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<p>Water, energy and environment are inextricably linked, and exhibit a close nexus with crop production, ecosystem sustainability and food security. Chemical fertilizers and irrigation water were the major hot spots of water and energy footprints, with significant impact on carbon (C) footprints that largely impacts ecosystem sustainability. The non-renewable energy (NRE) shared ~ 59–92%, while renewable energy (RE) comprised ~ 8–41% of total energy input (E<sub>I</sub>) in field crops. The direct energy (DE) and indirect energy (IDE) sources comprised ~ 10–74% and 26–90% of E<sub>I</sub>, respectively. In vegetable and fruit crops, the RE and NRE shared ~ 1.4–24% and 76–98.6%, whilst the DE and IDE sources shared ~ 14–90% and 10–86% of E<sub>I</sub>. The energy ratio varied between 1.49–5.00 for rice, 1.75–7.50 for wheat, 3.80–7.41 for maize and 0.70–4.80 for cotton ecosystems. The corresponding specific energy ranged between 6.4–16.7, 4.0–8.42, 3.80–6.93 and 4.99–19.2&#xa0;MJ&#xa0;kg<sup>−1</sup>, respectively. The greenhouse gases emission in crop production was related linearly to E<sub>I</sub> in crop production and was substantially decreased under optimized production situations. The study highlights the need of intensified agricultural extension efforts to disseminate the robust technological interventions for resource use optimization for decreased energy and C footprints in crop production for long-term system sustainability. The artificial neural networks and adaptive-neuro fuzzy inference system of variable complexity viz. single and multi-layered sub-networks developed for various crops in different agro-ecological regions could be highly helpful to the researchers and policymakers for designing future strategies for enhancing ecosystems’ resilience and environmental sustainability.</p>

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Water-energy-environment nexus for global food security and ecosystem sustainability-insight from energy budgeting, optimization and artificial intelligence

  • 期刊论文

  • 发表日期：

    2025年2月25日

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  • Gagandeep Kaur

摘要

Water, energy and environment are inextricably linked, and exhibit a close nexus with crop production, ecosystem sustainability and food security. Chemical fertilizers and irrigation water were the major hot spots of water and energy footprints, with significant impact on carbon (C) footprints that largely impacts ecosystem sustainability. The non-renewable energy (NRE) shared ~ 59–92%, while renewable energy (RE) comprised ~ 8–41% of total energy input (EI) in field crops. The direct energy (DE) and indirect energy (IDE) sources comprised ~ 10–74% and 26–90% of EI, respectively. In vegetable and fruit crops, the RE and NRE shared ~ 1.4–24% and 76–98.6%, whilst the DE and IDE sources shared ~ 14–90% and 10–86% of EI. The energy ratio varied between 1.49–5.00 for rice, 1.75–7.50 for wheat, 3.80–7.41 for maize and 0.70–4.80 for cotton ecosystems. The corresponding specific energy ranged between 6.4–16.7, 4.0–8.42, 3.80–6.93 and 4.99–19.2 MJ kg−1, respectively. The greenhouse gases emission in crop production was related linearly to EI in crop production and was substantially decreased under optimized production situations. The study highlights the need of intensified agricultural extension efforts to disseminate the robust technological interventions for resource use optimization for decreased energy and C footprints in crop production for long-term system sustainability. The artificial neural networks and adaptive-neuro fuzzy inference system of variable complexity viz. single and multi-layered sub-networks developed for various crops in different agro-ecological regions could be highly helpful to the researchers and policymakers for designing future strategies for enhancing ecosystems’ resilience and environmental sustainability.