FEED THE FUTURE NIGERIA AND NESTLÉ MAIZE QUALITY ...

[Activity Name] Activity M&E Plan [Approved or draft with date] 1

FEED THE FUTURE NIGERIA AND NESTLÉ MAIZE QUALITY IMPROVEMENT

PARTNERSHIP MONITORING,

EVALUATION, and LEARNING (MEL) PLAN

Approved Date: January 23, 2018

Version: 3 Approved September 30, 2019

Version: 3 Submitted September 11, 2019

Agreement Number: AID-620-LA-17-00002

Activity Start Date and End Date: 6/8/2017-6/5/2020

Total Award Amount: $1,318,000

AOR Name: Olagoke Akinlabi

Submitted by: Chris Hert, Program Officer CNFA

1828 L Street, NW Washington, DC 20036

Feed the Future Nigeria and Nestlé Maize Quality Improvement

Partnership

MONITORING,

EVALUATION & LEARNING (MEL) PLAN

DRAFT VERSION OF SEPTEMBER 2019 Contracted under AID-620-LA-17-00002

Feed the Future Nigeria and Nestlé Maize Quality Improvement Partnership

DISCLAIMER

The author’s views expressed in this publication do not necessarily reflect the views of the United States Agency

for International Development or the United States Government.

Feed the Future Nigeria and Nestlé Maize Quality Improvement Partnership Monitoring, Evaluation and Learning (MEL) Plan Draft Submitted October 29, 2018 1

ACRONYMS

ABU Ahmadu Bello University

DQA Data Quality Assessment

EA Extension Agent

MEL Monitoring, Evaluation, and Learning

MT Metric Ton

PIRS Performance Indicator Reference Sheet

USG United States Government


TABLE OF CONTENTS

1. INTRODUCTION TO THE FEED THE FUTURE NIGERIA AND NESTLÉ MAIZE QUALITY IMPROVEMENT PARTNERSHIP MONITORING, EVALUATION AND LEARNING PLAN .........................................................................................................................3

PURPOSE ..........................................................................................................................3

ACTIVITY INFORMATION AND CONTEXT ....................................................................4

ACTIVITY LOCATION AND INSTITUTIONAL CONTEXT .................................................... 4

ACTIVITY LOGICAL FRAMEWORK ................................................................................................... 1

2. THE FEED THE FUTURE NIGERIA AND NESTLÉ MAIZE QUALITY IMPROVEMENT PARTNERSHIP MEL PLAN.............................................................................................................4

PERFORMANCE MONITORING SYSTEM AND APPROACHES.........................................4

PERFORMANCE INDICATORS ............................................................................................................. 4

INDICATOR BASELINES AND TARGETS......................................................................................... 5

DATA QUALITY ASSURANCE AND DATA QUALITY ASSESSMENT (DQA) PROCEDURES ............................................................................................................................... 5

REPORTING OF INDICATOR DATA................................................................................................. 6

ROLES AND RESPONSIBILITIES ............................................................................................................ 6

COLLABORATION, LEARNING, AND ADAPTING APPROACHES .................................... 7

DATA COLLECTION METHODOLOGIES ........................................................................7

GENDER AND OTHER VULNERABLE GROUPS M&E SECTION .......................................8

EVALUATION, ASSESSMENT, SPECIAL STUDY AND OTHER LEARNING QUESTIONS .....................................................................................................................8

CALENDAR OF MEL EVENTS ...........................................................................................8

RESOURCES REQUIRED FOR MEL PLAN IMPLEMENTATION............................................... 9

3. PERFORMANCE INDICATOR TRACKING TABLE.................. Error! Bookmark not defined.

4. ACTIVITY PERFORMANCE INDICATORS REFERENCE SHEETS ............................................9

ANNEX B: DATA COLLECTION TOOLS ...................................................................................34


1. INTRODUCTION TO THE FEED THE FUTURE NIGERIA AND NESTLÉ MAIZE QUALITY IMPROVEMENT

PARTNERSHIP MONITORING, EVALUATION AND

LEARNING PLAN

Purpose

This Monitoring, Evaluation, and Learning (MEL) plan describes the results framework including

the goal and intermediate results that are expected to be achieved through the planned Activity activities, as well as the performance indicators that will be used to measure progress towards

achieving these results. The Logical Framework presents the hierarchy of results of the Feed the Future Nigeria and Nestlé Maize Quality Improvement Partnership Activity, and identifies the

indicators that will be used to track each identified result as well as the plan for data collection for each indicator. A gender-focused indicator is included to measure the participation of women.

In addition, indicators that track individuals will be disaggregated by sex and age to provide further

information on participation of these groups in Activity activities. The Performance Data Table includes the quantitative Life of Activity targets. Performance Indicator Reference Sheets are

included in Section 4.

The main purpose of the MEL plan is to describe the processes by which CNFA will know whether the Feed the Future Nigeria and Nestlé Maize Quality Improvement Partnership activity

is progressing towards achieving of the expected results.

As a management tool, MEL plan describes the performance indicators and process for

monitoring (data collection) to generate the performance data needed to inform and guide management decisions. The selected indicators provide means to measure results and enable

analysis of why targets are or are not achieved. Monitoring data (indicator results) will be used by Activity managers to adaptively manage the Activity, identifying what works and what doesn’t

towards achieving the Activity goal. The monitoring system will generate information about best practices and lessons learned, which will be shared with stakeholders to contribute to wider

learning.

The MEL plan includes the logical framework, which describes the interrelationship of intended

results and the indicators to measure each result; a performance data table, which outlines the indicators and sets targets for each year of the Activity; and the performance indicator reference

sheets for each indicator, which contain the methods of data collection (verification) to be implemented throughout the program.

CNFA will work with its partners, home office support, short-term consultants, and Activity staff

to regularly collect accurate data from relevant sources, reports, and surveys to verify results.


Activity Information and Context

The Feed the Future Nigeria and Nestlé Maize Quality Improvement Partnership between USAID/Nigeria and Nestlé Nigeria, PLC aims to enhance quality, safety, and transparency in Nigeria’s grain supply chain through a whole-of-supply-chain approach, implemented by CNFA.

The project works with multiple stakeholders, including smallholder farmers, input suppliers, grain aggregators, Nestlé, and local governments to improve the quality and quantity of maize and soybeans in the Kaduna State by decreasing levels of aflatoxins, fumonisins, and aluminum. This is done through a comprehensive mapping exercise that identifies areas of high levels of contaminants followed by training and support at each level of the supply chain to reduce levels of contamination to meet high quality standards such as those required by Nestlé. Trainings manuals have been developed by program partner, Purdue University. Over the life of the project, a total of 20,000 beneficiaries will be trained by project staff and local volunteers in effective mitigation measures to reduce the levels of key contaminants in maize and soybeans, increasing the available supply of safe, high quality maize and soybeans.

Activity Location and Institutional Context

The activity is implemented in two agro-ecological zones of the Kaduna State of Nigeria. There are 11 Local Government Areas (LGAs) in these zones: Soba, Makarifi, Zaria, Kudan, Kubau, Sabon Gari, Giwa, Ikara in the Maigana Zone; and Lere, Kauru, and Igabi in the Lere Zone. The project currently works in Soba, Makarifi, Zaria, Kudan, and Sabon Gari in Maigana and Lere, Kaura, Igabi in the Lere Zone. In Year 2, the project will scale up into all 11 LGA. The project works closely with the local agricultural minstiries, who provide extension agents who provide training and oversight of project activites to each level of the value chains. These agents are managed by project staff.


Activity Logical Framework

USAID/Nigeria IR 1.1: Agricultural Competitiveness Increased

USAID/Nigeria Sub

IR

Narrative

Summary Indicators Means of Verification

(Data Source & Methodology)

Assumptions

IR 1.1.2: Market Participation Increased

Goal: Increase volume of high-

quality maize and soybean

produced in Kaduna state.

1. EG 3-2 Number of individuals participating in

USG food security programs

-Review of program records; training registers

with beneficiary information collected

monthly and M&E team conducts spot checks to

verify accuracy of data

-Stable political environment -Stable security situations that

allows free movement

2. GNDR-2 Percentage of

female participants in USG-assisted programs designed

to increase access to productive economic

resources (assets, credit,

income or employment)

-Review of program

records; training registers with beneficiary

information collected monthly and M&E team

conducts spot checks to

verify accuracy of data

-Stable security situations that

allows free movement -Stable political environment

-Favorable government policies related to gender and agriculture

are sustained

3. Volume of sales of high quality maize and soybean

grain delivered to Nestlé with USG assistance (MT)

(custom)

-Nestlé purchase records. Senior Technical Advisor

reviews records to determine volume of

purchases from local

market. Value will also be tracked.

-No advent of natural disaster within the farming season

-Weather conditions to remain within the range needed for

production of maize and soybeans

4. Rate of rejection of maize

and soybean grain sourced by Nestlé in Kaduna State

-Nestlé purchase records

and testing analysis records. Senior Technical

Advisor reviews records to

determine volume of

-No advent of natural disaster

within the farming season -Weather conditions to remain

within the range needed for

production of maize and soybeans


purchases from local

market.

