Cage row arrangement affects the performance of laying hens in the hot humid tropics

Although the traditional cage system of housing laying hens is gradually being faced out due to welfare reasons, cages are still common in most developing tropical countries in different arrangements. In a 12-week experiment, the effects of a three cage row arrangement on hen-day production and egg qualities of Shaver Brown hens was studied. Data were collected from 2 layer sheds housing 9,000 hens in a 3-cage row arrangement (southern row, northern row and middle row) with 3,000 hens per row. Data were analysed for a randomized complete block design where cage rows were the treatments and weeks the blocks. Results showed no significant effects of cage row arrangement on feed intake, hen-day production, per cent yolk and Haugh unit (P>0.05). Egg weight, egg mass and per cent shell were significantly reduced and feed conversion ratio increased on the middle row (P<0.05). Egg weight, egg mass, per cent shell and feed conversion ratio did not differ between the side rows (P>0.05). These results suggest that battery cage row arrangement may not affect the rate of lay but egg weight, egg mass and efficiency of feed utilisation may be adversely affected in hens housed in the middle row. These findings have both economic and welfare implications

Soil biodiversity: functions, threats and tools for policy makers

Human societies rely on the vast diversity of benefits provided by nature, such as food, fibres, construction materials, clean water, clean air and climate regulation. All the elements required for these ecosystem services depend on soil, and soil biodiversity is the driving force behind their regulation. With 2010 being the international year of biodiversity and with the growing attention in Europe on the importance of soils to remain healthy and capable of supporting human activities sustainably, now is the perfect time to raise awareness on preserving soil biodiversity. The objective of this report is to review the state of knowledge of soil biodiversity, its functions, its contribution to ecosystem services and its relevance for the sustainability of human society. In line with the definition of biodiversity given in the 1992 Rio de Janeiro Convention, soil biodiversity can be defined as the variation in soil life, from genes to communities, and the variation in soil habitats, from micro-aggregates to entire landscapes. Bio Intelligence Service, IRD, and NIOO, Report for European Commission (DG Environment

