Risks, resources and reason: understanding smallholder decisions around farming system interventions in Eastern Indonesia

Adoption of new cattle management practices by Indonesian smallholders occurs less as a ‘technology transfer’ in the classical sense but rather as a series of conscious decisions by farming households weighing risks and resources as well as matching innovations to livelihood strategies. This paper uncovers the context of decisions and communication of innovations by way of social networks. The research looks at two geographically distinct cases where new cattle management practices have been introduced. We apply the lens of a common sense framework initially introduced by Clifford Geertz. Smallholder decisions are analysed within a socio-cultural context and a particular set of resources, risks and livelihood objectives. We show that the respective value placed on land, cattle and food security is central to adoption of new cattle management techniques. Far from accepting everything novel, smallholders are selective and willing to make changes to their farming system if they do not conflict with livelihood strategies. Innovations are communicated through a range of existing social networks and are either matched to existing livelihood strategies or perceived as stepping-stones out of agriculture.

Alligator Hunting Season Report 2012

The 2012 Public Alligator Hunting Season marked the fifth general alligator hunting season after a closure of nearly 40 years. This year’s public hunt, utilizing a random computer drawing, was open to all applicants, including nonresidents, and was conducted on public and private lands (not enrolled in the Private Lands Program) from the Midlands to the coast. A total of 321 applications for the WMA Alligator Hunt were received, 89.1% from residents, the remainder from eleven other states. The 2012 season began at noon on September 13th and ended at noon on October 10th. This booklet also shows the season results of the hunt and recommendations for the next year's hunt.

Alligator Hunting Season Report 2013

The 2013 Public Alligator Hunting Season marked the sixth general alligator hunting season after a closure of nearly 40 years. This year’s public hunt, utilizing a random computer drawing, was open to all applicants, including nonresidents, and was conducted on public and private lands (not enrolled in the Private Lands Program) from the Midlands to the coast. A total of 222 applications for the WMA Alligator Hunt were received, 89.1% from residents, the remainder from eleven other states. The 2013 season began at noon on September 14th and ended at noon on October 12th. This booklet also shows the season results of the hunt and recommendations for the next year's hunt.

Alligator Season CITES Tag Locations

This map shows the locations and gives the telephone numbers for Department of Natural Resources offices for obtaining CITES tags for hunting alligators in South Carolina.

South Carolina alligator hunting guide for 2016

This booklet was developed to provide basic information regarding the alligator hunting season and what hunters will need in order to familiarize themselves with taking alligators. It includes common hunting techniques, safety tips, how to harvest an alligator, requirements for processing an alligator, and how to care for an alligator hide.

Diet composition of a declining steppe bird the Little Bustard (Tetrax tetrax) in relation to farming practices

Foraging strategies and diet selection play an essential role in individual survival and reproductive success. The study of feeding ecology becomes crucial when it concerns endangered species such as the Little Bustard (Tetrax tetrax), whose populations are suffering strong declines as a consequence of agricultural intensification. Despite the fact that several populations are overwintering in areas affected by agricultural transformation, nothing is known about how feeding behavior responds to these changes. We studied for the first time the winter diet composition of the Little Bustard in Spain and compared it between areas with two different farming systems: dry and irrigated farmland. Diet was studied through the micro-histological analysis of 357 droppings collected in 16 locations across the wintering range of the Little Bustard in Spain. Up to 62 plant species were identified. Most consumed species were cultivated legumes (46.7%) and dicotyledon weeds (45.6%), while monocotyledons were scarcely consumed (7.7%). Diet composition differed significantly between dry and irrigated farmland areas. In irrigated areas, diet was mainly composed of legumes, in particular alfalfa (Medicago sativa). In contrast, in dry farmland areas diet was more diverse, composed mainly of weeds (Compositae, Papaveraceae, and Cruciferae) and also cultivated legumes, particularly vetch (Vicia sativa). These results suggest that legume crops could be an effective measure to improve habitat quality in areas with scarce food resources. However, in the case of irrigated areas, the strong reliance on alfalfa could make the Little Bustard more vulnerable to changes in land use. This study is the first step to understand the winter trophic requirements of the endangered Little Bustard, but further research is necessary to understand the food requirements of this species during the entire annual cycle.