IR 1.1.1: Agricultural

Productivity Increased

5. Percentage of maize and

soybean grains at farm level that meet minimum Nestlé

quality requirements (custom)

-Farm level testing during

harvest (October-January) using mobile testing devices

-Sampling of farmers across each Activity LGA

-No advent of natural disaster

within the farming season -Weather conditions to remain

within the range needed for production of maize and soybeans

-Farmers allow testing of their

grains

IR1: Increased use of

technology and practices that

reduce

contaminants in the maize and

soybean value chain

6. EG3.2-24 Number of individuals in the agriculture

system who have applied improved management

practices or technologies

with USG assistance [IM-Level]

-Direct beneficiaries (farmers and aggregators)

-Sample survey of direct beneficiary farmers

(beneficiary based survey,

farmer groups approach)

-Stable political environment that guarantees international

partnerships -Stable security situations that

allows free movement

7. EG.3.2-25 Number of

hectares under improved management practices or

technologies with USG

assistance

-Sample survey of direct

beneficiary farmers (beneficiary based survey,

farmer groups approach)

-Stable political environment that

guarantees international partnerships

IR 1.1.2: Market Participation Increased

8. Number of people reached by mass media

awareness campaign on contaminated grains

(custom)

-Radio coverage estimates (for radio campaigns)

-Attendance records (for events)

-Stability in information dissemination policies within the

country -Stable security situation in the

country

9. YOUTH-3: Percentage of

participants in USG-assisted programs designed to

-Review of program

records

-Stable security situations that

allows free movement -Stable political environment


increase access to

productive economic resources who are youth

(15-29).

-Favorable government policies

related to gender and agriculture are sustained


2. THE FEED THE FUTURE NIGERIA AND NESTLÉ MAIZE

QUALITY IMPROVEMENT PARTNERSHIP MEL PLAN

Performance Monitoring System and Approaches

Performance Indicators

Indicators have been selected to measure the intended results as illustrated in the Logical

Framework. They are selected to serve two main purposes: (I) to accurately measure impact on the direct beneficiaries of the activity, and (2) provide evidence to effectively guide Activity

management in making timely and informed decisions and adjustments to implementation strategy. Important criteria guiding the selection process are that indicators must be:

• Direct: a direct measure of the intended result and directly attributable to activity

interventions;

• Objective: a transparent and standard measure of the intended result;

• Quantitative: easily represented and conveyed in numerical terms;

• Practical: collected and analyzed timely and accurately, yet cost effectively; and

• Reliable: consistently high quality based on reliable sources and sound data collection

techniques.

Indicators

1. EG 3-2 Number of individuals participating in USG food security programs

2. GNDR-2 Percentage of female participants in USG-assisted programs designed to increase access to productive economic resources (assets, credit, income or employment)

3. Volume of sales of high quality maize and soybean grain delivered to Nestlé with USG assistance

(MT) (custom)

4. Rate of rejection of maize and soybean grain sourced by Nestlé in Kaduna State

5. Percentage of maize and soybean grains at farm level that meet minimum Nestlé quality

requirements (custom)

6. EG3.2-24 Number of individuals in the agriculture system who have applied improved management practices or technologies with USG assistance [IM-Level]

7. EG.3.2-25 Number of hectares under improved management practices or technologies with USG assistance

8. Number of people reached by mass media awareness campaign on contaminated grains (custom)

9. YOUTH-3: Percentage of participants in USG-assisted programs designed to increase access to productive economic resources who are youth (15-29).


Indicator Baselines and Targets

Targets will be reviewed on an annual basis and revised as needed with approval from Nestle

and USAID.

For all indicators except 3-5, all baselines were 0. This is due to the fact that all of these indicators

were related to quantitative, project-supported activities (number of households receiving assistance, number of hectares under improved management practices, etc.). As the results for

these indicators are reliant on project activities to provide measure, no results can be reported

prior to the start of project activities and are 0.

The remaining three indicators are:

-3. Volume of sales of high quality maize and soybean grain delivered to Nestle with USG

assistance (MT) -4. Rate of rejection of maize and soybean grain sourced by Nestle in Kaduna State

-5. Percentage of maize and soybean grains at farm level that meet minimum Nestlé quality requirements

Indicator 3 measures the volume of maize and soybeans that meet the highest quality threshold for targeted contaminant levels, while indicator 4 measures what percentage of grains tested by

Nestle pass the contaminant threshold levels set forth in the performance indicator reference

sheets (PIRS). Both indicators are calculated using sales and testing data provided by Nestle.

For indicator 5, this indicator was added at USAID’s request in year 2 to assess whether project

activities result in reduced contaminant levels at the farm level. To establish a baseline for this indicator, testing will be done on a sample of farmer grains during the harvest season (October-

January) to determine what percentage of grain meets the necessary quality thresholds. Since this indicator was only added in year 2, the results for this indicator for year 2 will also be the baseline

value.

Data Quality Assurance and Data Quality Assessment (DQA) Procedures

The implementation of most project trainings and data collection is done by the extenstion agents (EAs) and volunteers. They record the number of trainings given each week on a training

register and have trainees sign to confirm their attendance. These registers are shared with the Training and Volunteer Coordinators who, together with the zonal based Project Assistants,

conduct beneficiary visits at least twice a week to provide oversight and confirm the accuracy of the data submitted by the EAs and volunteers. The registers are added to a beneficiary

tracking database to ensure no double counting of beneficiaries takes place. Beneficiaries who

appear on the registers are randomly selected and visited by the Coordinators to confirm their participation in the trainings. The M&E Officer also conducts field visits to beneficiaries at least

twice a month to verify training results.


During the end of each quarter, a beneficiary spot check is done by the M&E team to verify the accuracy of the information collected in the training registers, which include the adoption of

targeted practices. A random selection of beneficiaries in interviewed by the M&E team. During the interview, the M&E team confirms that those selected beneficiaries did receive the trainings

included in the registers and they do engage in the improved technologies and practices

promoted by the project that are relevant to indicators 6 and 7.

Reporting of Indicator Data

The activity will include an indicator progress table in each quarterly report to be submitted 30

days after the end of the corresponding quarter. Indicators which are collected annually will be

included in the fourth quarter/annual report submitted October 30 th.

All reports will be submitted to the Agreement Officer’s Representative and Nestlé

representatives for review and comment before being approved per the terms of the award agreement. Each quarterly report will also include a narrative on the progress towards yearly

targets and a summary of results to date. The fourth quarter report will include a narrative summary of the activities for the year as well as progress towards yearly targets and an

explanation for any targets that were not reached.

The indicator results and any changes to targets will be uploaded into the Feed the Future Monitoring System each year per the schedule set forth by USAID. Along with the indicator

results, deviation narratives will be included for any result that varied more than 10% from the

yearly target.

Roles and Responsibilities

The core-identified participants of the activity MEL Team are the Team Leader, Senior Technical

Advisor, M&E Officer, and the Training Coordinators. CNFA headquarters will provide support as needed through the Program Officer. The MEL team will be responsible for the implementation

of the MEL plan with oversight from USAID and Nestlé.

Table 1: Tasks and Responsibilities

Task Responsibility

Collect performance data Activity and actors in the value chain

Review performance information Team Leader & MEL Team

Assess data quality MEL Team

Report performance results Team Leader & MEL Team


Review and update the M&E plan MEL Team

Collaboration, Learning, and Adapting Approaches

The activity regularly meets with other implmenters within the project area, including the Aflasafe Technology Transfer and Commericialization project implemented by the International Instititue for Tropical Agriculture. The activity collaborates together to share lessons learned on reducing aflatoxin in corn and soy as well as sharing links with suppliers of high quality inputs that can reduce contamination.

The activity also conducts a quarterly review of project activities to ascertain the effectiveness of activities, including a review of the quarterly results and collecting feedback from volunteers and staff on what did and did not work. Where necessary, activities are adapted to be more effective.

Data Collection Methodologies

Primary data sources include both studies and routine monitoring from the activity. Studies

include the activity baseline data from Nestlé and other technical studies. Regular monitoring and evaluation reporting, technical reporting from the activity volunteer coordinators and youth

volunteers, the final evaluation, and other data collected from aggregators and Nestlé are other data sources that will be used.

Data is collected in the training registers for each training conducted by project staff and

volunteers. These registers include beneficiary information as well as which targeted behaviors that they adopt. They are collected by the Training Coordinators on a monthly basis and receive

quarterly spot checks for accuracy by the M&E team.

Additional data sources that the activity can utilize in the M&E process throughout the activity

life time include:

• Secondary information review: secondary data information always provides crucial

information needed for the development of the MEL plan, and gives indication about the

historical data that will be used as reference or baseline for measuring the progress

toward achieving Activity targets. These data sources include but are not limited to the

following:

o Institute for Agricultural Research – Ahmadu Bello University (ABU), Zaria

o Nestlé

o Other funded Activity studies and reports

o Kaduna State Agricultural Development Program

o Database for cooperatives

o International Institute for Tropical Agriculture

o Former USAID Activity’s documents


o National Agricultural Extension and Research Liaison Services ABU, Zaria

• Participatory Qualitative Assessments: the activity will use qualitative techniques to obtain

information that involves the participation of local stakeholders in the process.

Information obtained through participatory qualitative assessments provides important

information/data for the Activity M&E system. Participatory Qualitative Assessments use

the following basic techniques: observation, in-depth interviews, focus discussions, and

visual techniques (Networks mapping).

Gender and Other Vulnerable Groups M&E Section

All beneficiaries registered under the project include gender identification. Including women in activities is key approach as the activity is required to have at least 40% of the beneficiaries be

women. Where possible, female farmer groups and other value chain actors will be identified and trained to ensure a high level of female participation. Trainings for these groups will be

tailored to ensure a gender sensitive approach and incorporate time-saving activities to ensure

women’s workload does not increase.

