scholarly journals Potential yield and yield gap analysis of sugarcane (Saccharum officinarum) using the DSSAT-CANEGRO model in different districts of Uttar Pradesh, India

2021 ◽  
Vol 23 (2) ◽  
pp. 147-153
Author(s):  
R.S. SINGH ◽  
K.K. SINGH ◽  
A.H. BHENGRA ◽  
S.M. SINGH ◽  
GANESH PRASAD ◽  
...  
Keyword(s):  
Gap Analysis ◽  
Total Yield ◽  
Uttar Pradesh ◽  
Saccharum Officinarum ◽  
The State ◽  
Weather Data ◽  
Yield Gap ◽  
Potential Yield ◽  
Daily Weather Data ◽  
Attainable Yield

DSSAT-CANEGRO model have been used to determine crop potential yield over eight districts (viz; Muzaffarnagar, Shahjahanpur, Agra, Lucknow, Basti, Faizabad, Allahabad and Jhansi) representing different agroclimatic conditions & environmentof Uttar Pradesh state in India. The thirty six years (1980-2016) daily weather data of above districts were used to simulate seasonal yield potentials under the various management conditions and compared with the respective district reported yield. The simulated mean potential yield by the CANEGRO model over different district of the state varied between 77.8 t ha-1 in Muzaffarnagar and 97.8 t ha-1 in Agra, while mean reported yield (fresh stalk mass) varied between 40.1 t ha-1 in Jhansi and 62.8 t ha-1 in Muzaffarnagar within the state. Similarly, the attainable yield by the model was simulated lowest of 65.1 t ha-1 in Shahjahanpur and the highest of 73.6 t ha-1 in Faizabad district. The management yield gap was between 9.0 to 30.0 t ha-1 while sowing yield gap was between 7.0 to 26.0 t ha-1 in different districts under study. Further it is not only interesting & surprising but also encouraging to growers that the trends in total yield gap at all the above districts in various agro-climatic zones were found decreasing (narrowed down) at the rate of 138.8 – 801.2 kg ha–1 year–1. Delayed planting by about 30 days in some of the districts resulted into a decrease in sugarcane yield to the tune of 106.7 to 146.7, 103.3 to 143.3 and 80.0 to 133.0 kg ha–1 day–1, respectively. Findings reveal that DSSAT crop simulation model can be an effective tool to aid in decision support system. Yield gap estimates using the past crop data and subsequent adjustment in planting window may help to achieve close to the potential yields.

scholarly journals Unravelling the variability and causes of smallholder maize yield gaps in Ethiopia

Food Security ◽  
2019 ◽  
Vol 12 (1) ◽  
pp. 83-103 ◽  
Author(s):  
Banchayehu Tessema Assefa ◽  
Jordan Chamberlin ◽  
Pytrik Reidsma ◽  
João Vasco Silva ◽  
Martin K. van Ittersum
Keyword(s):  
Stochastic Frontier Analysis ◽  
National Level ◽  
Total Yield ◽  
Maize Yield ◽  
Sub Saharan Africa ◽  
Yield Gap ◽  
Potential Yield ◽  
Frontier Analysis ◽  
Yield Gaps ◽  
Maize Yields

AbstractEthiopia has achieved the second highest maize yield in sub-Saharan Africa. Yet, farmers’ maize yields are still much lower than on-farm and on-station trial yields, and only ca. 20% of the estimated water-limited potential yield. This article provides a comprehensive national level analysis of the drivers of maize yields in Ethiopia, by decomposing yield gaps into efficiency, resource and technology components, and accounting for a broad set of detailed input and crop management choices. Stochastic frontier analysis was combined with concepts of production ecology to estimate and explain technically efficient yields, the efficiency yield gap and the resource yield gap. The technology yield gap was estimated based on water-limited potential yields from the Global Yield Gap Atlas. The relative magnitudes of the efficiency, resource and technology yield gaps differed across farming systems; they ranged from 15% (1.6 t/ha) to 21% (1.9 t/ha), 12% (1.3 t/ha) to 25% (2.3 t/ha) and 54% (4.8 t/ha) to 73% (7.8 t/ha), respectively. Factors that reduce the efficiency yield gap include: income from non-farm sources, value of productive assets, education and plot distance from home. The resource yield gap can be explained by sub-optimal input use, from a yield perspective. The technology yield gap comprised the largest share of the total yield gap, partly due to limited use of fertilizer and improved seeds. We conclude that targeted but integrated policy design and implementation is required to narrow the overall maize yield gap and improve food security.