Emissions from cattle farming in Brazil.

2016

The common bean (Phaseolus vulgaris L.) demonstration unity system - sudf - applicability potential for family farming.

2016

Agroecological management of insect pests on sugarbeets and lettuce cultivated in organic farming

Two-year field trials were conducted in northern Italy with the aim of developing a trapcrop-based agroecological approach for the control of flea beetles (Chaetocnema tibialis (Illiger), Phyllotreta spp. (Chevrolat) (Coleoptera: Chrysomelidae)) and Lygus rugulipennis Poppius (Hemiptera: Miridae), key pests of sugar beet and lettuce, respectively. Flea beetle damage trials compared a trap cropping treatment, i.e., a sugar beet plot with a border of Sinapis alba (L.) and Brassica juncea (L.) with a control treatment, i.e., a sugar beet plot with bare soil as field border. Sugar beets grown near trap crops showed a significant decrease (≈40%) in flea beetle damage compared to control. Moreover, flea beetle damage varied with distance from the edge of the trap plants, being highest at 2 m from the edge, then decreasing at higher distances. Regarding L. rugulipennis on lettuce two experiments were conducted. A semiochemical-assisted trap cropping trial was supported by another test evaluating the efficacy of pheromones and trap placement. In this trial, it was found that pheromone baited traps caught significantly more specimens of L. rugulipennis than unbaited traps. It was also found that traps placed at ground level produced larger catches than traps placed at the height of 70 cm. In the semiochemical-assisted trap cropping experiment, a treatment where lettuce was grown next to two Alfa-Alfa borders containing pheromone baited traps was compared with a control treatment, where lettuce was grown near bare soil. This experiment showed that the above-mentioned strategy managed to reduce L. rugulipennis damage to lettuce by ≈30%. From these studies, it appears that trap crop-based strategy, alone or with baited traps, made it possible to reduce crop damage to economically acceptable levels and to minimize the need for insecticide treatments, showing that those strategy could be implemented in organic farming as a means of controlling insect pests.

Smart Farming in Italian agriculture: essays on adoption and diffusion dynamics shaping the agricultural digital transition

Smart Farming Technologies (SFT) is a term used to define the set of digital technologies able not only to control and manage the farm system, but also to connect it to the many disruptive digital applications posed at multiple links along the value chain. The adoption of SFT has been so far limited, with significant differences at country-levels and among different types of farms and farmers. The objective of this thesis is to analyze what factors contributes to shape the agricultural digital transition and to assess its potential impacts in the Italian agri-food system. Specifically, this overall research objective is approached under three different perspectives. Firstly, we carry out a review of the literature that focuses on the determinants of adoption of farm-level Management Information Systems (MIS), namely the most adopted smart farming solutions in Italy. Secondly, we run an empirical analysis on what factors are currently shaping the adoption of SFT in Italy. In doing so, we focus on the multi-process and multi-faceted aspects of the adoption, by overcoming the one-off binary approach often used to study adoption decisions. Finally, we adopt a forward-looking perspective to investigate what the socio-ethical implications of a diffused use of SFT might be. On the one hand, our results indicate that bigger, more structured farms with higher levels of commercial integration along the agri-food supply chain are those more likely to be early adopters. On the other hand, they highlight the need for the institutional and organizational environment around farms to more effectively support farmers in the digital transition. Moreover, the role of several other actors and actions are discussed and analyzed, by highlighting the key role of specific agri-food stakeholders and ad-hoc policies, with the aim to propose a clearer path towards an efficient, fair and inclusive digitalization of the agrifood sector.