In year 2 of the project a new indicator was added to measure the level of youth participation

in project activities. While no data was collected in year 1 of the project on beneficiary age, a

survey will be conducted during the first two quarters of FY19 to establish the current level of youth participation. Once this is established, targets will be set for this indicator to ensure that

youth are included in activities.

Evaluation, Assessment, Special Study and Other Learning Questions

A value chain study to determine how maize and soy moves along the value chain from farmers to the final buyer was conducted in year 1 of the activity, which was used to inform changes in

the targeting of beneficiaries and trainings to ensure each level of the value chain is trained to

mitigate the targeted contaminants. This study was shared with USAID and Nestle in year 1.

Per the terms of the award, a final evaluation will be conducted in year 3 to assess the activity’s

impact and establish final results for each activity, as well as lessons learned and best practices.

This will be submitted within 90 days of the activites end.

At this time, no further evaluations, assessment, or special studies are planned for the activity.

Calendar of MEL Events

Table 1. Calendar of MEL Events

Event Date/Duration Comments


Preparation for quarterly beneficiary assessment

Last week of the last month of each quarter

This is when beneficiaries are selected to be surveyed as part of the approved sampling methodology and which improved technologies and practices (use of tarps for drying/threshing, storing grain on pallets in warehouses, etc.) are selected to count towards related indicators.

Quarterly beneficiary assessment

First week of the first month of the new quarter for previous quarter (i.e. for Oct-Dec quarter assessment, the assessment is done the first week of January)

Data from beneficiary assessment collated and cleaned

First Monday of the second week of the first month of the new quarter for the previous quarter

Quarterly data review meeting The 14th, 15th, or 16th of the first month of the new quarter for the previous quarter

Submission of quarterly report with indicator results

30 days after the end of the quarter

Supervisory field visits by project zonal staff to extension agents and volunteers to monitor activities

Twice a week

Supervisory field visits by M&E Officer and other project management staff to monitor activities

Twice a month

Resources Required for MEL Plan Implementation

As noted above, the MEL team will be responsible for the collection and reporting of all project results.

Along with the fully dedicated M&E Officer, the rest of the project team based both in Nigeria and at the CNFA headquarters will provide the necessary support to ensure that all data is reported in line with the methodologies laid out in the PIRS.ACTIVITY PERFORMANCE IndicatorS Reference Sheets


USAID Performance Indicator Reference Sheet 1

Name of Indicator: EG.3.2 Number of individuals participating in USG food security

programs [IM-level]

Name of Result Measured (DO, IR, sub-IR, Activity Purpose, Activity Outcome, Activity Output, etc.):

Goal: Increase volume of high-quality maize and soybean produced in Kaduna state.

Is This a Performance Plan and Report Indicator? No Yes X for Reporting

Year(s) 2019-2020

If yes, link to foreign assistance framework:

DESCRIPTION Precise Definition(s):

This indicator is designed to capture the breadth of our food security work. This indicator counts participants of Feed the Future-funded programs, including those we

reach directly, those reached as part of a deliberate service strategy, and those participating in the markets we strengthen. We expect Implementing Partners (IPs) to track or estimate the number of individual participants across different interventions within their own Activity and to report numbers of participants reached, not number of

contacts with the Activity or Activity-supported actors.

This indicator counts, with some exceptions listed below, all the individuals participating in our nutrition, resilience, and agriculture and food system activities, including: • Adults that Activitys or Activity-supported actors reach directly through nutrition-specific and community-level nutrition interventions, (e.g. parents and other caregivers participating in community care groups, healthcare workers provided with in-service training on how to manage acute malnutrition), but not children reached with nutrition-specific or community-based interventions, who are counted under indicators HL.9-1 and HL.9-2 instead;

• People reached by productive safety nets, community-based micro-finance and diversified livelihood activities through our assistance; • Members of households reached with household-level interventions (households with new access to basic sanitation through our work, households receiving family-sized rations); • Smallholder and non-smallholder producers that Activitys or Activity-supported actors reach directly (e.g. through an irrigation training, through a loan provided, through

distribution of drought-tolerant seeds to specific farmers); • Proprietors of firms in the private sector that we help strengthen (e.g. agrodealers, aggregators, processors), but not all the employees of those firms; • Producers who directly interact with those USG-assisted firms (e.g. the producers who are customers of an assisted agrodealer; the producers from whom an assisted trader or aggregator buys), but not customers or suppliers who are not producers;

• Participants whose main source of income is labor (e.g. Laborers/non-producer diversified livelihood participants); • People in civil society organizations and government whose skills and capacity have been strengthened by Activitys or Activity-supported actors; • School-aged children who are recipients of USG school feeding programs; In cases where activities work with multiple individuals in a household, this indicator counts all activity participants in t he household, not all members of the household.

However, in the case of sanitation services and family-sized rations, all members of the household receiving the sanitation facility or ration can be counted here.

An individual is a participant if s/he comes into direct contact with the set of interventions (goods or services) provided or facilitated by the activity. The intervention needs to be significant, meaning that if the individual is merely contacted or touched by an activity through brief attendance at a meeting or gathering, s/he should not be counted

as a participant. An intervention is significant if one can reasonably expect, and hold OUs and IMs responsible for achieving progress toward, changes in behaviors or other outcomes for these individuals based on the level of services and/or goods provided or accessed. Producers with increased access to goods, services and markets for their products and who purchase from or sell to market actors that have been strengthened as a result of our activities are considered to have received a significant

intervention.

Individuals who are trained by an IM as part of a deliberate service delivery strategy (e.g. cascade training) that then go on to deliver services directly to individuals or to train others to deliver services should be counted as participants of the activity—the capacity strengthening is key for sustainability and an important outcome in its own right. The individuals who then receive the services or training delivered by those individuals are also considered participants. However, spontaneous spillover of

improved practices to neighbors does not count as a deliberate service delivery strategy; neighbors who apply new practices based on observation and/or interactions

with participants who have not been trained to spread knowledge to others as part of a deliberate service delivery strategy should not be counted under this indicator.

Value chain facilitative and/or market-system activities may use a two-step process to identify and count participants:

1. The first step involves identifying which private sector firms have been assisted by the activity during the reporting year, and counting the number of proprietors of those firms. 2. The second step, which is only applicable to firms that buy from or sell to producers, is to count the number of producer customers or suppliers of each assisted firm.


The total number of participants for that activity is then the sum of the proprietors of the assisted firms and their producer customers/suppliers. For example, an IP working to strengthen the certified soy seed market within a defined market shed in the ZOI could use data on the number of certified soy seed sales by assisted firms during the reporting year to estimate the number of farmers purchasing certified soy seed (by using a conservative assumption that one sales equals one farmer applying), and then report that number as the number of producer participants. All assumptions underlying the indicator estimates should be documented annually in an Indicator Comment in

FTFMS. Data provision by assisted firms can be facilitated by entering into written agreements that include reporting and nondisclosure requirements and by showing assisted firms how the information provided is useful and used. Counting producer participants may be more straightforward if the value chain activity is also facilitating extension strategies, e.g. agrodealer agents that require knowing where the customers live and farm. While other Feed the Future indicators, such as "financing accessed", "value of sales," and "individuals applying improved practices" also capture the number of enterprises that contributed results to the indicator, this indicator only counts individual people, i.e. the farmer (not the farm), and the proprietor (not the firm). This indicator does not count the indirect beneficiaries of our activities. An

indirect beneficiary is someone who does not have direct contact with the activity but still benefits, such as the population that uses a new road constructed by the activity, neighbors who see the results of the improved technologies applied by direct participants and dec ide to apply the technology themselves (spillover), or the individuals who hear an activity-supported radio message but don’t receive any training or counseling from the activity. In part, this is because accurate tracking of indirect beneficiaries is challenging by its nature, despite the fact that spillover is a core component of the Feed the Future theory of change. In general, spillover is captured in Feed the Future

through measuring changes in population level indicators (e.g. proportion applying improved technologies and management practices) and linking those to the work

activities are doing directly.

Note that this indicator cannot be summed across years for a Activity total, since “new” and “continuing” participants are no t disaggregated, and thus this will only show a

total of individuals reached in any one reporting year.

Unit of Measure: Number. Result is cumulative.

Data Type: Integer


Disaggregated by:

Duration: New, Continuing

FIRST LEVEL

• Sex: the unique number of individuals should be entered here (i.e. no double-counting of individuals across disaggregate choices here)

• Male; Female; Not applicable (e.g. for household members counted from household -level interventions); • Disaggregates Not Available

•Age Category: the unique number of individuals should be entered here (i.e. no double -counting of individuals across disaggregate choices here)

• School-aged children (only to be used for counting those reached by USG school feeding programs; report the total reached with school feeding regardless of actual age); 15-29; 30+; • Not applicable (e.g. for household members counted from household-level interventions); Disaggregates Not Available Note: Children under five reached with nutrition interventions are counted under HL.9-1

•Type of Individual: double-counting individuals across types is permitted here

• Parents/caregivers; Household members (household-level interventions only), such as new access to basic sanitation and/or receipt of family rations; School-aged children (i.e. those participating in school feeding programs); People in government (e.g. policy makers, extension workers, healthcare workers); Proprietors of USG-assisted private sector firms (e.g. agrodealers, traders, aggregators, processors, service providers, manufacturers); People in civil society (e.g. NGOs, CBOs, CSOs, research and academic organizations, community volunteers) While private sector firms are considered part of civil society more broadly, only count their proprietors under the "Private Sector Firms" disaggregate and not the "Civil Society" disaggregate; Laborers (Non-producer diversified livelihoods participants); Producers (e.g. farmers, fishers, pastoralists, ranchers); Producers should be counted under the "Producers" disaggregate, not the "Private Sector Firms" disaggregate

SECOND LEVEL (only for the first-level disaggregate of “Producers”) o

Size: Smallholder (see definition below); Non-smallholder; Not applicable (for aquaculture); Disaggregates Not Available

Smallholder Definition: While country-specific definitions may vary, use the Feed the Future definition of a smallholder producer, which is one who holds 5 hectares or less of arable land or equivalent units of livestock, i.e. cattle: 10 beef cows; dairy: two milking cows; sheep and goats: five adult ewes/does; camel meat and milk: five camel cows; pigs: two adult sows; chickens: 20 layers and 50 broilers. The farmer does not have to own the land or livestock; Not Applicable; Disaggregates Not Available


Rationale for Indicator (optional): Understanding the reach of our work and the breakdown of the individuals participating by type, sex, and age will better inform our programming and the impacts we are having in various sectors or in various demographic groups. This understanding can then make us more effective or efficient in reaching our targeted groups. Understanding the extent of spillover and scale is also very important, but this will be assessed as a part of the ZOI survey and performance and impact evaluations rather than through annually reported IM-level indicators. This indicator is an output indicator and is linked to many parts of the Global Food Security Strategy results framework.