Citizen science and remote sensing for crop yield gap analysis

The world population is anticipated to be around 9.1 billion in 2050 and the challenge is how to feed this huge number of people without affecting natural ecosystems. Different approaches have been proposed and closing the ‘yield gap’ on currently available agricultural lands is one of them. The concept of ‘yield gap’ is based on production ecological principles and can be estimated as the difference between a benchmark (e.g. climatic potential or water-limited yield) and the actual yield. Yield gap analysis can be performed at different scales: from field to global level. Of particular importance is estimating the yield gap and revealing the underlying explanatory factors contributing to it. As decisions are made by farmers, farm level yield gap analysis specifically contributes to better understanding, and provides entry points to increased production levels in specific farming systems. A major challenge for this type of analysis is the high data standards required which typically refer to (a) large sample size, (b) fine resolution and (c) great level of detail. Clearly, obtaining information about biophysical characteristics and crop and farm management for individual agricultural activities within a farm, as well as farm and farmer’s characteristics and socio-economic conditions for a large number of farms is costly and time-consuming. Nowadays, the proliferation of different types of mobile phones (e.g., smartphones) equipped with sensors (e.g., GPS, camera) makes it possible to implement effective and low-cost “bottom-up” data collection approaches such as citizen science. Using these innovative methodologies facilitate the collection of relatively large amounts of information directly from local communities. Moreover, other data collection methods such as remote sensing can provide data (e.g., on actual crop yield) for yield gap analysis. The main objective of this thesis, therefore, was to investigate the applicability of innovative data collection approaches such as crowdsourcing and remote sensing to support the assessment and monitoring of crop yield gaps. To address the main objective, the following research questions were formulated: 1) What are the main factors causing the yield gaps at the global, regional and crop level? 2) How could data for yield gap explaining factors be collected with innovative “bottom-up” approaches? 3) What are motivations of farmers to participate in agricultural citizen science? 4) What determines smallholder farmers to use technologies (e.g., mobile SMS) for agricultural data collection? 5) How can synergy of crowdsourced data and remote sensing improve the estimation and explanation of yield variability? Chapter 2 assesses data availability and data collection approaches for yield gap analysis and provides a summary of yield gap explaining factors at the global, regional and crop level, identified by previous studies. For this purpose, a review of yield gap studies (50 agronomic-based peer-reviewed articles) was performed to identify the most commonly considered and explaining factors of the yield gap. Using the review, we show that management and edaphic factors are more often considered to explain the yield gap compared to farm(er) characteristics and socio-economic factors. However, when considered, both farm(er) characteristics and socio-economic factors often explain the yield gap. Furthermore, within group comparison shows that fertilization and soil fertility factors are the most often considered management and edaphic groups. In the fertilization group, factors related to quantity (e.g., N fertilizer quantity) are more often considered compared to factors related to timing (e.g., N fertilizer timing). However, when considered, timing explained the yield gap more often. Finally, from the results at regional and crop level, it was evident that the relevance of factors depends on the location and crop, and that generalizations should not be made. Although the data included in yield gap analysis also depends on the objective, knowledge of explaining factors, and methods applied, data availability is a major limiting factor. Therefore, bottom-up data collection approaches (e.g., crowdsourcing) involving agricultural communities can provide alternatives to overcome this limitation and improve yield gap analysis. Chapter 3 explores the motivations of farmers to participate in citizen science. Building on motivational factors identified from previous citizen science studies, a questionnaire based methodology was developed which allowed the analysis of motivational factors and their relation to farmers’ characteristics. Using the developed questionnaire, semi-structured interviews were conducted with smallholder farmers in three countries (Ethiopia, Honduras and India). The results show that for Indian farmers a collectivistic type of motivation (i.e., contribute to scientific research) was more important than egoistic and altruistic motivations. For Ethiopian and Honduran farmers an egoistic intrinsic type of motivation (i.e., interest in sharing information) was most important. Moreover, the majority of the farmers in the three countries indicated that they would like to receive agronomic advice, capacity building and seed innovation as the main returns from the citizen science process. Country and education level were the two most important farmers’ characteristics that explained around 20% of the variation in farmers’ motivations. The results also show that motivations to participate in citizen science are different for smallholders in agriculture compared to other sectors. For example fun has appeared to be an important egoistic intrinsic factor to participate in other citizen science projects, the smallholder farmers involved in this research valued ‘passing free time’ the lowest. Chapter 4 investigates the factors that determine farmers to adopt mobile technology for agricultural data collection. To identify the factors, the unified theory of acceptance and use of technology (UTAUT2) model was employed and extended with additional constructs of trust, mastery-approach goals and personal innovativeness in information technology. As part of the research, we setup data collection platforms using open source applications (Frontline SMS and Ushahidi) and farmers provided their farm related information using SMS for two growing seasons. The sample for this research consisted of group of farmers involved in a mobile SMS experiment (n=110) and another group of farmers which was not involved in a mobile SMS experiment (n=110), in three regions of Ethiopia. The results from the structural equation modelling showed that performance expectancy, effort expectancy, price value and trust were the main factors that influence farmers to adopt mobile SMS technology for agricultural data collection. Among these factors, trust is the strongest predictor of farmer’s intention to adopt mobile SMS. This clearly indicates that in order to use the citizen science approach in the agricultural domain, establishing a trusted relationship with the smallholder farming community is crucial. Given that performance expectancy significantly predicted farmer’s behavioural intention to adopt mobile SMS, managers of agricultural citizen science projects need to ensure that using mobile SMS for agricultural data collection offers utilitarian benefits to the farmers. The importance of effort expectancy on farmer’s intention to adopt mobile SMS clearly indicates that mobile phone software developers need to develop easy to use mobile applications. Chapter 5 demonstrates the results of synergetic use of remote sensing and crowdsourcing for estimating and explaining crop yields at the field level. Sesame production on medium and large farms in Ethiopia was used as a case study. To evaluate the added value of the crowdsourcing approach to improve the prediction of sesame yield using remote sensing, two independent models based on the relationship between vegetation indices (VIs) and farmers reported yield were developed and compared. The first model was based on VI values extracted from all available remote sensing imagery acquired during the optimum growing period (hereafter optimum growing period VI). The second model was based on VI values extracted from remote sensing imagery acquired after sowing and before harvest dates per field (hereafter phenologically adjusted VI). To select the images acquired between sowing and harvesting dates per field, farmers crowdsourced crop phenology information was used. Results showed that vegetation indices derived based on farmers crowdsourced crop phenology information had a stronger relationship with sesame yield compared to vegetation indices derived based on the optimum growing period. This implies that using crowdsourced information related to crop phenology per field used to adjust the VIs, improved the performance of the model to predict sesame yield. Crowdsourcing was further used to identify the factors causing the yield variability within a field. According to the perception of farmers, overall soil fertility was the most important factor explaining the yield variability within a field, followed by high presence of weeds. Chapter 6 discusses the main findings of this thesis. It draws conclusions about the main research findings in each of the research questions addressed in the four main chapters. Finally, it discusses the necessary additional steps (e.g., data quality, sustainability) in a broader context that need to be considered to utilize the full potential of innovative data collection approaches for agricultural citizen science.</p