Big Data approaches as a support for precision livestock farming techniques

With the advent of new technologies it is increasingly easier to find data of different nature from even more accurate sensors that measure the most disparate physical quantities and with different methodologies. The collection of data thus becomes progressively important and takes the form of archiving, cataloging and online and offline consultation of information. Over time, the amount of data collected can become so relevant that it contains information that cannot be easily explored manually or with basic statistical techniques. The use of Big Data therefore becomes the object of more advanced investigation techniques, such as Machine Learning and Deep Learning. In this work some applications in the world of precision zootechnics and heat stress accused by dairy cows are described. Experimental Italian and German stables were involved for the training and testing of the Random Forest algorithm, obtaining a prediction of milk production depending on the microclimatic conditions of the previous days with satisfactory accuracy. Furthermore, in order to identify an objective method for identifying production drops, compared to the Wood model, typically used as an analytical model of the lactation curve, a Robust Statistics technique was used. Its application on some sample lactations and the results obtained allow us to be confident about the use of this method in the future.

Innovative microbiome-based system for the improvement of productivity, safety and sustainability of mussels farming

Northwestern Adriatic Sea Mediterranean mussels are exposed to fluctuating environmental parameters and to natural and anthropogenic stressors. Today is well known that mussels can be defined as holobiont, even if remains a lot to elucidate about how an organism and its microbial component response to environmental stress. This PhD dissertation aims to investigate microbiome possible adaptive patters exploiting the organism physiology response to stress, using the NGS sequencing method. The experimental approach consisted of two phases to first determine (i) the microbiome at a tissue scale level, (ii) the microbiome and physiological response to natural and anthropogenic stress environment and the chemical assessment of the microecosystem the Northwestern Adriatic Sea Mediterranean Mussel lives in. Results revealed firstly a robust microbiome well differentiated from seawater microecosystem, with compositional variations at the organ level. Thanks to those findings, digestive gland, the organ in which digestive and detoxification processes allow animal to tolerate and accumulate xenobiotics of natural and anthropogenic origin, was the selected tissue for the second phase of the project. The second phase of the project evaluated the putative physiological variations and the compositional changes in microbiome of digestive gland. I then manage to assess microbiome region trends across the north Adriatic, with each sampling site well differentiated from the others. Finally, a chemical method able to a powerful tool for the analytical detection of the major pollutants in mussels were validated. These first results may provide baseline information for future studies approaches of seasonal and region trends of microbiota profiles and physiological responses in terms of metabolism.

Long-term Prospects For The Environmental Profile Of Advanced Sugar Cane Ethanol.

This work assessed the environmental impacts of the production and use of 1 MJ of hydrous ethanol (E100) in Brazil in prospective scenarios (2020-2030), considering the deployment of technologies currently under development and better agricultural practices. The life cycle assessment technique was employed using the CML method for the life cycle impact assessment and the Monte Carlo method for the uncertainty analysis. Abiotic depletion, global warming, human toxicity, ecotoxicity, photochemical oxidation, acidification, and eutrophication were the environmental impacts categories analyzed. Results indicate that the proposed improvements (especially no-til farming-scenarios s2 and s4) would lead to environmental benefits in prospective scenarios compared to the current ethanol production (scenario s0). Combined first and second generation ethanol production (scenarios s3 and s4) would require less agricultural land but would not perform better than the projected first generation ethanol, although the uncertainties are relatively high. The best use of 1 ha of sugar cane was also assessed, considering the displacement of the conventional products by ethanol and electricity. No-til practices combined with the production of first generation ethanol and electricity (scenario s2) would lead to the largest mitigation effects for global warming and abiotic depletion. For the remaining categories, emissions would not be mitigated with the utilization of the sugar cane products. However, this conclusion is sensitive to the displaced electricity sources.

Profundidade de deposição de semente de milho na região dos Campos Gerais, Paraná

No Tillage system is fully incorporated to farming in the region of Campos Gerais, state of Paraná. Accuracy and precision in the planting process are items of great importance for the success of this system. In order to evaluate the planting process, thirty eight farms were selected as sites for analysis of the placement depth of seeds. The research area was 4 or 5 planting rows, evaluating 10 plantlets per row. The average seed depth was around 46 mm, and significant differences between rows were observed in 21 areas. The average coefficient of variation was around 20%, the statistical limit between medium and high. Analyses of other parameters show that those coefficients may represent different errors in the process. The planting process in Campos Gerais can be considered efficient regarding to the average seed depth. However, the analysis of variability implies de need of actions concerning to anthropic and machinery factors.