PLAN FOR DATA COLLECTION

Data Source: Activity interventions records. Training registers.

Method of Data Collection and Construction: Review of Activity records. Training registers are collected from volunteer trainers by the Training and Volunteer Coordinators

each month that record the number of people trained and the necessary data points for that beneficiary (age, gender, practices/technologies implemented, etc.). These are then shared with the M&E Officer, who reviews and aggregates them. Each quarter, a randomly selected sample of the beneficiaries from these registers (a minimum of 30%) are pulled by the MEL Team. The trainees selected are visited by the M&E team to confirm the accuracy of the data recorded in the register. The data from the total number of the beneficiaries recorded in the registers is then used develop the indicator result.

Data Analysis: As noted above, the M&E team reviews the training registers and aggregates the data into a database. Then a minimum of 30% of the beneficiaries who are included are sampled randomly and receive a visit from the M&E team to confirm the validity of their participation and behaviors/technologies implemented. The M&E team then uses the training register to confirm the data previous collected to ensure it is accurate.

Reporting Frequency: Annually

Individual(s) Responsible at USAID: AOR

TARGETS AND BASELINE

Baseline Timeframe: Baseline is 0 before the start of activity interventions.

Rationale for Targets (optional):

DATA QUALITY ISSUES

Dates of Previous Data Quality Assessments and Name of Reviewer(s):

N/A

Date of Future Data Quality Assessments (optional):

Known Data Limitations:

CHANGES TO INDICATOR

Changes to Indicator:

Other Notes (optional):

THIS SHEET LAST UPDATED ON: 10/29/2018



Name of Indicator: GNDR-2 Percentage of female participants in USG-assisted programs

designed to increase access to productive economic resources (assets, credit, income or

employment)


Goal: Increase volume of high-quality maize and soybean produced in Kaduna state.


Year(s) 2019-2020


DESCRIPTION

Precise Definition(s):

Productive economic resources include: assets - land, housing, businesses, livestock or financial assets such as savings; credit; wage or self-employment; and income. Programs include: • micro, small, and medium enterprise programs; • workforce development programs that have job placement activities; • programs that build assets such as land redistribution or titling; housing titling; agricultural programs that provide assets such as livestock; or programs designed to help adolescent females and young women set up savings

accounts. This indicator does NOT track access to services, such as business development services or stand-alone employment training (e.g., employment training that does not also include job placement following the training). The unit of measure will be a percentage expressed as a whole number. Numerator = Number of female program participants Denominator = Total number of male and female participants in the program

The resulting percentage should be expressed as a whole number. For example, if the number of females in the program (the numerator) divided by the total number of participants in the program (the denominator) yields a value of .16, the number 16 should be the reported result for this indicator. Values for this indicator can range from 0 to 100. The numerator and denominator must also be reported as disaggregates.

Unit of Measure: Percentage of participants. Result is cumulative.

Data Type: Percentage (expressed as whole number)

Disaggregated by: Numerator (Number of female program participants); Denominator (Total number of male and female participants in the program)

Rationale for Indicator (optional): The lack of access to productive economic resources is frequently

cited as a major impediment to gender equality and women’s empowerment, and is a particularly important factor in making women vulnerable to poverty. Ending extreme poverty, a goal outlined in the Sustainable Development Goals and USAID's Vision to Ending Extreme Poverty, will only be achievable if women are economically empowered.



Data Source: Activity records

Method of Data Collection and Construction: Numerator (Number of female program participants); Denominator (Total number of male and female participants in the program)

Data Analysis: The M&E team reviews the training registers (which include the gender of

the participant) and aggregates the data into a database. Then a minimum of 30% of the beneficiaries who are included are sampled randomly and receive a visit from the M&E team to confirm the validity of their participation and behaviors/technologies implemented.




Baseline Timeframe: Baseline is 0 before start of activity interventions.


DATA QUALITY ISSUES


May 2018, USAID/Nigeria



CHANGES TO INDICATO R






Name of Indicator: EG3.2-24 Number of individuals in the agriculture system who have

applied improved management practices or technologies with USG assistance [IM-Level]


IR1: Increased use of technology and practices that reduce contaminants in the maize and soybean supply chain.


Year(s) 2019-2020


DESCRIPTION

Precise Definition(s): This indicator measures the total number of agriculture system actors participating in the USG-funded activity who have applied improved management practices and/or technologies promoted by the USG anywhere within the food and agriculture system during

the reporting year. These individuals can include:

• Farmers, ranchers and other primary sector producers of food and nonfood crops, livestock and livestock products, fish and other fisheries/aquaculture products, agro-forestry products, and natural resource-based products, including non-timber forest products such

as fruits, seeds, and resins; • Individuals in the private sector, such as entrepreneurs, input suppliers, traders, processors, manufacturers, distributors , service providers, and wholesalers and retailers;

• Individuals in government, such as policy makers, extension workers and natural resource managers; • Individuals in civil society, such as researchers or academics and non-governmental and community organization staff. The indicator tracks those individuals who are changing their behavior while participating in USG-funded activities. Individuals who

attended training or were exposed to a new technology do not count under this indicator unless the individual actually applies what she/he learned. For example, if an agriculture extension agent attends a gender -sensitive agriculture extension training, he can be counted under this indicator once he applies what he learned by changing the way he reaches out to and interacts with the fem ale

farmers to whom he provides extension services. Improved management practices or technologies are those promoted by the implementing partner as a way to increase agriculture productivity or support stronger and better functioning systems. The im proved management practices and technologies are agriculture-related, including those that address climate change adaptation or climate

change mitigation. Implementing partners promoting one or a package of specific management practices and technologies report practices under categories of types of improved management practices or technologies. This indicator captures results where they

were achieved, regardless of whether interventions were carried out, and results achieved, in the ZOI.

Management practice and technology type categories, with some illustrative (not exhaustive) examples, include:

• Crop genetics: e.g. improved/certified seed that could be higher -yielding, higher in nutritional content (e.g. through bio-fortification,

such as vitamin A-rich sweet potatoes or rice, high-protein maize), and/or more resilient to climate impacts (e.g. drought tolerant maize, or stress tolerant rice); improved germplasm. • Cultural practices: context specific agronomic practices that do not fit in other categories, e.g. seedling production and

transplantation; cultivation practices such as planting density, crop rotation, and mounding. • Livestock management: e.g. improved livestock breeds; livestock health services and products such as vaccines; improved livestock handling practices and housing; improved feeding practices; improved grazing practices, improved waste management practices, improved fodder crop, cultivation of dual purpose crops. • Wild-caught fisheries management: e.g. sustainable fishing practices; improved nets, hooks, lines, traps, dredges, trawls; improved

hand gathering, netting, angling, spearfishing, and trapping practices.

cage culture; improved pond culture; pond preparation; sampling and harvesting; management of carrying capacity.


• Aquaculture management: e.g. improved fingerlings; improved feed and feeding practices; fish health and disease control; improved

cage culture; improved pond culture; pond preparation; sampling and harvesting; management of carrying capacity. • Natural resource or ecosystem management: e.g. terracing, rock lines; fire breaks; biodiversity conservation; strengthening of ecosystem services, including stream bank management or restoration or re/afforestation; woodlot management.

• Pest and disease management: e.g. Integrated Pest Management; improved fungicides; appropriate application of fungicides; improved and environmentally sustainable use of cultural, physical, biological and chemical insecticides and pesticides; crop rotation; aflatoxin prevention and control. • Soil-related fertility and conservation: e.g. Integrated Soil Fertility Management; soil management practices that increase biotic

activity and soil organic matter levels, such as soil amendments that increase fertilizer -use efficiency (e.g. soil organic matter, mulching); improved fertilizer; improved fertilizer use practices; inoculant; erosion control. • Irrigation: e.g. drip, surface, and sprinkler irrigation; irrigation schemes.

• Agriculture water management -non-irrigation-based: e.g. water harvesting; sustainable water use practices; practices that improve water quality. • Climate mitigation: technologies selected because they minimize emission intensities relative to other alternatives (while preventing

leakage of emissions elsewhere). Examples include low-or no-till practices; restoration of organic soils and degraded lands; efficient nitrogen fertilizer use; practices that promote methane reduction; agroforestry; introduction/expansion of perennials; practices that promote greater resource use efficiency (e.g. drip irrigation, upgrades of agriculture infrastructure and supply chains). • Climate adaptation/climate risk management: technologies promoted with the explicit objective of reducing risk and minimizing the

severity of the impacts of climate change. Examples include drought and flood resistant varieties; short -duration varieties; adjustment of sowing time; agricultural/climate forecasting; early warning systems; diversification, use of perennial varieties; agrofor estry; risk insurance.