scholarly journals Yield Gap Analysis in Major Field Crops of Tamil Nadu

2021 ◽  
pp. 104-113
Author(s):  
A. Divakaran ◽  
V. Keerthana ◽  
M. Udhayakumar
Keyword(s):  
Tamil Nadu ◽  
Gap Analysis ◽  
Technology Development ◽  
Arable Land ◽  
Work Force ◽  
Land Area ◽  
Yield Gap ◽  
Potential Yield ◽  
Major Field ◽  
Field Crops

Agriculture plays a vital role in Indian economy, contributes 13% of gross domestic product and provides employment opportunities to more than 50% of work force.  In India 60% of land area are arable leads to second largest country in terms of total arable land area. The technology development rate is 2 percent and farm productivity rate only increase by 0.3 percent in major crops. It implied that outreach of technology from lab to land have several constraints. In this study, yields gaps of major field crops are calculated with the data provided by the joint directorate of Tamil Nadu, to find, to which extent the advancement in agriculture is helpful and it is found out that the yield gap II of selected varieties of major crops are high. It shows the deviation from the potential yield of the variety with the actual yield obtained by the farmer.

scholarly journals Monitoring and Analyzing Yield Gap in Africa through Soil Attribute Best Management Using Remote Sensing Approaches: A Review

2021 ◽  
Vol 13 (22) ◽  
pp. 4602
Author(s):  
Keltoum Khechba ◽  
Ahmed Laamrani ◽  
Driss Dhiba ◽  
Khalil Misbah ◽  
Abdelghani Chehbouni
Keyword(s):  
Remote Sensing ◽  
Soil Properties ◽  
Crop Yield ◽  
Gap Analysis ◽  
Smallholder Farmers ◽  
Current Status ◽  
African Countries ◽  
Yield Gap ◽  
Potential Yield ◽  
Yield Gap Analysis

Africa has the largest population growth rate in the world and an agricultural system characterized by the predominance of smallholder farmers. Improving food security in Africa will require a good understanding of farming systems yields as well as reducing yield gaps (i.e., the difference between potential yield and actual farmer yield). To this end, crop yield gap practices in African countries need to be understood to fill this gap while decreasing the environmental impacts of agricultural systems. For instance, the variability of yields has been demonstrated to be strongly controlled by soil fertilizer use, irrigation management, soil attribute, and the climate. Consequently, the quantitative assessment and mapping information of soil attributes such as nitrogen (N), phosphorus (P), potassium (K), soil organic carbon (SOC), moisture content (MC), and soil texture (i.e., clay, sand and silt contents) on the ground are essential to potentially reducing the yield gap. However, to assess, measure, and monitor these soil yield-related parameters in the field, there is a need for rapid, accurate, and inexpensive methods. Recent advances in remote sensing technologies and high computational performances offer a unique opportunity to implement cost-effective spatiotemporal methods for estimating crop yield with important levels of scalability. However, researchers and scientists in Africa are not taking advantage of the opportunity of increasingly available geospatial remote sensing technologies and data for yield studies. The objectives of this report are to (i) conduct a review of scientific literature on the current status of African yield gap analysis research and their variation in regard to soil properties management by using remote sensing techniques; (ii) review and describe optimal yield practices in Africa; and (iii) identify gaps and limitations to higher yields in African smallholder farms and propose possible improvements. Our literature reviewed 80 publications and covered a period of 22 years (1998-2020) over many selected African countries with a potential yield improvement. Our results found that (i) the number of agriculture yield-focused remote sensing studies has gradually increased, with the largest proportion of studies published during the last 15 years; (ii) most studies were conducted exclusively using multispectral Landsat and Sentinel sensors; and (iii) over the past decade, hyperspectral imagery has contributed to a better understanding of yield gap analysis compared to multispectral imagery; (iv) soil nutrients (i.e., NPK) are not the main factor influencing the studied crop productivity in Africa, whereas clay, SOC, and soil pH were the most examined soil properties in prior papers.

