Good Growth Plan 2014-2019 - Spain

Abstract
---------------------------

Syngenta is committed to increasing crop productivity and to using limited resources such as land, water and inputs more efficiently. Since 2014, Syngenta has been measuring trends in agricultural input efficiency on a global network of real farms. The Good Growth Plan dataset shows aggregated productivity and resource efficiency indicators by harvest year. The data has been collected from more than 4,000 farms and covers more than 20 different crops in 46 countries. The data (except USA data and for Barley in UK, Germany, Poland, Czech Republic, France and Spain) was collected, consolidated and reported by Kynetec (previously Market Probe), an independent market research agency. It can be used as benchmarks for crop yield and input efficiency.

Geographic coverage
---------------------------

National coverage

Analysis unit
---------------------------

Agricultural holdings

Kind of data
---------------------------

Sample survey data [ssd]

Sampling procedure
---------------------------

A. Sample design
Farms are grouped in clusters, which represent a crop grown in an area with homogenous agro- ecological conditions and include comparable types of farms. The sample includes reference and benchmark farms. The reference farms were selected by Syngenta and the benchmark farms were randomly selected by Kynetec within the same cluster.

B. Sample size
Sample sizes for each cluster are determined with the aim to measure statistically significant increases in crop efficiency over time. This is done by Kynetec based on target productivity increases and assumptions regarding the variability of farm metrics in each cluster. The smaller the expected increase, the larger the sample size needed to measure significant differences over time. Variability within clusters is assumed based on public research and expert opinion. In addition, growers are also grouped in clusters as a means of keeping variances under control, as well as distinguishing between growers in terms of crop size, region and technological level. A minimum sample size of 20 interviews per cluster is needed. The minimum number of reference farms is 5 of 20. The optimal number of reference farms is 10 of 20 (balanced sample).

C. Selection procedure
The respondents were picked randomly using a “quota based random sampling” procedure. Growers were first randomly selected and then checked if they complied with the quotas for crops, region, farm size etc. To avoid clustering high number of interviews at one sampling point, interviewers were instructed to do a maximum of 5 interviews in one village.

BF Screened from Spain were selected based on the following criterion:

(a) Pepper growers (Province Almeria):
- Passive greenhouse
- Part of a integrated producer or cooperative
- Exported orientated
- RF producing variety 'Melchor'

-> Integrated producers: those that integrate the production & exportation of crops. They own the land and buy production outside to fulfill market demands. This is different from cooperatives as this ones only buy production to small farmers associated to them, they don't own land, they are intermediates to sell farmer production.
-> Professionals, marketing oriented, direct link to foodchain (It means that Cooperatives or Integrated Producers sell directly to supermarkets or traders in Europe)
- innovators (early adopters)
- Sell production to cooperatives and growers receive technical support, varieties, recommendations ( from cooperatives).

(b) Tomato growers (Province Almeria):
- Passive greenhouse
- part of a integrated producer or cooperative
- Exported orientated
- RF producing variety 'Caniles'
-> Integrated producers: those that integrate the production & exportation of crops. They own the land and buy production outside to fulfill market demands. This is different from cooperatives as this ones only buy production to small farmers associated to them, they don't own land, they are intermediates to sell farmer production.
-> Professionals, marketing oriented, direct link to foodchain (It means that Cooperatives or Integrated Producers sell directly to supermarkets or traders in Europe) - innovators (early adopters)
Sell production to cooperatives and growers receive technical support, varieties, recommendations ( from cooperatives).

(c) Medium/Large growers (Province: Andalucía (Cities: Cádiz, Huelva, Sevilla, Córdoba):
- Full time farmers
- Growing sunflowers and cereals as main income source
- Open minded: they are open to introduce new varieties, they adopt new technologies in a fast way, but it's still a crop where there is a low input of technology available.
- High input spending (background info: this crop is of low investment, they don't do irrigation, only a cheap herbicide and some fertilizers, so it's not a crop where nowadays they invest more, unless you give more productive seeds.)
- Need to identify benchmark farms that have similar size but use local practices. (i.e. Planting date later )
- Early adopters of new technologies
- Benchmark grower can use HTC seeds. This is only 5% of the market, so only 5% use this and 95% use non HTC seeds, due to more productivity. Our variety will bring HTC tolerace + productivity, so farmer will get a reduction on costs + increase in yield, to increase gains.