• Marketing and distribution: e.g. contract farming technologies and practices; improved input purchase technologies and practices; improved commodity sale technologies and practices; improved market information system technologies and practices. • Post-harvest handling and storage: e.g. improved transportation; decay and insect control; temperature and humidity control;

improved quality control technologies and practices; sorting and grading, sanitary handling practices. • Value-added processing: e.g. improved packaging practices and materials including biodegradable packaging; food and chemical safety technologies and practices; improved preservation technologies and practices. • Other: e.g. improved mechanical and physical land preparation; non-market-and non-climate-related information technology;

improved record keeping; improved budgeting and financial management; Improved capacity to repair agricultural equipment; improved quality of agricultural products or technology.

This indicator endeavors to capture the individuals who have made the decision to apply a particular management practice or technology, not those who have had to do so as a condition of employment or an obligation. For example, if a manager in a com pany that distributes agriculture produce decides to use refrigerator trucks for transport and plans the distribut ion route using GIS

information to maximize efficiency, both practices that are promoted by the USG-funded activity, the manager is counted as one individual; the five drivers of the newly refrigerated trucks who are driving the new routes are not counted. If the manager and co-owner together decided to apply these new practices, they are counted as two individuals. Another example would be if a franchise o ffers a new fertilizer mix developed with USG assistance and makes it available to franchisees, yet those franchisees make the decision

whether or not to offer it. In this case both the decision-maker(s) at the franchise level and the franchisees who decide to offer it get counted as individuals applying a new management practice.

It is common for USG-funded activities to promote more than one improved technology or management practice to farmers and other individuals, This indicator allows the tracking of the total number of participants that apply any improved management practice or technology during the reporting year and the tracking of the total number of participants that apply practices or technologies in specific

management practice and technology type categories. • Count the participant if they have applied a management practice or technology promo ted with USG assistance at least once in the reporting year. Count the producer participant who applied improved management practices or technologies regardless of the size of the plot on which practices were applied.


• Count each participant only once per year in the applicable Sex disaggregate category and Age disaggregate category to track the

number of individuals applying USG-promoted management practice or technology type. If more than one participant in a household is applying improved technologies, count each participant in the household who does so. • Under the Commodity disaggregate, count each participant once under each commodity for which they apply a USG-promoted

management practice or technology type. For example, if a participant uses USG-promoted improved seed for the focus commodities of maize and legume, count that participant once under maize and once under legumes. • Count each individual once per management practice or technology type once per year under the appropriate Management

practice/technology type disaggregates. Individuals can be counted under a number of different Management

• For example:

o If a participant applied more than one improved technology type during the reporting year, count the participant under

each technology type applied.

o If an activity is promoting a technology for multiple benefits, the participant applying the technology may be reported

under each relevant Management practice/technology type category. For example, a farmer who is using drought

tolerant seeds could be reported under Crop genetics and Climate adaptation/climate risk management depending for

what purpose(s) or benefit(s) the activity is being promoted to participant farmers. For example, if a private enterprise

invested in newer, more efficient machinery to process or otherwise improve the raw product that is also intended to

reduce emissions intensities, this practice would be counted under “value-added processing” and “climate mitigation”.

o Count a participant once per reporting year regardless of how many times she/he applied an improved

practice/technology type. For example, a farmer has access to irrigation through the USG-funded activity and can now

cultivate a second crop during the dry season in addition to the rainy season. Whether the farmer applies USG-

promoted improved seed to her plot during one season and not the other, or in both the rainy and dry season, she

would only be counted once in the Crop Genetics category under the Management practice/technology type

disaggregate (and once under the Irrigation category.)

o Count a participant once per practice/technology type category regardless of how many specific practices/technologies

under that technology type category she/he applied. For example, a Activity is promoting improved plant spacing and

planting on ridges. A participant applies both practices. She/he would only be counted once under the Cultural practices

technology type category.

IPs may use sales data from assisted firms for some kinds of inputs to estimate the number of producers for indicators EG.3.2-24

Number of individuals in the agriculture system who have applied improved management practices or technologies with USG assistance [IM-level], and EG.3.2-25 Number of hectares under improved management practices or technologies with USG assistance [IM-level] if they use clearly documented assumptions that are regularly validated through spot surveys or similar methods. For example, an IP working to strengthen the certified soy seed market within a defined market shed in the ZOI could use data on the

number and volume of certified soy seed sales by assisted firms during the reporting year to estimate the number of farmers a pplying certified soy seed (by using a conservative assumption that one sales equals one farmer applying) and hectares under certified seed by assuming a periodically validated planting density. All assumptions underlying the indicator estimates should be documented

annually in an Indicator Comment. However, if an agrodealer gives away seed packs with the purchase of other inputs as a promotion,

more validation would be necessary for the IP to assume farmers purchasing the other input are also applying that seed.

If a lead farmer cultivates a plot used for training, e.g., a demonstration plot used for Farmer Field Days or Farmer Field School, the lead farmer should be counted as a participant applying improved practices/technologies for this indicator. In addition, the area of the demonstration plot should be counted under indicator EG.3.2-25 Number of hectares under improved management practices or technologies with USG assistance [IM-level]. However, if the demonstration or training plot is cultivated by a researcher (a

demonstration plot in a research institute, for instance), neither the area nor the researcher should be counted under this indicator or

indicator EG.3.2-25.

Participants who are part of a group or members of an organization that apply improved technologies on a demonstration or oth er common plot should not be counted under this indicator, the area of the common plot should not be counted under indicator EG.3.2-25 Number of hectares under improved management practices or technologies with USG assistance [IM-level], and the yield should

not be counted under indicator EG.3-10, -11, -12 Yield of targeted agricultural commodities among program participants with USG assistance [IM-level]. For cultivated cropland, these three indicators (EG.3.2-24, EG.3.2-25 and EG.3-10, -11, -12) only capture results

for land that is individually managed.


However, there are some cases where group members can be counted under this indicator. For example, as a result of participat ing in

a USG-funded activity, a producer association purchases a dryer and then provides drying services for a fee to its members. In this

scenario, any member that uses the dryer service can be counted as applying an improved management practice under this indica tor.

Note that the list of practice/technology type disaggregates is broader under this indicator than the list of practice/technology type disaggregates under indicator EG.3.2-25 because this indicator tracks application of improved practices/technologies beyond those

that are applied to a defined land or water area.

Unit of Measure: Number. Result is specific to the reporting period.

Data Type: Integer.

Disaggregated by: FIRST LEVEL

Value chain actor type:

▪ Smallholder producers (e.g. farmers, ranchers, and other primary sector producers of food and nonfood crops, livestock

products, wild fisheries, aquaculture, agro-forestry, and natural resource-based products)

▪ Non-smallholder producers (e.g. farmers, ranchers, and other primary sector producers of food and nonfood crops, livestock

products, wild fisheries, aquaculture, agro-forestry, and natural resource-based products)

▪ People in government (e.g. policy makers, extension workers)

▪ People in private sector firms (e.g. processors, service providers, manufacturers)

▪ People in civil society (e.g. staff and volunteers from non-governmental organizations, community-based organizations,

research and academic organizations)

▪ Others

Note: Only count producers under the "Producers" disaggregate and not the "Private Sector Firms" disaggregate to avoid double-counting. While private sector firms are considered part of civil society more broadly, only count them under the "Private Sector

Firms" disaggregate and not the "Civil Society" disaggregate to avoid double-counting.

Smallholder Definition: While country-specific definitions may vary, use the Feed the Future definition of a smallholder producer,

which is one who holds 5 hectares or less of arable land or equivalent units of livestock, i.e. cattle: 10 beef cows; dairy: two milking cows; sheep and goats: five adult ewes/does; camel meat and milk: five camel cows; pigs: two adult sows; chickens: 20

layers and 50 broilers. The farmer does not have to own the land or livestock.

SECOND LEVEL

Sex: Male, Female

Age: 15-29, 30+

Management practice or technology type: Crop genetics, Cultural practices, Livestock management, Wild-caught fisheries management, Aquaculture management, Natural resource or ecosystem management, Pest and disease management, Soil -related fertility and conservation, Irrigation, Agriculture water management-non-irrigation based, Climate mitigation, Climate

adaptation/climate risk management, Marketing and distribution, Post-harvest handling and storage, Value-added

processing, Other

Commodity (See list in FTFMS):

Activities promoting sustainable intensification or those where multiple commodities are involved (e.g. transportation), wher e

counting participants by commodity is complicated and/or not meaningful are not required to disaggregate participants by

commodity, and should use the "Not applicable" category under the Commodity disaggregate.


Rationale for Indicator (optional): Improved management practices and technological change and adoption by different actors throughout the agricultural system will be critical to increasing agricultural productivity and supporting stronger and better functioning systems. This indicator falls under IR 1: Strengthened inclusive agriculture systems that are productive and profitable in the Global

Food Security Strategy (GFSS) results framework.


Data Source: Direct beneficiaries (farmers and aggregators).

Method of Data Collection and Construction: Sample survey of direct beneficiary farmers(beneficiary based survey, farmer groups approach). Data is collected quarterly during

beneficiary survey. Using the beneficiary registry developed from the training registers, a minimum of 30% of the beneficiaries who initially reported applying improved technologies and practices are randomly selected by the M&E team and visited and the accuracy of their application is verified by the M&E team.

