Water productivity of milk produced in three different dairy production systems in Southern Brazil

Assessing the eco-efficiency of milk production systems using water-energy-labor-food nexus

Globally, massive resource inputs and undesired outputs hindered the further development of the dairy industry. This study proposed a method applying data envelopment analysis to the water-energy-labor-food nexus to assess the eco-efficiency of the milk production system (MEE) from a systemic perspective. Using national statistics on scale farms for the period 2014-2021, we illustrated the effects of scale and intensification on MEE in China. In the study period, the production cost increased by 23 % and milk production rose by 30 % at the same time. Despite the increases in both water and energy inputs, the rise in milk production weakened the resource burdens and thus lifted MEE by 24 %. The resource investment pattern shifted from water- and labor-oriented to energy-oriented. Under current conditions, production technology and system management were at higher superiority to advance than farm scale, while mechanization and on-farm clean energy production are the keys to further lifting MEE.

How the type of dairy production system affects the nutrient balance from an environmental and economic perspective

The knowledge of nutrient flow in dairy farms has to be explored to find optimized strategies for efficient nutrient conversion to milk. This study aims to improve the understanding of variances in nitrogen and phosphorus balance and efficiency indicators between dairy farm systems. The study analyzed 67 dairy cattle farms located in the watershed Lajeado Tacongava, Rio Grande do Sul State, Brazil. Selected dairy farms represented three production systems: confined (3 farms); semi-confined (7 farms); pasture-based (57 farms). Input-output nutrient balances were calculated at the dairy system level for nitrogen and phosphorus over a year. Inputs are feed and fertilizer and outputs are milk and meat. The main nitrogen and phosphorus input on the all farms resulted from the feed. The average N and P surplus on pasture-based farms were 352 and 49 kg ha-1 year-1, respectively. In semi-confined systems were 508 and 63 kg ha-1 year-1 and in confined systems were 786 and 70 kg ha-1 year-1. When considering the monetary value of the total N surplus, the averages were US$ 2.615, 4.950, and 12.171 for pasture-based, semi-confined and confined systems respectively. Monetary values of P surplus were US$ 346, 588, and 1119 for pasture-based, semi-confined and confined. The productive aspects that most determined the values of N and P surplus were the total number of lactating cows and the farm area. Results indicate that surplus can partially replace chemical nitrogen fertilizer, except in the confined system, and fully replace phosphorus fertilizer. Confined farms presented values to use surplus as fertilizer greater than the crop demand. For the other production systems, it happens only for phosphorus. Large variability between dairy farms of the same production system and between different production systems was observed. It reflects the inherent productive, economic, and environmental conditions of each farm and system.

Sustainability of livestock farms: The case of the district of Moyobamba, Peru

The Peruvian Amazon is a geographical area with great biodiversity, where the main economic activities are agricultural crops and grazing animals. The evaluation of sustainability in production systems is based on the analysis of economic, environmental and social components, which are variable between production units or livestock farms. The classification of livestock farms based on their characteristics of similarity and differences can contribute to the most appropriate assessment of their level of sustainability. The objective of this research was to determine the level of sustainability of livestock farms in the district of Moyobamba, San Martín, Peru, based on environmental, economic and social criteria. The research was carried out from November 2018 to February 2019 with a survey of a sample of 60 livestock farms out of a population of 2220. A survey-type form and data collection in the field were applied, adapting a methodology that proposes inferring on 33 indicators grouped into six criteria: three environmental criteria (soil quality, pasture health and animal quality), two economic criteria (farm system and farm economy), and a social criterion of the farm. A scale from 1 to 10 was used to assess the condition of each indicator. The typification of farms was carried out through a Conglomerate Analysis. To analyze the level of sustainability, Amoeba graphs were constructed for each defined farm group. Qualitative variables were analyzed with contingency tables and quantitative variables using the T test (p < 0.05). Three types of livestock farms were identified, differentiated by level of education, farm size, years in cattle raising and number of cattle heads (p < 0.05), where Group 1 is less experienced, Group 1 has more area and cattle, and Group 3 only have older years in livestock. There were significant differences between the evaluated criteria and the sustainability index. From the typification of livestock farms, Group 2 (13 farms) presented a higher level of sustainability as did Group 3 (16 farms), while Group 1 (31 farms) presented unsustainable conditions. The environmental indicators based on animal quality and farm system show unsustainability in all farms the District of Moyobamba, as they fail to exceed the threshold of sustainability (5).