Mode of data collection
---------------------------

Face-to-face [f2f]

Research instrument
---------------------------

Data collection tool for 2019 covered the following information:

(A) PRE- HARVEST INFORMATION

PART I: Screening
PART II: Contact Information
PART III: Farm Characteristics
a. Biodiversity conservation
b. Soil conservation
c. Soil erosion
d. Description of growing area
e. Training on crop cultivation and safety measures
PART IV: Farming Practices - Before Harvest
a. Planting and fruit development - Field crops
b. Planting and fruit development - Tree crops
c. Planting and fruit development - Sugarcane
d. Planting and fruit development - Cauliflower
e. Seed treatment

(B) HARVEST INFORMATION

PART V: Farming Practices - After Harvest
a. Fertilizer usage
b. Crop protection products
c. Harvest timing & quality per crop - Field crops
d. Harvest timing & quality per crop - Tree crops
e. Harvest timing & quality per crop - Sugarcane
f. Harvest timing & quality per crop - Banana
g. After harvest
PART VI - Other inputs - After Harvest
a. Input costs
b. Abiotic stress
c. Irrigation

See all questionnaires in external materials tab

Cleaning operations
---------------------------

Data processing:
Kynetec uses SPSS (Statistical Package for the Social Sciences) for data entry, cleaning, analysis, and reporting. After collection, the farm data is entered into a local database, reviewed, and quality-checked by the local Kynetec agency. In the case of missing values or inconsistencies, farmers are re-contacted. In some cases, grower data is verified with local experts (e.g. retailers) to ensure data accuracy and validity. After country-level cleaning, the farm-level data is submitted to the global Kynetec headquarters for processing. In the case of missing values or inconsistences, the local Kynetec office was re-contacted to clarify and solve issues.

Quality assurance
Various consistency checks and internal controls are implemented throughout the entire data collection and reporting process in order to ensure unbiased, high quality data.

• Screening: Each grower is screened and selected by Kynetec based on cluster-specific criteria to ensure a comparable group of growers within each cluster. This helps keeping variability low.

• Evaluation of the questionnaire: The questionnaire aligns with the global objective of the project and is adapted to the local context (e.g. interviewers and growers should understand what is asked). Each year the questionnaire is evaluated based on several criteria, and updated where needed.

• Briefing of interviewers: Each year, local interviewers - familiar with the local context of farming -are thoroughly briefed to fully comprehend the questionnaire to obtain unbiased, accurate answers from respondents.

• Cross-validation of the answers:
o Kynetec captures all growers' responses through a digital data-entry tool. Various logical and consistency checks are automated in this tool (e.g. total crop size in hectares cannot be larger than farm size)
o Kynetec cross validates the answers of the growers in three different ways:
1. Within the grower (check if growers respond consistently during the interview)
2. Across years (check if growers respond consistently throughout the years)
3. Within cluster (compare a grower's responses with those of others in the group)
o All the above mentioned inconsistencies are followed up by contacting the growers and asking them to verify their answers. The data is updated after verification. All updates are tracked.

• Check and discuss evolutions and patterns: Global evolutions are calculated, discussed and reviewed on a monthly basis jointly by Kynetec and Syngenta.

• Sensitivity analysis: sensitivity analysis is conducted to evaluate the global results in terms of outliers, retention rates and overall statistical robustness. The results of the sensitivity analysis are discussed jointly by Kynetec and Syngenta.

• It is recommended that users interested in using the administrative level 1 variable in the location dataset use this variable with care and crosscheck it with the postal code variable.

Data appraisal
---------------------------

Due to the above mentioned checks, irregularities in fertilizer usage data were discovered which had to be corrected:

For data collection wave 2014, respondents were asked to give a total estimate of the fertilizer NPK-rates that were applied in the fields. From 2015 onwards, the questionnaire was redesigned to be more precise and obtain data by individual fertilizer products. The new method of measuring fertilizer inputs leads to more accurate results, but also makes a year-on-year comparison difficult. After evaluating several solutions to this problems, 2014 fertilizer usage (NPK input) was re-estimated by calculating a weighted average of fertilizer usage in the following years.

