Abstract

Benchmarking programs for crop and livestock farms have been used by farmers to identify ways to improve farm efficiencies. This study developed a set of benchmarks for oyster, mussel, and seaweed farming in Maine (USA). Farm-level survey data were used to calculate benchmarking metrics for each farm respondent. Results showed the importance of disaggregating benchmarking metrics by production scale, gear type, and whether farms were initial startup (defined in this study as <5 years in business) or established (>5 years in business) farms. The initial analysis of cost structures on individual farms provided useful information from which to identify key categories for disaggregation. Identification of the most important cost inputs further points to which benchmarks will be of greatest value for different groups of farms. Results for oyster farms showed that startup costs per oyster harvested were lowest ($0.20/oyster) on established bottom culture farms as compared to $0.96/oyster for established suspended oyster farms, and highest ($1.75/oyster) on startup oyster farms. Profits (Net Farm Income) per oyster were greatest on established bottom oyster farms followed by established suspended oyster farms, but were negative on average, for startup farms. Per-hectare, however, profits were greater on established suspended than bottom culture oyster farms. Labor efficiencies were also greatest for established suspended oyster farms (65 oysters/hour of labor), followed by established bottom culture oyster farms (55 oysters/hour of labor), with the lowest labor efficiency (44 oysters/hour of labor) for startup oyster farms. Given the inherent variability among aquaculture farms, adequate numbers of observations of participating farmers are necessary within each production scale/gear type and startup/established categories for benchmarks to be of value. For emerging sectors of aquaculture, benchmarking metrics can be useful for navigating the critical startup period, but obtaining sufficient numbers of observations is a challenge. Benchmarking metrics for established farm businesses provide guidance on the levels of production and economic performance necessary to be successful. Overall, benchmark values are most useful when applied in a holistic fashion that takes into consideration the performance of the farm across all production, revenue, expense, and efficiency categories (labor, capital, and financial).

摘要

农民已利用农作物和牲畜农场的基准测试计划来确定提高农场效率的方法。这项研究为美国缅因州的牡蛎、贻贝和海藻养殖制定了一套基准。农场层面的调查数据用于计算每个农场受访者的基准指标。结果显示了按生产规模、装备类型以及农场是初次启动（在本研究中定义为经营<5年）还是成熟（经营>5年）农场分类基准指标的重要性。对各个农场成本结构的初步分析提供了有用的信息，可从中确定关键的分类类别。确定最重要的成本投入进一步指出哪些基准对于不同的农场群体具有最大价值。牡蛎养殖场的结果显示，已建立的底层养殖场的每只收获牡蛎的启动成本最低（0.20 美元/牡蛎），而已建立的暂停牡蛎养殖场的启动成本为 0.96 美元/牡蛎，而初创牡蛎养殖场的启动成本最高（1.75 美元/牡蛎）。已建立的底层牡蛎养殖场的每只牡蛎利润（农场净收入）最高，其次是已建立的暂停牡蛎养殖场，但初创农场的平均利润为负。然而，按公顷计算，已建立的暂停养殖牡蛎养殖场的利润高于底层养殖牡蛎养殖场。已建立的暂停牡蛎养殖场的劳动效率也最高（65 只牡蛎/每小时劳动力），其次是已建立的底层养殖牡蛎养殖场（55 牡蛎/每小时劳动力），启动时的劳动效率最低（44 牡蛎/每小时劳动力）牡蛎养殖场。鉴于水产养殖场之间固有的差异性，在每个生产规模/设备类型和启动/已建立的类别中，参与农民的足够数量的观察是必要的，以使基准有价值。对于水产养殖的新兴行业，基准指标对于度过关键的启动期很有用，但获得足够数量的观察结果是一个挑战。成熟农场企业的基准指标为成功所需的生产水平和经济绩效提供了指导。总体而言，基准值在以整体方式应用时最有用，考虑农场在所有生产、收入、费用和效率类别（劳动力、资本和财务）方面的绩效。在每个生产规模/装备类型和启动/既定类别中，参与农民的足够数量的观察是必要的，这样基准才有价值。对于水产养殖的新兴行业，基准指标对于度过关键的启动期非常有用，但获得足够数量的观察结果是一个挑战。成熟农场企业的基准指标为成功所需的生产水平和经济绩效提供了指导。总体而言，基准值在以整体方式应用时最有用，考虑农场在所有生产、收入、费用和效率类别（劳动力、资本和财务）方面的绩效。在每个生产规模/装备类型和启动/既定类别中，参与农民的足够数量的观察是必要的，这样基准才有价值。对于水产养殖的新兴行业，基准指标对于度过关键的启动期很有用，但获得足够数量的观察结果是一个挑战。成熟农场企业的基准指标为成功所需的生产水平和经济绩效提供了指导。总体而言，基准值在以整体方式应用时最有用，考虑农场在所有生产、收入、费用和效率类别（劳动力、资本和财务）方面的绩效。