An empirical study of yield gap in seed cotton production in Tamil Nadu state, India

2015 ◽  
Vol 49 (6) ◽  
Author(s):  
Zelda A. Elum ◽  
C. Sekar
Keyword(s):  
Tamil Nadu ◽  
Total Yield ◽  
Relative Yield ◽  
Multiple Regression Model ◽  
The State ◽  
Bt Cotton ◽  
Cotton Production ◽  
Seed Cotton ◽  
Yield Gap ◽  
Negative Effect

A study was carried out in Tamil Nadu to examine the extent of yield gap in seed cotton. The study used data from 180 farmers in the State. The purpose of the study was to implement a framework that measures the relative yield of seed cotton produced in the study area. A multiple regression model was used to analyse the determinants of yield gap and the results showed that potash gap had a statistically significant but negative effect on yield while nitrogen had a statistically significant and positive effect. Total yield gap in Bt cotton (1658 kg/ha) was significantly higher than that of conventional cotton (594 kg/ha). Thus, there was considerable scope for improvement in the use of Bt technology since the farmers were yet to fully harness the proposed benefits of this genetically modified crop. Further analysis showed that the yield gap in various districts of the state were significantly different. It was inferred from the results that increased application of nitrogen increased yield but increased usage of potash had diminishing effects, while the applying of more labour and insecticides increased yield. It is suggested that there should be intensified effort on the sensitization of farmers about the detrimental effects of using inputs in excess.

scholarly journals Prediction of potential and attainable yield of wheat : A case study on yield gap

MAUSAM ◽  
2022 ◽  
Vol 53 (1) ◽  
pp. 45-52
Author(s):  
R. K. MALL ◽  
M. K. SRIVASTAVA
Keyword(s):  
Simulation Models ◽  
Yield Potential ◽  
Wheat Crop ◽  
Yield Gap ◽  
Potential Yield ◽  
Potential Productivity ◽  
Field Experimentation ◽  
Attainable Yield

This study reports the role of field experimentation and system simulation in better quantifying the productivity of wheat crop, and examine how knowledge on potential productivity can improve the efficiency of the production system. When knowledge from field experimentation is utilised into crop weather simulation models, gap between actual, attainable and potential yield for a given environment can be determined and opportunities for yield improvement can be assessed. Results show that while actual district average yields show increasing trend, decreasing trend is noticed in potential and attainable yield. While the total and management yield gap is decreasing over time, research yield gap does not show any trend, it is nearly stagnant from early eighties to late nineties. The study reported here presents the advantage of simulation models to determine the yield gap against a variable annual yield potential for a agro-climatic region.

scholarly journals Rice Yield Gaps in Smallholder Systems of the Kilombero Floodplain in Tanzania

Agronomy ◽  
2020 ◽  
Vol 10 (8) ◽  
pp. 1135
Author(s):  
Julius Kwesiga ◽  
Kristina Grotelüschen ◽  
Kalimuthu Senthilkumar ◽  
Daniel Neuhoff ◽  
Thomas F. Döring ◽  
...  
Keyword(s):  
Field Experiments ◽  
Farmyard Manure ◽  
Total Yield ◽  
Crop Management ◽  
Nutrient Deficiencies ◽  
Green Manures ◽  
Yield Gap ◽  
Potential Yield ◽  
Mineral N ◽  
Yield Gaps

