P uptake at both stages. Although L-DS did not improve shoot growth and P uptake until the tenth-leaf stage, more than 55% higher root biomass and increased root length could be found in 10-18 cm depth compared to M-DS and U-DS treatments. This could potentially enhance P exploration in a larger soil volume and enable water absorption from deeper soil layers. However, no advantage in P uptake was observed with LP and HP until the ten-leaf stage. In conclusion, this thesis highlights the importance of optimizing P utilization strategies in maize production systems facing the dual challenges of P deficiency and drought stress. While soil liming and cultivar selection can help, high-solubility P fertilizers like DAP remain irreplaceable by RP due to their superior ability to support root development. It also discussed the possibilities and mechanisms for mitigating P and water- deficiency by promoting root growth in deeper soil layers through applying P fertilizers. This study provides a comprehensive evaluation of the feasibility of various maize cultivation and management practices under combined P deficiency and drought conditions, offering valuable references and practical guidelines for sustainable maize production in resource-limited environments.

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