摘要
---------------------------
先正达致力于提高作物产量，并更有效地利用有限的资源，如土地、水和投入品。自2014年起，先正达在全球真实农场上对农业投入品效率的趋势进行了测量。良好增长计划数据集展示了按收获年份汇总的生产率和资源效率指标。数据来自超过4,000个农场，覆盖了46个国家中的20多种作物。数据（除美国数据和英国、德国、波兰、捷克共和国、法国和西班牙的大麦数据外）由独立的市场研究机构Kynetec（原Market Probe）收集、整合和报告。这些数据可用作作物产量和投入效率的基准。
地理覆盖范围
---------------------------
全国覆盖范围
分析单元
---------------------------
农业经营
数据类型
---------------------------
样本调查数据 [ssd]
抽样程序
---------------------------
A. 样本设计
农场被分组成簇，这些簇代表了在具有同质农业生态条件的区域内种植的作物，并包括可比类型的农场。样本包括参考和基准农场。参考农场由先正达选定，基准农场由Kynetec在同一簇内随机选定。
B. 样本量
每个簇的样本量是根据衡量随时间推移作物效率统计显著增加的目标来确定的。这是基于Kynetec对目标生产率增加和每个簇中农场指标变异性假设进行的。预期增加越小，所需的样本量就越大，以便在时间上测量显著差异。簇内的变异性基于公开研究和专家意见假设。
此外，种植者也被分组成簇，作为控制方差的一种手段，以及根据作物规模、地区和技术水平区分种植者的手段。每个簇至少需要20个访谈。参考农场的最低数量为5个中的20个。参考农场的最佳数量为20个中的10个（平衡样本）。
C. 选择程序
受访者是通过“配额随机抽样”程序随机挑选的。首先随机选择种植者，然后检查他们是否符合作物、地区、农场规模等配额。为了避免在单一抽样点集中过多的访谈，访谈员被指示在一个村庄中进行最多5次访谈。
BF Screened from Spain were selected based on the following criterion:
(a)胡椒种植者（阿尔梅里亚省）
- 被动温室
- 集成生产者或合作社的一部分
- 出口导向
- 生产品种'Melchor'
-> 集成生产者：那些整合作物生产和出口的企业。他们拥有土地，并购买外部生产以满足市场需求。这与合作社不同，因为合作社仅购买与他们相关的小农户的生产，他们不拥有土地，他们是销售农民生产的中间商。
-> 专业人士，以市场为导向，与食品链直接联系（这意味着合作社或集成生产者直接向欧洲的超市或贸易商销售）- 创新者（早期采用者）
- 向合作社销售生产，种植者获得技术支持、品种、建议（来自合作社）。
(b)番茄种植者（阿尔梅里亚省）
- 被动温室
- 集成生产者或合作社的一部分
- 出口导向
- 生产品种'Caniles'
-> 集成生产者：那些整合作物生产和出口的企业。他们拥有土地，并购买外部生产以满足市场需求。这与合作社不同，因为合作社仅购买与他们相关的小农户的生产，他们不拥有土地，他们是销售农民生产的中间商。
-> 专业人士，以市场为导向，与食品链直接联系（这意味着合作社或集成生产者直接向欧洲的超市或贸易商销售）- 创新者（早期采用者）
- 向合作社销售生产，种植者获得技术支持、品种、建议（来自合作社）。
(c)中等/大型种植者（安达卢西亚省：加的斯、赫罗纳、塞维利亚、科尔多瓦市）
- 全职农民
- 以向日葵和谷物为主要收入来源
- 开放式思维：他们愿意引入新品种，快速采用新技术，但该作物仍然是技术投入较低的一种。
- 高投入支出（背景信息：这种作物投资较低，他们不进行灌溉，仅使用廉价的除草剂和一些肥料，因此这不是一个现在投资更多的作物，除非你提供更富有生产力的种子。）
- 需要确定具有相似规模但使用当地实践的基准农场。（例如，种植日期较晚）
- 新技术的早期采用者
- 基准种植者可以使用HTC种子。这仅占市场的5%，因此只有5%使用它，95%使用非HTC种子，因为更富有生产力。我们的品种将带来HTC耐受性+生产力，因此农民将获得成本降低+产量增加，以增加收益。
数据收集方式
---------------------------
面对面 [f2f]
研究工具
---------------------------
2019年的数据收集工具涵盖了以下信息：
(A) 采收前信息
第一部分：筛选
第二部分：联系信息
第三部分：农场特征
a. 生物多样性保护
b. 土壤保护
c. 土壤侵蚀
d. 种植区域描述
e. 作物栽培和安全措施培训
第四部分：采收前耕作实践
a. 播种和果实发育 - 田地作物
b. 播种和果实发育 - 树木作物
c. 播种和果实发育 - 甘蔗
d. 播种和果实发育 - 花菜
e. 种子处理
(B) 采收信息
第五部分：采收后耕作实践
a. 肥料使用
b. 作物保护产品
c. 每种作物的采收时间和质量 - 田地作物
d. 每种作物的采收时间和质量 - 树木作物
e. 每种作物的采收时间和质量 - 甘蔗
f. 每种作物的采收时间和质量 - 香蕉
g. 采收后
第六部分 - 采收后其他投入
a. 投入成本
b. 非生物胁迫
c. 灌溉

