This paper focuses on techniques in utilizing remote sensor technology for precision crop production by farmers as climate change adaptation strategy in Nigeria. Descriptive survey research design was adopted for the study and was carried out between August 2013 and May 2014. The findings of the study revealed that 32 items were needed by farmers in utilizing sensory technology for precision crop production. The study recommended that the 32 items identified by the study should be utilized by extension agent in teaching the farmers the use of sensor technology for precision crop production while the farmers should make themselves available for the training.
In every part of the world, farmers engage in crop production with the aim of providing food, income, raw materials and foreign exchange among others for the citizens. Crop production is the act of cultivating the soil in order to provide food and other materials for man and industrial uses. Crops grown require soil nutrients and water in addition to sunlight to derive the photosynthetic process so as to produce edible products for man’s use. Crop production is climate sensitive with outdoor production activities that depend largely on particular levels of weather conditions. This means that crop production is one of the most sensitive agricultural sectors to climate change.
Climate change is the significant and lasting variation in the statistical properties of the average weather condition when considered over long periods of time, regardless of cause [
Adaptation is the adjustment in natural or human systems in response to actual or expected climate stimuli or their effects [
Precision farming refers to information and technology-based agricultural management system to improve crop production efficiency by adjusting farming inputs to specific conditions within each area on a field [
Remote sensing technology (RST) refers to the science of wirelessly observing and obtaining information on crop and soil characteristics using devices attached to aircraft, satellite, and agricultural equipment such as tractor [
RST can provide useful information for many crop management decisions, including detection of nutrient or water deficiencies and excesses in the soil, damages caused by insects, weeds, or diseases in various portions of the cultivated fields. RST obtains information about an object (crop or soil) without directly contacting it. Data collected can range from a simple colour photograph to the crop’s emission of electromagnetic energy [
Remote-sensory technology has a variety of applications, including environmental monitoring, site-specific agronomic management (SSM), land cover classification, climate- and land-use-change detection, and drought monitoring [
Using RST in PF will revolutionize the data collection in agricultural field, support the highly sought after automated agriculture system (AAS) which requires intensive sensing of environmental conditions at the ground level and rapid communication of the raw data to a local or remote server where there is the availability of computational and storage power, the identification of pests in the crops, drought or increased moisture, decision making, while the control of farm equipment is done in real time using automated actuation devices [
The most important step in PF is the generation of maps of the soil with its characteristics [
In Nigeria, many farmers detect presence of draught, pests and diseases and plant-water requirement through scouting method. This traditional method provides single point coverage which does not permit farmers to know the exert soil and plant conditions in addition to preventing them by monitoring trends in the production for effective crop management decisions. It was also observed that despite farmers’ effort to use different means for increased crop production in the country, occurrence of irregular and non-predictive rainfall pattern and sunshine hours continued to lower harvests of cassava, maize, melon and yam with at least 2.5% decline of harvests per annum [
1) Planning techniques needed in utilization of sensor technology in crop production;
2) Operation techniques of sensory technology.
This study adopted survey research design and was carried out in Nigeria between August 2013 and May 2014. The population for this study was 352 made up of 52 lecturers of agriculture from federal universities and 300 extension agents from ADP offices in Nigeria. A 32 item structured questionnaire identified from literature reviewed for the study was used to collect data from the respondents. Each questionnaire item was assigned a 4 response options of Highly Needed (HN) = 4, Averagely Needed (AN) = 3, Slightly Needed (SN = 2) and Not Needed (NN) = 1. The questionnaire items were face validated by 3 experts; two lecturer of agriculture from Enugu State University of Science and Technology (ESUT) Enugu and one extension officer from Imo State Agricultural Development Project (ADP) office. The Cronbach alpha method was used to determine the internal consistency of the items and a coefficient of 0.87 was obtained. The researchers collected the data with the help of eight assistants who were selected based on their familiarity with the study area. The respondents were requested to check the level to which each items was required with the aim to help develop a stepwise techniques that could be used as a training package for the farmer in the utilization of sensor technology. Out of 352 copies of the questionnaire administered, 327 (49 from lecturers and 278 from extension agents) were returned and used for data analysis.
The data collected for the study were analyzed using weighted mean to answer the research questions. In order to take decision on the needed item, real limit of numbers were assigned to each item thus: Highly Needed (HN 4) = 3.50 - 4.49; Averagely Needed (AN 3) = 2.50 - 3.49; Slightly Needed (SN 2) = 1.50 - 2.49; Not Needed (NN 1) = 1.00 - 1.49. So any item with a mean value within the real limit as indicated was interpreted accordingly as; Highly Needed (HN), Averagely Needed (AN) or Slightly Needed (SN) whereas any item with a mean value less than 1.50 was interpreted as Not Needed (NN). The standard deviation was used to determine the closeness of the respondents from the mean. Any item with a standard deviation of 1.96 or below indicated that the respondents were close to the mean and to one another in their responses while any item with a standard deviation above 1.96 showed that the respondents were far from the mean and to each other in their responses.
The results of the study were obtained from the research questions answered and presented in table 1 and table 2.
What are planning techniques needed in the utilization of sensor technology for precision crop production?
Data for answering research question one were presented in table 1.