Data Analysis: The M&E team reviews the training registers (which include whether the

participant implemented the targeted improved technologies and/or practices) and aggregates the data into a database. Then a minimum of 30% of the beneficiaries who are included are sampled randomly and receive a visit from the M&E team to confirm the validity of their participation and behaviors/technologies implemented.






DATA QUALITY ISSUES


N/A









Name of Indicator: EG.3.2-25 Number of hectares under improved management practices

or technologies with USG assistance




Year(s) 2019-2020


DESCRIPTION


This indicator measures the area in hectares where USG-promoted management practices or improved technologies were applied

during the reporting year to areas managed or cultivated by producers participating in a USG-funded activity. Management practices counted are agriculture-related, land- or water-based management practices and technologies in sectors such as cultivation of food or fiber, aquaculture, fisheries, and livestock management, including those that address climate change adaptation and mitigation.

Improved management practices or technologies are those promoted by the implementing partner as a way to increase producer’s

productivity directly or to support stronger and better functioning systems.

The application of both intensive and extensive agriculture-related management practices and technologies in different landscapes are

captured under the Type of Hectare disaggregate. The Type of Hectare disaggregates are: crop land, cultivated pasture, rangeland, conservation/protected area, freshwater or marine ecosystems, aquaculture, and other[1]. Intensive interventions are those where higher levels of inputs, labor and capital are applied relative to the size of land. Extensive interventions are those where smaller

amounts of inputs, labor and capital are applied relative to the size of land. For example, an intervention working to increase the production of fingerlings in aquaculture is considered intensive while using improved grazing practices for livestock in a rangeland landscape would be considered extensive. Those interventions carried out on crop land, cultivated pasture and aquaculture are

considered “intensive”. Those carried on rangeland, conservation/protected area and freshwater or marine ecosystems are considered

“extensive”. The same area cannot be counted under more than one Type of Hectare disaggregate category.

This indicator captures results where they were achieved, regardless of whether interventions were carried out, and result s achieved,

in the ZOI.

A management practice or technology can be applied under a number of different hectare types. For example, improved grazing

practices could take place in cultivated pasture, rangeland, or conservation and mixed-used landscapes, and climate

adaptation/climate risk management interventions can be applied in all hectare types.

Management practice and technology type categories, with some illustrative (not exhaustive) examples, include:

• Crop genetics: e.g. improved/certified seed that could be higher-yielding or higher in nutritional content (e.g. through bio-

fortification, such as vitamin A-rich sweet potatoes or rice, or high-protein maize), and/or more resilient to climate impacts

(e.g. drought tolerant maize or stress tolerant rice); improved germplasm.

• Cultural practices: context specific agronomic practices that do not fit in other categories, e.g. seedling production and

transplantation; cultivation practices such as planting density, crop rotation, and mounding.

• Livestock management: e.g. improved grazing practices, improved fodder crop, cultivation of dual purpose crops.

• Wild-caught fisheries management: e.g. sustainable fishing practices.

• Aquaculture management: e.g. pond culture; pond preparation; management of carrying capacity.

• Natural resource or ecosystem management: e.g. biodiversity conservation; strengthening of ecosystem services, including

stream bank management or restoration or re/afforestation; woodlot management.

• Pest and disease management: e.g. Integrated Pest Management; improved fungicides; appropriate application of

fungicides; improved and environmentally sustainable use of cultural, physical, biological and chemical insecticides and

pesticides; crop rotation; alflatoxin prevention and control during production.

• Soil-related fertility and conservation: e.g. Integrated Soil Fertility Management; soil management practices that increase

biotic activity and soil organic matter levels, such as soil amendments that increase fertilizer -use efficiency (e.g. soil organic

matter, mulching); improved fertilizer; improved fertilizer use practices; inoculant; erosion control.

• Irrigation: e.g. drip, surface, and sprinkler irrigation; irrigation schemes.

• Agriculture water management - non-irrigation-based: e.g. water harvesting; sustainable water use practices; practices that

improve water quality.

• Climate mitigation: technologies selected because they minimize emission intensities relative to other alternatives (while

preventing leakage of emissions elsewhere). Examples include low- or no-till practices; restoration of organic soils and

degraded lands; efficient nitrogen fertilizer use; practices that promote methane reduction; agroforestry;

introduction/expansion of perennials; practices that promote greater resource use efficiency (e.g. drip irrigation).

• Climate adaptation/climate risk management: technologies promoted with the explicit objective of reducing risk and

minimizing the severity of climate change. Examples include drought and flood resistant varieties; short -duration varieties;

adjustment of sowing time; diversification, use of perennial varieties; agroforestry.


• Other: e.g. improved mechanical and physical land preparation. Since it is very common for USG activities to promote more than one improved management pr actice or technology, this indicator allows the tracking of the number of hectares under the different management practices and technology types and the total unique

number of hectares on which one or more practices or technologies has been applied at the activity level.

• If a participant applied more than one improved technology during the reporting year, count that area on which the participan t

applied those technologies under each relevant Management Practice type applied under the relevant Hectare type.

However, count the area only once in the applicable Sex, Age and Commodity disaggregate categories under the relevant

Hectare type. This will not result in double-counting for the total in FTFMS.

• If an activity is promoting a single technology for multiple benefits, the area under the technology may be reported under

each relevant category under the Management Practice/Technology Type disaggregate. For example, drought tolerant seeds

could be reported under Crop genetics and Climate adaptation/climate risk management depending for what purpose(s) or

benefit(s) the activity was promoted.

• If a participant cultivates a plot of land more than once in the reporting year, the area should be counted each time one or

more improved management practice/technology is applied. For example, because of access to irrigation as a result of a

USG activity, a farmer can now cultivate two cycles of crops instead of one. If the farmer applies USG-promoted

technologies on her/his plot for the two cycles, the area of the plot would be counted twice under this indicator. Note that the

farmer would only be counted once under indicator EG.3.2-24 Number of individuals in the agriculture system who have

applied improved management practices or technologies with USG assistance [IM-level]. If a lead farmer cultivates a plot used for training, e.g. a demonstration plot used for Farmer Field Days or Farmer Field School, the

area of the demonstration plot should be counted under this indicator. In addition, the lead farmer should be counted as one individual under indicator EG.3.2-24 Number of individuals in the agriculture system who have applied improved management practices or

technologies with USG assistance [IM-level].

This is a snapshot indicator, which is designed to capture farmer application only for the reporting year. Individuals who applied a USG activity-promoted management practice before the intervention constitute the baseline. Individual that still continue to apply the USG

activity-promoted during the Activity period get counted for applying the technology in any subsequent years they apply that technology. However, this also means that yearly totals can NOT be summed to count application by unique individuals over the life of

the Activity.

IPs may use sales data from assisted firms for some kinds of inputs to estimate the number of producers for indicator EG.3.2-24 Number of individuals in the agriculture system who have applied improved management practices or technologies with USG assistance [IM-level] and indicator EG.3.2-25 Number of hectares under improved management practices or technologies with USG

assistance [IM-level] if they use clearly documented assumptions that are regularly validated through spot surveys or similar methods. For example, an IP working to strengthen the certified soy seed market within a defined market shed in the ZOI could use data on the number and volume of certified soy seed sales by assisted firms during the reporting year to estimate the number of farmers a pplying

certified soy seed (for example, by using a conservative assumption that one sales equals one farmer applying) and hectares under certified seed by assuming a periodically validated planting density. All assumptions underlying the indicator estimates shou ld be documented annually in an Indicator Comment. However, if an agrodealer gives away seed packs with the purchase of other inputs as

a promotion, more validation would be necessary for the IP to assume farmers purchasing the other input would also apply that seed.

Demonstration plots cultivated by researchers (a demonstration plot in a research institute, for instance) should not be counted under

this indicator nor should the researcher be counted under this indicator or indicator EG.3.2-24. The area of a demonstration or

common plot cultivated under improved practices or technologies by participants who are part of a group or members of an

organization should not be counted under this indicator, the participants should not be counted under indicator EG.3.2-24 Number of

individuals in the agriculture system who have applied improved management practices or technologies with USG assistance [IM -

level], and the yield should not be counted under indicator EG.3-10, -11, -12 Yield of targeted agricultural commodities among

program participants with USG assistance [IM-level].


For cultivated cropland, these three indicators (EG.3.2-24, EG.3.2-25, and EG.3-10, -11, -12) only capture results for land that is

individually managed. However, communally- or group-managed areas under extensive ”Type of Hectares” disaggregates, such as conservation landscapes or rangeland, can be reported under this indicator under the association-applied category under the Sex and Age disaggregate. Association-applied would be applicable for landscapes where communities or organizations develop and adhere

to policies regarding management, harvest, protection, etc.

[1] Type of hectare disaggregates defined as:

▪ Crop land: areas used for the production of crops for harvest, including cultivated, harvested, fallow or crop failure. Include

home gardens in this category.

▪ Cultivated pasture: land where forage crops are primarily grown for grazing

▪ Rangelands: land on which the native vegetation (climax or natural potential plant community) is predominantly grasses,

grass-like plants, forbs, or shrubs suitable for grazing or browsing use.

▪ Conservation/protected areas: terrestrial areas that are protected because of their recognized, natural, ecological or cu ltural

values. The protected status may fall into different categories and include strictly protected to those that allow for some

limited human occupation and/or sustainable use of natural resources, such as agroforestry, collection of NTFPs, etc.