To meet the growing rice demand in Africa, gaps between actual and attainable yields have to be reduced. In Tanzania, this particularly concerns smallholder rain-fed production systems in the floodplains. After quantifying the existing yield gaps, key contributing factors need to be analyzed to improve site-specific management. Field experiments were conducted for three years and in three pedo-hydrological environments (fringe, middle, and center positions) of the Kilombero floodplain to evaluate: (1) The grain yield under farmers’ management (actual yield), (2) yield with the best-recommended management (attainable yield), and (3) the non-limited yield simulated by the APSIM model (potential yield). In the field, we additionally assessed incremental effects of (1) field bunding and soil levelling, (2 and 3) additionally applying of 60 kg N ha−1, as urea or as farmyard manure (FYM), and (4 and 5) incorporating in-situ-grown leguminous green manures. Attainable yields were determined with mineral N application at 120 kg ha−1, additional PK fertilizer and supplemental irrigation. On average across years and positions, the potential, the attainable, and farmers’ actual yields were 11.5, 8.5, and 2.8 t ha−1 indicating a high total yield gap. About 16–38%, 11–20%, and 28–42% of this gap could be attributed to non-controllable yield-reducing (i.e., pest and diseases), yield-limiting (i.e., water and nutrient deficiencies), and yield-defining factors (i.e., poor soil and crop management), respectively. Results indicate a closure of the exploitable yield gap (differences between attainable and farmers’ actual yields) by up to 6.5 t ha−1 (nearly 60% of the potential yield). This exploitable yield gap was larger in 2016 than in 2017. Also, the gap was larger in the water-limited fringe and middle than in the frequently submerged center positions. Simple field bunds combined with land levelling could close 15–35% of the exploitable yield gap, depending on field positions and year. FYM or green manures were less effective than mineral N; however, in 2017 and in the wetter middle and center positions, they reduced the yield gap by >50%. We conclude that yield gaps in rainfed rice in Kilombero floodplain are large, but that a site- and system-specific adaptation of crop management can close much of the exploitable yield gap and increase grain yields by 0.7–4.8 t ha−1. Similar benefits may be obtained in other hydrologically variable floodplain environments of the region and beyond.

scholarly journals Large scale assessment of the production process and rice yield gap analysis by comparative performance analysis and boundary-line analysis methods

2019 ◽  
Vol 14 (2) ◽  
pp. 123-131 ◽  
Author(s):  
Ahmad Gorjizad ◽  
Salman Dastan ◽  
Afshin Soltani ◽  
Hosein Ajam Norouzi
Keyword(s):  
Gap Analysis ◽  
Rice Yield ◽  
Relative Yield ◽  
Boundary Line ◽  
Yield Gap ◽  
Potential Yield ◽  
Comparative Performance ◽  
Actual Yield ◽  
Yield Gap Analysis ◽  
Line Analysis

To reduce the yield gap, specifying yield constraints in a particular area is necessary. A complete yield gap assessment method must provide information regarding potential yield, actual yield, and causes of the gap and their importance. Therefore, documenting the production process to explain crop management factors in each area is very important. The objective of the study was to perform a rice yield gap analysis by using comparative performance analysis (CPA) and boundary-line analysis (BLA). Data were gathered from about 100 paddy fields in Neka, eastern Mazandaran province, one of the major rice producing regions in Iran, in 2015 and 2016. All agricultural practices from nursery preparation to harvest have been recorded for improved rice cultivars. CPA focuses on the ability to estimate potential yield and the reason for a yield gap. Boundary lines were fitted to the edge of the data cloud of crop yield versus management variables in data from paddy fields monitoring. The documenting analysis shows that the range of paddy yield in 100 fields varied from 6100 to 8200 kg ha–1. Potential yields were 9241 kg ha–1 for CPA method, and 7999 kg ha–1 for BLA method. Furthermore, yield gap predicted 2047 kg ha–1 for CPA method and 874 kg ha–1 for BLA method. In BLA, the average relative yield and relative yield gap of the 13 investigated variables were 89.75% and 10.25% respectively. These results show the importance of each management factor in yield gap. It was concluded that CPA and BLA as applied in the study is a cheap and simple method that, without the need for expensive experimentation, is able to detect yield gap and its causes in a district. From these results, it can be said that the calculated yield gap is close to the definition given for the utilised yield gap and shows the difference between the actual yield and attainable yield in relation to the environmental conditions of the region.

scholarly journals Yield Gap Analysis, Economics, Adoption, and Horizontal Spread of Tomato (Lycopersicon esculentum Mill.) Cultivation through Front Line Demonstration in Eastern Uttar Pradesh, India