Cushion plant morphology controls biogenic capability\ua0and facilitation effects of Silene acaulis along\ua0an elevation gradient

The stress-gradient hypothesis (SGH) predicts that the balance of plant\u2013plant interactions shifts along abiotic environmental gradients, with facilitation becoming more frequent under stressful conditions. However, recent studies have challenged this perspective, reporting that positive interactions are, in some cases, more common at the intermediate level of environmental severity gradients. Here, we test whether and how neighbour effects by Silene acaulis cushions vary along a 700 m wide altitudinal transect, in relation to cushion morphological traits and environmental severity. Field measurements along the gradient, within and outside cushions, included (i) species richness and cover of coexisting vascular plants; (ii) cushion morphology; (iii) above- and below-ground microclimate; and (iv) soil quality. We used the relative interaction index to decouple neighbour trait effects and environmental severity effects on plant diversity at different elevations. The ability of the cushion plant to facilitate heterospecifics shifts considerably along the elevation gradient, being greatest at the intermediate level. On the other hand, Silene morphological traits steadily change along the gradient, from lax, soft and flat-shaped cushion habits at low elevation to tightly knit and dome-shaped habits at high elevation. Cushion morphological changes are associated with mitigating effects on microclimate, indicating that cushions effectively act as a heat-trap at medium and high elevations, while at low elevations the soft and flat cushions avoid excessive heat accumulation by tight coupling with the surrounding atmosphere. At the upper end of the gradient, cushion cespitose\u2013pulvinate compactness and high stem density appear to be critical traits in modulating the net effect of plant\u2013plant interaction, since the space available for hosting other vascular species is considerably reduced. In conclusion, this work provides a mechanistic link between plant morphological traits, associated biogenic microclimate changes and variation in net plant\u2013plant interactions along the explored severity gradient. Our findings support an alternative conceptual model to SGH, with plant facilitation collapsing at the upper extreme of the abiotic stress gradient

Crop Management with the IoT: an Interdisciplinary Survey

In this study we analyze how crop management is going to benefit from the Internet of Things providing an overview of its architecture and components from an agronomic and a technological perspective. The present analysis highlights that IoT is a mature enabling technology, with articulated hardware and software components. Cheap networked devices may sense crop fields at a finer grain, to give timeliness warnings on stress conditions and the presence of disease to a wider range of farmers. Cloud computing allows to reliably store and access heterogeneous data, developing and deploy farm services. From this study emerges that IoT is also going to increase attention to sensor quality and placement protocol, while Machine Learning should be oriented to produce understandable knowledge, which is also useful to enhance Cropping System Simulation systems

IoT Applications Computing

The evolution of emerging and innovative technologies based on Industry 4.0 concepts are transforming society and industry into a fully digitized and networked globe. Sensing, communications, and computing embedded with ambient intelligence are at the heart of the Internet of Things (IoT), the Industrial Internet of Things (IIoT), and Industry 4.0 technologies with expanding applications in manufacturing, transportation, health, building automation, agriculture, and the environment. It is expected that the emerging technology clusters of ambient intelligence computing will not only transform modern industry but also advance societal health and wellness, as well as and make the environment more sustainable. This book uses an interdisciplinary approach to explain the complex issue of scientific and technological innovations largely based on intelligent computing

Energy, structure, soil and self-regulation in plant/soil systems: a conceptual model