查看所有问卷在外部材料选项卡中
数据清洗操作
---------------------------
数据处理：
Kynetec使用SPSS（社会科学统计软件包）进行数据录入、清洗、分析和报告。收集后，农场数据被输入到本地数据库中，由本地Kynetec机构进行审查和质量检查。在出现缺失值或不一致的情况下，将重新联系农民。在某些情况下，种植者数据将与当地专家（例如零售商）进行核实，以确保数据准确性和有效性。在国家层面清洗后，农场级数据被提交到全球Kynetec总部进行处理。在出现缺失值或不一致的情况下，将重新联系本地Kynetec办公室以澄清和解决问题。
质量保证
在整个数据收集和报告过程中，实施了各种一致性检查和内部控制，以确保数据无偏见、高质量。
• 筛选：每个种植者都是根据簇特定标准由Kynetec筛选和选定的，以确保每个簇内种植者群体的可比性。这有助于保持变异性低。
• 问卷评估：问卷与项目的全球目标一致，并根据当地环境（例如，访谈员和种植者应理解所提出的问题）进行调整。每年根据几个标准评估问卷，并在必要时进行更新。
• 访谈员简报：每年，熟悉当地农业环境的当地访谈员将接受彻底的简报，以便充分理解问卷，从受访者那里获得无偏见、准确的答案。
• 答案交叉验证：
o Kynetec通过数字数据录入工具捕获所有种植者的回答。在此工具中自动执行各种逻辑和一致性检查（例如，公顷总数不能大于农场规模）
o Kynetec以三种不同的方式交叉验证种植者的答案：
1. 种植者内部（检查种植者在访谈期间是否一致地回答）
2. 横跨年份（检查种植者在整个年份中是否一致地回答）
3. 簇内（将种植者的回答与组内其他人的回答进行比较）
o 所有上述不一致之处都通过联系种植者并要求他们核实其答案来跟进。在核实后更新数据。所有更新都得到跟踪。
• 检查和讨论演变和模式：Kynetec和先正达每月共同计算、讨论和审查全球演变。
• 敏感性分析：进行敏感性分析以评估全球结果，包括异常值、保留率和整体统计稳健性。敏感性分析的结果由Kynetec和先正达共同讨论。
• 建议对有兴趣使用位置数据集中的行政级别1变量（如邮政编码变量）的用户，应谨慎使用此变量，并与邮政编码变量进行交叉检查。
数据评估
---------------------------
由于上述检查，发现了肥料使用数据中的不规则性，必须对其进行纠正：
对于2014年的数据收集波次，受访者被要求提供在田间应用的肥料NPK率的总体估计。从2015年开始，问卷被重新设计，以更加精确，并通过单个肥料产品获取数据。测量肥料投入的新方法导致结果更准确，但也使得年与年之间的比较变得困难。在评估了多种解决方案后，通过计算以下年份的肥料使用加权平均值，重新估计了2014年的肥料使用（NPK输入）。