2019 ◽  
Vol 5 (02) ◽  
pp. 124-128
Author(s):  
P. K. Misra ◽  
S. N. Singh ◽  
Pardeep Kumar ◽  
M. K. Pandey
Keyword(s):  
Gap Analysis ◽  
Uttar Pradesh ◽  
Cost Ratio ◽  
Yield Gap ◽  
Tomato Crop ◽  
Tomato Production ◽  
Net Return ◽  
Horizontal Spread ◽  
Eastern Uttar Pradesh ◽  
The Impact

The present study was undertaken to found the yield gap through FLDS on tomato crop. The Krishi Vigyan Kendra, Varanasi conducted Frontline demonstration on 10 farmers for each year since 2010-11, 2011-12 and 2012-13 in different locations of Varanasi district. Frontline demonstrations were conducted on tomato by the active participation of the farmers with the objective of improved technologies of tomato production potential. Use of hybrid variety, balanced use of fertilizer on the basis soil testing report and integrated pest and disease management etc are the main technologies to be tested in this demonstration. Tomato is a major vegetable crop of eastern Uttar Pradesh. But the productivity of tomato are very low in this district due to lack of knowledge and partial adoption of recommended package of practice by tomato cultivators. The data of study revealed to the cost of cultivation, production, productivity, gross return and net return were collected as per schedule and analyzed. The result of present study revealed that average highest yield in demonstration was recorded 643.83 q ha-1 was obtained in demonstrated plot over control (522.66 q ha-1) with an additional yield of 121.17 q ha-1 and the increasing the average tomato productivity by 23.88 per cent. The extension gap and technology gap ranged between 119.50 to 122.50 and 93.50 to 119.50 q ha-1, respectively, with the technology index of 16.51% during the demonstration years. Besides this, the demonstrated plots gave higher gross return, net return with higher benefit cost ratio when compared to farmer’s practice. In present study efforts were also made to study the impact of FLD on horizontal spread which was increased 269.38%, if appropriate package and practices are followed.

Yield and nutrient gap analysis for potato in northwest China

2018 ◽  
Vol 156 (8) ◽  
pp. 971-979 ◽  
Author(s):  
X. Liu ◽  
S. Li ◽  
P. He ◽  
P. Zhang ◽  
Y. Duan
Keyword(s):  
Gap Analysis ◽  
Potato Production ◽  
Northwest China ◽  
Fertilizer Application ◽  
Potato Yield ◽  
High Yield ◽  
Yield Gap ◽  
Partial Factor Productivity ◽  
Attainable Yield ◽  
On Farm

AbstractAnalysis of the potato yield gap and the corresponding nutrient gap can help in devising strategies and measurements to increase productivity for closing the gaps through improved practices. On-farm experiments conducted in the main potato production areas of northwest China were used to determine attainable yield. Official statistical data were used to determine the actual on-farm yield. Yield gap was the difference between attainable yield and actual on-farm yield. Nutrient gap was calculated by dividing the size of yield gap by partial factor productivity. Results indicated that nitrogen (N), phosphorus (P) and potassium (K) fertilization increased potato yield by an average of 1169–7625, 2937–5336 and 2331–7338 kg/ha, respectively. The maximum attainable yields (the 90th percentile yields) were 50 145, 37 855, 30 261 and 56 616 kg/ha and the average actual on-farm yield were 14 179, 16 732, 10 271 and 19 990 kg/ha in the Inner Mongolia Autonomous Region (IMAR), Gansu, Ningxia and Qinghai provinces, respectively. In the above four regions, yield would need to increase by 165, 70, 112 and 121% from actual yield to reach 75% of attainable yield. Compared with recent 3-year average NPK rates by farmers, the total NPK rates need to increase by 90.1–134.3% for IMAR, 42.9–69.2% for Gansu, 68.1–111.2% for Ningxia and 48.1–83.8% for Qinghai to improve productivity to near the 75% attainable yield. In conclusion, the high yield responses to fertilizer application provide opportunities to close the large yield gaps through balanced nutrition.

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