Mineral Concentrations in Bovine Milk from Farms with Contrasting Grazing Management

Thirty conventional and twenty-four organic dairy farms were divided into equal numbers within system groups: high-pasture, standard-pasture, and low-pasture groups. Milk samples were collected monthly for 12 consecutive months. Milk from high-pasture organic farms contained less fat and protein than standard- and low-pasture organic farms, but more lactose than low-pasture organic farms. Grazing, concentrate feed intake and the contribution of non-Holstein breeds were the key drivers for these changes. Milk Ca and P concentrations were lower in standard-pasture conventional farms than the other conventional groups. Milk from low-pasture organic farms contained less Ca than high- and standard-pasture organic farms, while high-pasture organic farms produced milk with the highest Sn concentration. Differences in mineral concentrations were driven by the contribution of non-Holstein breeds, feeding practices, and grazing activity; but due to their relatively low numerical differences between groups, the subsequent impact on consumers’ dietary mineral intakes would be minor.

Status of accumulated heavy metals in soils from organic and conventional farms in Akinyele Local Government, Ibadan, Oyo State, Nigeria

The risk associated with the presence of heavy metals in soil is their potential toxicity and ability to enter the ecosystem through the food chain. Total heavy metal content of a soil is inadequate for predicting the toxicity of heavy metals in soil. Therefore, the current study was designed to determine the various forms in which the selected heavy metals: Chromium (Cr), Lead (Pb), Nickel (Ni), and Cadmium (Cd) exist in the soil to ascertain the available forms for plant uptake. Soils samples were randomly collected from selected organic and conventional farms in Akinyele local government, Ibadan, Oyo State, Nigeria, at different depths (0-15, 15-30 and 30-45 cm) using random sampling method. Routine analysis was carried out to determine the textural classes and chemical properties of soil samples. The total heavy metals of the soil samples were determined and their fractions were analysed using sequential extraction method. Cadmium was not detected in most of the soil samples. Residual fraction was predominant in all the analysed heavy metals. In addition, Cr was more associated with the oxidizable fraction having a range of 0.1 mg/kg from Ajibode organic farm (AO) at 30-45 cm depth. Pb and Ni were both more associated with reducible fraction with Pb having a range of 2.7 mg/kg in Ajibode conventional farm (AI) at 0-15 cm depth and 0.1 mg/kg in (AI) at 30-45 cm depth. Reducible values of Ni ranges from 4.3 mg/kg in AI at 0-15 cm to 1.4 mg/kg in AO at 30-45 cm. The apparent mobility and bioavailability for these heavy metals in the studied soils were in the order: Pb>Cr>Ni. The result showed that uptake of heavy metals by the plants would be low as the concentration of the exchangeable form of the heavy metals in the analysed soil sample has the least concentration when compared with the other forms.

Smart Indoor Farms: Leveraging Technological Advancements to Power a Sustainable Agricultural Revolution

Conventional farming necessitates a large number of resources and infrastructure such as land, irrigation, manpower to manage farms, etc. Modern initiatives are required to automate conventional farms. Smart indoor farms offer the potential to remedy the shortfalls of conventional farms by providing a controlled, intelligent, and smart environment. This paper presents a three-dimensional perspective consisting of soilless farming, energy harvesting, and smart technologies, which could be considered as the three important characteristics of smart indoor farms. A six-layer smart indoor farms architecture has also been proposed, which explains how data are collected using various sensors and devices and then transmitted onto the cloud infrastructure for further analysis and control through various layers. Artificial lighting, smart nutrition management, and artificial climate control, to name a few, are some of the important requirements for smart indoor farms while considering control and service management factors. The major bottleneck in installing such systems is both the economical and the technical constraints. However, with the evolution of technology (and when they become widely available in the near future), a more favourable farming scenario may emerge. Furthermore, smart indoor farms could be viewed as a potential answer for meeting the demands of a sustainable agricultural revolution as we move closer to Agriculture 4.0. Finally, in order to adapt smart indoor farms and their study scope, our work has presented various research areas to potential researchers.

Piglet Gut and in-Barn Manure from Farms on a Raised without Antibiotics Program Display Reduced Antimicrobial Resistance but an Increased Prevalence of Pathogens

In response to new stringent regulations in Canada regarding the use of antibiotics in animal production, many farms have implemented practices to produce animals that are raised without antibiotics (RWA) from birth to slaughter. This study aims to assess the impact of RWA production practices on reducing the actual total on-farm use of antibiotics, the occurrence of pathogens, and the prevalence of antimicrobial resistance (AMR). A 28-month longitudinal surveillance of farms that adopted the RWA program and conventional farms using antibiotics in accordance with the new regulations (non-RWA) was conducted by collecting fecal samples from 6-week-old pigs and composite manure from the barn over six time points and applying whole-genome sequencing (WGS) to assess the prevalence of AMR genes as well as the abundance of pathogens. Analysis of in-barn drug use records confirmed the decreased consumption of antibiotics in RWA barns compared to non-RWA barns. WGS analyses revealed that RWA barns had reduced the frequency of AMR genes in piglet feces and in-barn manure. However, metagenomic analyses showed that RWA barns had a significant increase in the frequency of pathogenic Firmicutes in fecal samples and pathogenic Proteobacteria in barn manure samples.