▪ Fresh-water and marine ecosystems: aquatic areas that include freshwater, such as lakes, ponds, rivers, streams, springs,

and freshwater wetlands, and water with higher salt content, such as salt marshes, mangroves, estuaries and bays, oceans,

and marine wetlands.

▪ Aquaculture; areas dedicated to the breeding, rearing and harvesting of aquatic animals and plants for food.

▪ Other: Areas that don’t fit into these categories. Please describe the Hectare type in the indicator comment.


Data Type: Decimal (track to one decimal place)

Disaggregated by: FIRST LEVEL

Type of Hectare:

▪ Crop land,

▪ Cultivated pasture,

▪ Rangeland,

▪ Conservation/protected area,

▪ Freshwater or marine ecosystems;

▪ Aquaculture,

▪ Other

SECOND LEVEL:

Sex: Male, Female, Association-applied

Age: 15-29, 30+, Association-applied

Management practice or technology type (see description, above): Crop genetics, Cultural practices, Livestock management, Wild-caught fisheries management, Aquaculture management, Natural resource or ecosystem management, Pest and disease management, Soil-related fertility and conservation, Irrigation, Agriculture water management-non-irrigation based, Climate mitigation,

Climate adaptation/climate risk management, Other

Commodity (see list in FTFMS): Activities promoting sustainable intensification or those where multiple commodities are involved

where counting hectares is complicated and not meaningful are not required to disaggregate by commodity, and should use the

"Disaggregates not available" category under the Commodities disaggregate


Rationale for Indicator (optional): Improved management practices on agriculture land, in aquaculture, and in freshwater and marine fisheries will be critical to increasing agricultural productivity. This indicator tracks successful application of technologies and management practices in an effort to improve agricultural productivity, agricultural water productivity, sustainability, and resilience to climate change. In the GFSS results framework,

this indicator reports contributions to IR.4: Increased sustainable productivity, particularly through climate-smart approaches.


Data Source: Direct beneficiary farmers

Method of Data Collection and Construction: Sample survey of direct beneficiary farmers

(beneficiary based survey, farmer groups approach). Data is collected quarterly during beneficiary survey. Using the beneficiary registry developed from the training registers, a minimum of 30% of the beneficiaries who initially reported applying improved technologies and practices randomly selected and are visited, and the accuracy of their application is verified by the M&E team. The hectarage of their fields which apply those technologies/practices is then verified using GPS or field area applications.

Data Analysis: The M&E team reviews the training registers (which include whether the participant implemented the targeted improved technologies and/or practices) and aggregates the data into a database. Then a minimum of 30% of the beneficiaries who are included are sampled randomly and receive a visit from the M&E team to confirm the

validity of their participation and behaviors/technologies implemented.






DATA QUALITY ISSUES


N/A









Name of Indicator: Number of people reached by mass media awareness campaign on

contaminated grains (custom)



Is This a Performance Plan and Report Indicator? No X Yes for Reporting

Year(s)


DESCRIPTION

Precise Definition(s):

This indicator counts the number of people who are reached by activity supported awareness campaigns that have messages related to reducing contaminants in grains, in the areas targeted by the Activity. Campaigns may include radio messages, printed media, text messages, and events.


Data Type: Integer

Disaggregated by: None

Rationale for Indicator (optional): Mass media campaigns will amplify the messages disseminated

through training to promote agricultural practices that reduce contaminants in grain. Farmers who apply these practices and effectively reduce contaminants in their output to meet stringent quality requirements will be able to sell into the Nestlé supply chain, increasing Nestlé’s sourcing from local markets.



Data Source: Activity interventions records stating the estimated reach of each campaign.

For radio broadcasts, number reached will be estimated using audience data from the station. For printed media, number reached will be estimated based on number of materials printed and disseminated. For text messages, number reached will be obtained from the service used for dissemination. For events, number reached will be estimated from observation of attendance.

Method of Data Collection and Construction: Review of Activity records and Sample survey of direct beneficiary A random population of 400 is surveyed using the survey form included below from the LGAs where project activities are implemented, as well as Kaduna city to serve as a control. The percentage of respondents who say they listened to the broadcast is applied to the populations of the LGAs surveyed to provide a result of the total

number reached.

Data Analysis: The results of the listenership survey are shared with project staff. Along with determining the listeners’ basic information and whether they listen to the broadcast, the survey also determines whether they absorbed the technical topics covered in the broadcast.

This information is used to inform what topics will be addressed and emphasized in future broadcasts.






DATA QUALITY ISSUES

Dates of Previous Data Quality Assessments and Name of Reviewer(s): N/A




Changes to Indicator: N/A





Name of Indicator: YOUTH-3 Percentage of participants in USG-assisted programs

designed to increase access to productive economic resources who are youth (15-29) [IM-

level]


IR1: Increased use of technology and practices that reduce contaminants in the maize and soybean


Year(s) 2019-2020


DESCRIPTION


DEFINITION:

Youth is a life stage when one transitions from the dependence of childhood to adulthood independence. The meaning of “youth” varies in different societies. Based on the Feed the Future youth technical guide, the 10-29 age range is used for youth while keeping in mind the concept of “life stages,” specifically 10-14, 15-19, 20-24, and 25-29 years as put forward in the USAID Youth in Development Policy. Feed the Future activities will primarily cover working age youth ages 15-29. Partners may have different age range definitions

for youth based on their specific country contexts.

The productive economic resources that are the focus of this indicator are physical assets, such as land, equipment, buildings and,

livestock; and financial assets such as savings and credit; wage or self-employment; and income.

Programs include:

▪ value chain activities and market strengthening activities working with micro, small, and medium enterprises;

▪ financial inclusion programs that result in increased access to finance, including programs designed to help youth set up

savings accounts

▪ workforce development programs that have job placement activities;

▪ programs that build or secure access to physical assets such as land redistribution or titling; and programs that provide assets

such as livestock

This indicator does NOT track access to services, such as business development services or agriculture, food security or nutr ition

training.

The unit of measure for this indicator is a percent expressed as a whole number.

The numerator and denominator must also be reported as data points in the FTFMS.

Feed the Future Implementing Partners (IPs) and Post teams have the option of reporting directly on this indicator using data that aligns

with the indicator definition, or, to reduce IP burden, can use data from one of the two Feed the Future performance indicators listed

below:

From indicator EG.4.2-7 Number of individuals participating in group-based savings, micro-finance or lending programs with USG assistance [IM-level]:

a. For the numerator, use data on the number of youth participants.

b. For the denominator, use the total number of participants. Do not include “disaggregates not available”.

From indicator EG.3.2-27 Value of agriculture-related financing accessed as a result of USG assistance [IM-level]:

a. For the numerator, use data on the number of enterprises with all youth proprietors.


b. For the denominator, use the total number of enterprises. Do not include enterprises with a mix of youth (age 15-29)

and adults (age 30+) or “disaggregates not available”.

To avoid double counting, IPs that are reporting on more than one of the indicators listed above should use data from the ind icator with

the largest number of participants in the denominator.


Unit of Measure: Percent expressed as a whole number

Data Type: Percentage

Disaggregated by: None

Rationale for Indicator (optional): Harnessing the energy, potential, and creativity of youth in developing countries is critical for sustainably reducing global hunger, malnutrition, and poverty while reducing the risk of conflicts and extremisms fueled by

growing numbers of marginalized and frustrated youth [1]. To achieve the objectives of the U.S. Government Global Food Security Strategy (GFSS) and A Food-Secure 2030 vision, Feed the Future needs to harness the creativity and energy of youth. This indicator will allow Feed the Future to track progress toward increasing access to productive resources for Feed the Future program participants

who are youth. Under the GFSS, this indicator is linked to CCIR 4: Increased youth empowerment and livelihoods.


Data Source: Activity interventions records and Sample survey of direct beneficiary farmers

Method of Data Collection and Construction: Review of Activity records and Sample survey of direct beneficiary.

Data Analysis: The M&E team reviews the training registers (which include the age of the participant) and aggregates the data into a database. Then a minimum of 30% of the beneficiaries who are included are sampled randomly and receive a visit from the M&E team to confirm the validity of their participation and behaviors/technologies implemented. See

section ‘other notes’ for more detail.






DATA QUALITY ISSUES


N/A






Other Notes (optional): Per AOR guidance, the percentage will be calculated as follows: Numerator – Total number of youth in the agricultural system who have applied improved management practices or technologies with USG assistance (EG3.2-24) Denominator – Number of individuals in the agricultural system who have applied improved

management practices or technologies with USG assistance (EG3.2-24)



Annex B: Data COLLECTION tools

Assessment Form for Commercial Grain Stores

LGA------------------

Compiled by------------------------------------------------------------------------------------------

Date-----------------------------------------------------------------------------------------------------

S/n

Name and Location Gender Age Use of well-ventilated stores

Storage of grains on Pallets

M F YES NO YES NO


Assessment Form for Agro-input Dealers

LGA------------------

Compiled by------------------------------------------------------------------------------------------

Date-----------------------------------------------------------------------------------------------------

S/n

Name and Location

Gender Age

Use of well-ventilated stores

Storage of Seeds on Pallets or Planks

M F YES NO YES NO


Monthly Monitoring Form for Agro-Input Dealers

LGA---------------------------------Month------------------------------

S/n

Input Dealer

ID

No. of training received

Use of well

ventilated stores

Sale of only

treated seeds

Storage of

Seeds on

Pallets

Sale of only well packaged

seeds

Source of

Products

Sale of non-

expired products

Availability of First Aid Box

Use of

PPE,

Hand gloves ,Eye and head gears

Good Knowledge

of products

Availability of

Purchase and sales records

Compiled by:-------------------------------------------------------------- Date:----------------------------------------------------------------------------------

Verified by:---------------------------------------------------------------- Date:----------------------------------------------------------------------------------


Farmer Monthly (June, July, August) Monitoring Form

Date---------------------------Community

S/N Farmer ID

Ha Planted to

No. of times visited

Dressed Seeds

Seed Germination

Test

Soil Testing

Plant Spacing

Fertilizer App

Seed Rate

Use of Aflasafe

Maize Soya Maize Soya

Compiled by:-------------------------------------------------------------- Date:----------------------------------------------------------------------------------

Verified by:---------------------------------------------------------------- Date:----------------------------------------------------------------------------------


FEED THE FUTURE NIGERIA AND NESTLE MAIZE QUALITY IMPROVEMENT PARTNERSHIP

FARM VISIT/OBSERVATION FORM

Prepared by: …………………………………….. Sign: ……………………………………………………………

Verified by: ……………………………………… Sign: ……………………………………………………………

SN DATE FARMER’S NAME VILLAGE/COMMUNITY

OBSERVATION (e.g. leaf coloration, leaf curling, army

worm, etc.)