1989 Fall.Includes bibliographical references.Typescript (Photocopy).A new concept is presented which suggests that in stable plant/soil systems, plants control the soil environmental factors that affect plant growth and the interactions among those factors by controlling system structure. The concept is based on the plant-control hypothesis and rhizocentric model of soil structural development. The plant-control hypothesis declares that in plant/soil systems energy is the primary resource, and structure an essential regulator of energy flows. The rhizocentric model of soil structural development in grass-dominated plant/soil systems describes the process which results in plant-control of soil structure, and, consequently, of energy and nutrient flows for such systems. In conjunction, the plant-control hypothesis and rhizocentric model form a conceptual model of control in plant/soil systems. The conceptual model may help explain the self-regulatory capabilities of stable plant/soil systems, and the causes of instability in some agricultural plant/soil systems. Examination of published data from various sources has revealed no case in which application of the conceptual control model did not result in logically consistent, reliable prediction of experimental outcomes, plausible interpretation of previously uninterpretable results, and often, formulation of testable new hypotheses. It is concluded that the control model -- and the plant-control hypothesis and rhizocentric model which it implies -- has enough credibility to merit further critical examination as a potentially useful conceptual tool for soil and agricultural science, biology, and ecology

Journal of Agrometeorology

Not AvailableJournal of Agrometeorology Not Availabl

Cotton Agriculture and the Function of Gravel Mulch in the Northern Rio Grande

The site of Poshu’Owingeh was one of several ancestral Tewa villages to experience rapid growth in the 14th and 15th centuries A.D. in northern New Mexico. Recent research has proposed that this growth was one aspect of a trend characterized by nonlinear socioeconomic change produced by increasing population size and connectivity. Agriculture, commodity production, and exchange are fundamental to this model, but direct evidence for intensification is limited and no empirical data exists for the function and mechanics of the technologies which are supposed to have supported surplus production. This research addresses the problem by examining paleobotanical and soil evidence for the function of gravel mulch, a unique agricultural technology hypothesized to have supported cotton agriculture in portions of the Northern Rio Grande. Physical soil properties and base cation ratios are used to reconstruct the irrigation effect of gravel mulch, and soil nutrient levels are measured to assess change in soil quality associated with cultivation. Fossil pollen assemblages recovered from agricultural soil layers are used to determine the mix of crops grown in gravel mulch fields. A spatial database of archaeological sites is used to reconstruct Puebloan population dynamics in the Tewa Basin. This is compared to published estimates of population growth, the timing of socioeconomic developments in the region, and climate reconstructions. Fossil pollen concentrations indicate that cotton was the main crop grown at Poshu’Owingeh. The substantial increase in the ratio of cotton to maize and a decrease in the diversity of economic wild plant taxa at Poshu’Owingeh suggest cotton cultivation was more intensive here than other documented sites in the region. Soil analysis revealed no evidence for degradation associated with gravel mulch. Cation ratios and particle size distribution in the A horizon suggest that gravel mulch continues to enhance subsurface water flux. I estimate that the runoff required to produce the sodium leaching observed in mulched profiles is generated by relatively intense precipitation generated by monsoon storms. Peak rates for the spatial expansion of farming populations responsible for the construction of the gravel mulch-cotton fields follows rapid population growth in the great Tewa Basin, is coincident with the intensification of regional exchange networks, and strengthening of the North American Monsoon. Given the mechanics of agricultural technology documented in this study, and hypotheses for the importance of cotton in the regional economy; it is concluded that population dynamics, climate change, and human niche construction interacted played a significant role in social change and economic expansion in the late precontact Northern Rio Grande

Transforming Agriculture in Southern Africa

This book provides a synthesis of the key issues and challenges facing agriculture and food production in Southern Africa. Southern Africa is facing numerous challenges from diverse issues such as agricultural transformations, growing populations, urbanization and climate change. These challenges place great pressure on food security, agriculture, water availability and other natural resources, as well as impacting biodiversity. Drawing on case studies from Lesotho, Malawi, Mozambique, Namibia, South Africa, Swaziland, Tanzania, Zambia and Zimbabwe, the chapters in this book consider these challenges from an interdisciplinary perspective, covering key areas in constraints to production, the most important building blocks of good farming practices, and established and emerging technologies. This book will be a valuable support for informing new policies and processes aimed at improving food production and security and developing sustainable agriculture in Southern Africa. This informative volume will be key reading for those interested in agricultural science, African studies, rural studies, development studies and sustainability. It will also be a valuable resource for policymakers, governmental and nongovernmental organizations, and agricultural practitioners