Suitable Integrated Farming System Models in Terms of Energetics, Greenhouse Gas Emissions and Employment Generation for the Small and Marginal Farmers

Food grain production has multiplied over the last two decades in India, but natural resources are overexploited in modern farming. Farmers, especially those with small and marginal holdings, are suffering losses more often than not, the cost of production is increasing year after year, and profits are not up to the necessary levels. To address such challenges, there has been a broad recognition of the importance of employing farming system approaches in research. The cultivation of cropping systems with orchard crops and livestock components can play a significant role in the optimal utilization of resources, enhancing energy use efficiency as well as the eco-efficiency index, and reducing carbon footprints. This study was carried out to create a suitable IFS model with high economic and energy efficiency for small-holder farmers in India’s southern plateau and hills with a negligible impact on the environment. The following were the seven models: M1: Rice − Groundnut; M2: Rice − Groundnut, Pigeonpea + Sweetcorn (1:3) − Bajra, Bt cotton + Greengram (1:2) − Maize; M3: Rice − Groundnut, Pigeonpea + Sweetcorn (1:3) − Bajra, Pigeonpea + Maize (1:3) − Sunhemp; Napier grass, Sheep (5 + 1); M4: Rice − Groundnut, Pigeonpea + Sweetcorn (1:3) − Bajra, Bt cotton + Greengram (1:2) − Maize, Pigeonpea + Maize (1:3) − Sunhemp, Poultry unit; M5: Guava, Hedge Lucerne, Napier grass, Bt cotton + Greengram (1:2) − Maize, Sheep (5 + 1); M6: Guava, Bt cotton + Greengram (1:2) − Maize, Rice − Groundnut, Poultry; M7: Rice − Groundnut, Pigeonpea + Sweetcorn (1:3) − Bajra, Pigeonpea + Maize (1:3) − Sunhemp; Napier grass, Hedge lucerne, Poultry (100), Sheep (5 + 1). Model M1 was used to represent the local region, and the other models were compared in terms of economics, energetics, greenhouse gas emissions, and employment creation. The M7 and M3 models, according to the results, have higher economic efficiency (₹342.3 day−1, ₹263.7 day−1), increase output energy (228,529 and 183,231 MJ) net energy (258,184 and 198,920 MJ), produce net negative emissions (−2842 and −2399 kg CO2 eq.), and create jobs year-round (112.5 and 110.5 man days year−1), respectively. This is primarily because they have multiple highly efficient components that make them viable for Telangana’s small and marginal farmers.

Authors

Institutions

Publication Details

Journal
Sustainability
Published
2024-11-21
DOI
https://doi.org/10.3390/su162310189
Primary Topic
Agriculture Sustainability and Environmental Impact
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Suitable Integrated Farming System Models in Terms of Energetics, Greenhouse Gas Emissions and Employment Generation for the Small and Marginal Farmers

Nallagatla Vinod Kumar, Mohamed A. Mattar, Ch. Pragathi Kumari, M. Sharath Chandra et al.
Sustainability
Agriculture Sustainability and Environmental Impact
article

Suitable Integrated Farming System Models in Terms of Energetics, Greenhouse Gas Emissions and Employment Generation for the Small and Marginal Farmers

Nallagatla Vinod Kumar, Mohamed A. Mattar, Ch. Pragathi Kumari, M. Sharath Chandra, Khalid M. Elhindi, Rayapati Karthik, Manthati Goverdhan, Rajan Bhatt, T. Ram Prakash, Danavath Saida Naik, Maparla Venkata Ramana
article en

Abstract

Food grain production has multiplied over the last two decades in India, but natural resources are overexploited in modern farming. Farmers, especially those with small and marginal holdings, are suffering losses more often than not, the cost of production is increasing year after year, and profits are not up to the necessary levels. To address such challenges, there has been a broad recognition of the importance of employing farming system approaches in research. The cultivation of cropping systems with orchard crops and livestock components can play a significant role in the optimal utilization of resources, enhancing energy use efficiency as well as the eco-efficiency index, and reducing carbon footprints. This study was carried out to create a suitable IFS model with high economic and energy efficiency for small-holder farmers in India’s southern plateau and hills with a negligible impact on the environment. The following were the seven models: M1: Rice − Groundnut; M2: Rice − Groundnut, Pigeonpea + Sweetcorn (1:3) − Bajra, Bt cotton + Greengram (1:2) − Maize; M3: Rice − Groundnut, Pigeonpea + Sweetcorn (1:3) − Bajra, Pigeonpea + Maize (1:3) − Sunhemp; Napier grass, Sheep (5 + 1); M4: Rice − Groundnut, Pigeonpea + Sweetcorn (1:3) − Bajra, Bt cotton + Greengram (1:2) − Maize, Pigeonpea + Maize (1:3) − Sunhemp, Poultry unit; M5: Guava, Hedge Lucerne, Napier grass, Bt cotton + Greengram (1:2) − Maize, Sheep (5 + 1); M6: Guava, Bt cotton + Greengram (1:2) − Maize, Rice − Groundnut, Poultry; M7: Rice − Groundnut, Pigeonpea + Sweetcorn (1:3) − Bajra, Pigeonpea + Maize (1:3) − Sunhemp; Napier grass, Hedge lucerne, Poultry (100), Sheep (5 + 1). Model M1 was used to represent the local region, and the other models were compared in terms of economics, energetics, greenhouse gas emissions, and employment creation. The M7 and M3 models, according to the results, have higher economic efficiency (₹342.3 day−1, ₹263.7 day−1), increase output energy (228,529 and 183,231 MJ) net energy (258,184 and 198,920 MJ), produce net negative emissions (−2842 and −2399 kg CO2 eq.), and create jobs year-round (112.5 and 110.5 man days year−1), respectively. This is primarily because they have multiple highly efficient components that make them viable for Telangana’s small and marginal farmers.

SustainabilityVol. 16(23)
King Saud University (SA), Professor Jayashankar Telangana Agricultural University (IN), Krishi Vigyan Kendra, Ghatkhed Amravati (IN)
King Saud University
Affordable and clean energy
Openalex Percentile: Top 79%
Agriculture Sustainability and Environmental Impact
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.