Resource Use Efficiency Among Aerobic and Conventional Rice Farms in Eastern Dry Zone of Karnataka: A Comparative Analysis

The efficiency with which farmers use available resources is very important for agricultural production. This study examines the comparative resource use efficiency (RUE) between aerobic and conventional rice farms in Eastern Dry Zone (Zone-5) of Karnataka. Cross-sectional data were collected from 100 rice cultivating farmers (50 in Aerobic farms and 50 in Conventional farms) using snow ball sampling technique. Cobb-Douglas production function, Marginal analysis of resource utilization, Data Envelopment Analysis (DEA) were some of the analytical tools used in the study. The mean aerobic farm size was 0.43 ha while in Conventional rice, it was 0.63 ha. The physical water use efficiency (WUE) in aerobic farms (3.84 q/acre inch) was higher than conventional farms (1.64 q/acre inch). Also, the economic WUE was higher in aerobic farms (1643.54 `/acre inch) compared to conventional farms (269.41 `/acre inch). RUE indicated that, resources were not optimally utilized in both Aerobic Rice Cultivation (ARC) and Conventional Rice Cultivation (CRC). Bullock labour, machine labour, seeds and irrigation were underutilized in ARC, whereas, FYM was underutilized in CRC indicating that usage of additional amount of these inputs leads to increase in the returns. The DEA revealed that aerobic rice cultivating farms were more technically and economically efficient compared to conventional rice cultivating farms. Effective policies to promote and create awareness about aerobic rice can boost the rice production and productivity sustainably. The focus should be given to optimal allocation of resources which enhances the farm productivity and returns

A Comparison of the Prevalence of the Parasites of the Digestive Tract in Goats from Organic and Conventional Farms

The aim of the study was to compare the prevalence and intensity of gastrointestinal parasitic infections in goats kept on organic (n = 76) and conventional farms (n = 82). In general, a higher prevalence of some gastrointestinal parasitic infections was found in the conventional farms compared to the organic farms: the mean prevalence of Eimeria spp. was 85.4% in conventional farms and 77.6% in organic farms, that of Fasciola hepatica was 6.10% in conventional farms and 2.63% in organic farms, and that of Moniezia expansa was 31.7% and 17.1%, in conventional and organic farms, respectively. Both farm types demonstrated a similar mean prevalence of nematodes (80.3 vs. 84.2%). Conventional farms demonstrated a significantly higher intensity of infection with E. arloingi, Haemonchus spp., Nematodirus spp. and Moniezia expansa compared to organic farms. They also demonstrated a higher intensity of infection with Eimeria spp. than organic farms. The prophylactic programs used to combat parasitic infections in both types of farms appear ineffective and require improvement. There is a need for goat herds to be covered by ongoing parasitological monitoring. It is also recommended that keepers employ rotational or intensive rotational grazing methods and take care to ensure the hygiene of animal quarters and livestock rooms.

HAM-ART: An optimised culture-free Hi-C metagenomics pipeline for tracking antimicrobial resistance genes in complex microbial communities

Shotgun metagenomics is a powerful tool to identify antimicrobial resistance (AMR) genes in microbiomes but has the limitation that extrachromosomal DNA, such as plasmids, cannot be linked with the host bacterial chromosome. Here we present a laboratory and bioinformatics pipeline HAM-ART (Hi-C Assisted Metagenomics for Antimicrobial Resistance Tracking) optimised for the generation of metagenome-assembled genomes including both chromosomal and extrachromosomal AMR genes. We demonstrate the performance of the pipeline in a study comparing 100 pig faecal microbiomes from low- and high-antimicrobial use pig farms (organic and conventional farms). We found significant differences in the distribution of AMR genes between low- and high-antimicrobial use farms including a plasmid-borne lincosamide resistance gene exclusive to high-antimicrobial use farms in three species of Lactobacilli.Author SummaryAntimicrobial resistance (AMR) is one of the biggest global health threats humanity is facing. Understanding the emergence and spread of AMR between different bacterial species is crucial for the development of effective countermeasures. In this paper we describe a user-friendly, affordable and comprehensive (laboratory and bioinformatics) workflow that is able to identify, associate and track AMR genes in bacteria. We demonstrate the efficiency and reliability of the method by comparing 50 faecal microbiomes from pig farms with high-antibiotic use (conventional farms), and 50 faecal microbiomes from pig farms with low-antibiotic use (organic farms). Our method provides a novel approach to resistance gene tracking, that also leads to the generation of high quality metagenomic assembled genomes that includes genes on mobile genetic elements, such as plasmids, that would not otherwise be included in these assembled genomes.

Organic and Conventional Grape Growing in Italy: a Technical Efficiency Comparison Using a Parametric Approach

Several studies have focused attention on the differences between organic and conventional farms in terms of efficiency, and controversial findings have resulted from these applications. One source of controversy concerns the assumption about the frontier(s) adopted for the comparison: a common frontier or two separate frontiers for organic and conventional methods? This paper aims to estimate technical efficiency in Italian grape farming. A stochastic frontier analysis (SFA) was applied to a sample of 531 farms (440 conventional and 91 organic farms) collected from the Farm Accountancy Network Database. Among others, a test for evaluating whether a unique or separate frontier was performed. The findings suggest that organic and conventional farms would lie on a common frontier and that organic farms have greater capacity than conventional farms in using their own technical inputs (efficiency amounts to 83.6% and 77.8%, respectively). A number of implications derive from these findings.