FARMER’S

THUMB PRINT

EA’s REMARK

1

2

3


TRAINING ATTENDANCE LIST

FEED THE FUTURE NIGERIA AND NESTLE MAIZE QUALITY IMPROVEMENT PARTNERSHIP

CULTIVATING NEW FRONTIERS IN AGRICULTURE (CNFA-NIGERIA) DATE:

TITLE: VENUE:

S/NO First Name Last Name Status Old New

Gender M F

Address/ID Telephone Signature


ASSESSMENT OF APPLICATION OF RECOMMENDED PRACTICES BY FARMERS

Background Information

1. Name of Community:---------------------------------------

2. Ward:-------------------------------------------------------------

3. LGA:--------------------------------------------------------------

4. Name of farmer:…………………………………………………………

5. Age:---------------------------------------------------------------

4. Sex: Male [ ] Female [ ]

5. Please indicate if you applied any of the recommended practices between October and December 2018

SN Improved Practice

Yes No

1 Used recommended harvesting method for soya

2 Used recommended harvesting method for maize

3 Use of Tarpaulins in Threshing of soya

7 Use of Tarpaulins in Threshing of maize

8 Use of Tarpaulins in drying of soya


9 Use of Tarpaulins in drying of maize

10 Used PICS Bags for Storage maize

11 Store grains on pallet or planks tops.

6. Size of Maize and Soy farms and production

Crops Ha Output(bags)* Yield kg *Bags of Soy threshed on tarpaulin

*Bags of Maize

threshed on tarpaulin

Maize

Soya

1bag=100kg

Completed by--------------------------------------------------------------

Date:-------------------------------------------------------------------------


QUESTIONNAIRE

FARM RADIO LISTENERSHIP SURVEY

(A) Socio-Economic or Demographic Characteristics of Respondents.

(1) Name of Respondent………………………………………………………………………………. (2) Village…………………………………………………………………………………………………………. (3) Local Government Area……………………………………………………………………………….. (4) Gender Male ( ) Female ( ) (5) Marital Status: Single ( ) Married ( ) Divorced ( ) Others………………… (6) Highest Educational Level:

(a) Primary Education ( ) (b) Secondary Education ( ) (c) Tertiary Education ( ) (d) Non-Formal Education ( )

(7) Age of Respondents…………………………………………………. Years (8) Household Size of Respondents…………………………..Member…..…Male …… Female

(B) Radio Listening Habits (Reach, Relevance, and Response)

(9) Do you listen to FRCN Kaduna? Yes ( ) No ( ) (10) Kindly tick your position concerning listenership of KuSaurara Manoma programs

of FRCN Kaduna. (a) Listeners ( ) (b) Non- Listeners ( )

(11) How frequent did you listen to the farm radio programs (a) Once per Week ( ) (b) Twice per Week ( ) (c) Weekly ( ) (d) Monthly ( ) (e) Others Specify…………………………..

(a) No revisions were done here. See comments above regarding the fact that this is not a

sample survey, but a data spot check for accuracy.Recently ( ) (b) Last 7 Days ( ) (c) Last Month ( ) (d) Last 2 Month ( )


(12) Where did the respondents listen to the farm radio program? (a) At Home ( ) (b) Inside the Car ( ) (c) Farm ( ) (d) At Work ( ) (e) In Public Places ( ) (f) On Public Transport ( ) (g) Others Specify……………………………..

(13) How did the respondents listen to the farm radio programs? (a) Own a Radio ( ) (b) Through Relatives ( ) (c) Through Friends ( ) (d) Others Specify…………………………………..

(14) With whom did you listen to the farm radio programs? (a) Alone (b) With Family Members (c) With Friends and Relatives (d) Others Specify………………………………………

(15) State your commitment to the farm radio program (a) Dedicated Listener ( ) (b) Interested Listener ( ) (c) Casual Listener ( ) (d) Others Specify……………………………..

(16) Is the content, topic, issues discussed in the farm radio program relevant to the main issue? (a) Yes ( ) (b) No ( )

(17) Did you accept the farm radio program in meeting the main issue/ (a) Yes ( ) (b) No ( )

(18) Did you understand the content of the farm radio program?

(a) Yes ( ) (b) No ( )

(19) State the duration you stayed listening to the farm radio program/broadcast day.……………………………Minutes

(20) Is the farm radio program delivered at appropriate time?


(a) Yes ( ) (b) No ( )

(21) If No, Please state the time you consider appropriate for the farm radio program…………………………………………………………..

(22) Why did you listen to the farm radio program? (a) Informed ( ) (b) Entertainment ( ) (c) Educated ( ) (d) Local News ( ) (e) National News ( ) (f) Others Specify………………………………

(23) Specify changes that occur as a result of farm radio program (a) Adjusting the behavior of target audience ( ) (b) Audience taking specific action to address the issues ( ) (c) Both (a) and (b)

(24) Please state other changes that occurred as a result of listening to the farm radio program( Multiple Choices) (a) Use of Improved Agricultural Practices inform of Certified Seeds,

Planting Spacing, Fertilizers, Herbicides, Fungicides and Insecticides ( ) (b) Harvesting at the Right Time and Drying to Prevent Contaminations( ) (c) Joining Farmers Group to access Information and Credit Facilities ( ) (c)Improved Maize and Soyabean Quality ( ) (b) Increase Output of Maize and Soyabean ( ) (c)Increase Profitability of Maize and Soyabean Enterprise ( ) (d) Improved Supplies of Maize and Soyabean as Outgrowers and Reduced Rejection of these Products by Buyers ( ) (e) Low Incidence of Health Problems ( ) (f) Better Ways of Communicating Safe Food Consumption among People ( ) (g) Reduced Aluminum Uptake in Foods (Maize and Soyabeans) ( )

(25) Please state your level of awareness of the KuSaurara Manoma farm radio

program.

(a) Aware ( ) (b) Not –Aware ( )

(C) Perceived Index of Farm Radio Program Listeners


(27) Perceived Index of the Respondents to the Farm Radio Program

S/N

Perceived Statement

Strongly Agree 5

Agree 4

Neutral 3

Disagree 2

Strongly Disagree 1

(i) Contents, Topics Covered In the Farm Radio Programs are Relevant to the Main Issue Discussed

(ii) Farm Radio Programs Do Not Bring any Significant Changes Among the General Populace in Adjusting their Behaviour or Audience taking Actions to Address the Main Issues

(iii) There is General Acceptance and Understanding of the Farm Radio Programs among the Populace

(iv) There is General Public Awareness of the Farm Radio Programs among the Populace

(v) The Frequency, Timing, and Duration of the Farm Radio Program is Appropriate for the General Populace

(vi) There is Gender Equality in the Acceptance of the Farm Radio Programs among the General Populace.

(vii) Mycotoxins do contaminate Maize and Soyabeans either at Harvest or Under PostHarvest Condition

(viii) Mycotoxins do cause health Hazards to humans and animals

(ix) Mycotoxins do cause huge losses to farmers

(x)

Soil that contains 5% to 10% Al is


the Primary Source of Aluminium contamination of Maize and Soyabean grown on Such Soil

(xi) Ingested Aluminum from Food and Other Vetinary Drugs, Fertilizers, Agrochemicals accumulate in Body, Compete With Useful Calcium Absorption and Cuases slow Growth in Infants

(xii) Maize and Soyabean Contaminated With Aluminum has Suffered Rejection against Some Supplies

(xiii) Improvement in Health of Rural Communities through Consumption Of Safe Products

(xiv) Improvement in Agricultural Practices of Smallholder Farmers And Farmers Associations

(xv) Enhancement of Rural Supply Along Supply Chains of Farmers And Farmers Associations

(D) Problems and Suggested Solutions towards Overall Success of Farm Radio

Programs (28) State Major Problems or Issues to the Overall Success of the Farm Radio

Programs (a)……………………………………………………………………………………………………….. (b)……………………………………………………………………………………………………….. (c)…………………………………………………………………………………………………………. (d)…………………………………………………………………………………………………………..

(29) State Suggested Solutions to the Overall Success of the Farm Radio Programs. (a) ……………………………………………………………………………………………………. (b) ……………………………………………………………………………………………………...


(c)………………………………………………………………………………………………………

(d)……………………………………………………………………………………

…………………

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