Data in
The standard deviation of all the 17 items ranged from 0.08 - 0.82 which were below 1.96. The values indicated that the respondents were close to the mean and to one another in their opinions.
What are operational techniques needed in the utilization of sensor technology for precision crop production?
S/N | Items on planning techniques needed in the utilization of sensor technology | SD | Rm | |
---|---|---|---|---|
1 | Acquire computer operation technique | 3.69 | 0.61 | HN |
2 | Identify crop farm to be monitored | 3.21 | 0.76 | AN |
3 | Identify agro-device allied information | 3.72 | 0.57 | HN |
4 | Determine the number of sensory devices required per hectare | 3.58 | 0.82 | HN |
5 | Determine plant density | 2.52 | 0.24 | AN |
6 | Generate soil map with its characteristics | 3.47 | 0.50 | AN |
7 | Create agro―electronic computer data base | 3.71 | 0.26 | HN |
8 | Distribute sensory devices per hectare | 3.67 | 0.27 | HN |
9 | Configure devises in the farm land | 3.45 | 0.13 | AN |
10 | Set up base information for transmission of collected data | 3.73 | 0.09 | HN |
11 | Connect sensor to any existing communication infrastructure (internet) | 2.71 | 0.12 | AN |
12 | Identify relevant personnel | 3.57 | 0.08 | HN |
13 | Procure relevant facilities for the project | 3.59 | 0.26 | HN |
14 | Identify necessary adjustments to make for accurate data collection | 3.38 | 0.22 | AN |
15 | Identify records to keep | 2.31 | 0.29 | HN |
16 | Budget for the gadgets | 3.54 | 0.18 | HN |
17 | Source for fund | 2.49 | 0.12 | SN |
Note: Rm―Remark; HN―Highly Needed; AN―Averagely Needed; SN―Slightly Needed.
S/N | Item statement on operation techniques of sensor technology | SD | Rm | |
---|---|---|---|---|
1 | Calculate vegetation index (cover, growth and canopy) | 3.53 | 0.13 | HN |
2 | Mount or attach sensory devices on the equipment | 3.45 | 0.28 | AN |
3 | Drive ground-based mounted device | 3.80 | 0.47 | HN |
4 | Issue appropriate command to remote sensor | 2.50 | 0.42 | AN |
5 | Operate computer from home or strategic place | 3.87 | 0.14 | HN |
6 | Control the devices during use | 3.74 | 0.56 | HN |
7 | Manipulate the graphical user interface of the sensor technology | 3.64 | 0.14 | HN |
8 | Monitor the crop yield | 2.87 | 0.91 | AN |
9 | Control scenarios with graphical user interface | 3.23 | 0.75 | AN |
10 | Record the observations or readings | 3.89 | 0.29 | HN |
11 | Detach the device after use | 3.89 | 0.76 | HN |
12 | Calculate vegetative index | 3.73 | 0.08 | HN |
13 | Interpret data | 3.88 | 0.18 | HN |
14 | Make suggestions based on interpreted data | 3.57 | 0.15 | HN |
15 | Apply the data for crop production in specific areas of the farm | 3.65 | 0.39 | HN |
Note: Rm―Remark; HN―Highly Needed; AN―Averagely Needed; SN―Slightly Needed.
Data for answering research question one were presented in table 1.
Data in
The standard deviation of all the 15 items ranged from 0.14 - 0.91 which were below 1.96. The values indicated that the respondents were close to the mean and to one another in their opinions.
The result of the study in table 1 revealed that in planning for utilization of sensor technology the farmers needed to acquire computer operation technique to collect route data to other sensors and back to external base station, determine the number of sensor devices required per hectare, determine the plant density, set up based information, configure and distribute sensor devises in the farm, connect sensor to any existing communication infrastructure (internet), identify crop farm to be monitored and agro-based allied information, relevant personnel, determine records to keep and provide necessary fund among others. The findings of this study were in line with the findings of [
The result of the study in table 2 revealed that in operating sensor technology, the farmer needed the techniques that could enable him calculate vegetation index (cover, growth and canopy), drive ground-based mounted device, issue appropriate command to remote sensor, manipulate the Graphical User Interface of the sensor, monitor the crop yield, interpret data and make suggestions among others. The findings of the study were in conformity with the findings of [
The findings of the authors cited above helped to validation the results of this study.
It is the wish of farmers to produce enough to feed the teaming population without much stress despite the impact of climate change. This objective can only be achieved by the farmers through the use of sensory technologies for precision crop production. The problem is that most farmers lack the necessary techniques needed for effective manipulation of sensory technology in crop farming. Furthermore, the extension agents who educate the farmers on new technologies were also interested in making the farmers effective in crop production but the stepwise techniques on the utilization of sensor technology are not available for the teaching of farmers. It was based on this scenario that this topic emerged with the aim to identify the techniques needed by farmers in utilizing sensor technology for precision crop production as climate change adaptation strategy. This study identified 32 items that could be utilized by farmers in utilizing sensor technology in crop production as a coping strategy to climate change. The study therefore recommended that the extension agents should utilize the identified techniques in teaching farmers to make them become abreast with the needed techniques in utilization of sensor technology as adaptation strategy to climate change impacts. It was also recommended that farmers should make themselves available for the training to make them competent in guarding against climate change impact.