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Exploring the Financial Viability of Greenhouse Tomato Growers under Climate Change-Induced Multiple Stress

January 2024

DOI:10.3390/proceedings2024094016

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Conference: International Conference of the Hellenic Association of Agricultural Economists

Authors:

Giorgos Diakoulakis

Agricultural Economics Research Institute

In this study, we implement a linear programming farm model to explore the impact of climate change-induced multiple stress on the financial viability of greenhouse tomato growers. The main results are that new technologies and innovations can compensate growers for any profit loss associated with climate change. However, if the cost of adaptation is high enough, then its financial benefits are constrained by how efficient these innovations are in terms of productivity. We did not observe significant differences in input use between ‘innovative’ and ‘conventional’ production, and the yield under the adoption of new technologies was higher compared to ‘conventional’ production.

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Citation: Diakoulakis, G.N.;

Tsiboukas, K.; Savvas, D. Exploring the

Financial Viability of Greenhouse

Tomato Growers under Climate

Change-Induced Multiple Stress.

Proceedings 2024,94, 16.

https://doi.org/10.3390/

proceedings2024094016

Academic Editor: Eleni

Theodoropoulou

Published: 23 January 2024

Licensee MDPI, Basel, Switzerland.

This article is an open access article

distributed under the terms and

conditions of the Creative Commons

Attribution (CC BY) license (https://

creativecommons.org/licenses/by/

4.0/).

proceedings

Proceeding Paper

Exploring the Financial Viability of Greenhouse Tomato Growers

under Climate Change-Induced Multiple Stress †

Giorgos N. Diakoulakis 1, * , Konstantinos Tsiboukas 1and Dimitrios Savvas 2

1Laboratory of Agribusiness Management, Department of Agricultural Economics and Rural Development,

Agricultural University of Athens, Iera Odos 75, 11855 Athens, Greece; tsiboukas@aua.gr

2Laboratory of Vegetable Production, Department of Crop Production, Agricultural University of Athens,

Iera Odos 75, 11855 Athens, Greece; dsavvas@aua.gr

*Correspondence: di_gi@aua.gr

†Presented at the 17th International Conference of the Hellenic Association of Agricultural Economists,

Thessaloniki, Greece, 2–3 November 2023.

Abstract: In this study, we implement a linear programming farm model to explore the impact of

climate change-induced multiple stress on the ﬁnancial viability of greenhouse tomato growers. The

main results are that new technologies and innovations can compensate growers for any proﬁt loss

associated with climate change. However, if the cost of adaptation is high enough, then its ﬁnancial

beneﬁts are constrained by how efﬁcient these innovations are in terms of productivity. We did not

observe signiﬁcant differences in input use between ‘innovative’ and ‘conventional’ production, and

the yield under the adoption of new technologies was higher compared to ‘conventional’ production.

Keywords: linear programming; farm model; greenhouse tomato; climate change

1. Introduction

The relationship between climate change and agriculture has a long tradition in the

scholarly literature, e.g., [

–

]. Additionally, during the last couple of years, the results

of climate change, like high temperature and drought, have signiﬁcantly affected the

ﬁnancial viability of producers [

]. To this end, many scholars call for the adoption of

new technologies and innovations both as a mean towards environmental improvements

but also as a mean towards producers’ (or growers’) ﬁnancial stability [6].

Furthermore, mathematical programming farm models have been excessively used

to understand farmers’ (or growers) production choices, e.g., [

]. Among them, linear

programming farm models (thereafter, LP-FM) have been used to analyze production plans

in the agricultural sector, e.g., [9].

In this study, we are interested in the impact of climate change-induced multiple stress,

namely increased heat, draught, and salinity. Particularly, we utilize a simple LP-FM to

explore two vital questions. First, how climate change-induced multiple stress will affect

the ﬁnancial viability of Mediterranean greenhouse tomato growers. Second, how the

adoption of new technologies and innovations can compensate growers for any proﬁt

losses due to climate change-induced multiple stress.

2. Materials and Methods

Our methodology can be divided into the following steps. First, we interviewed

22 greenhouse tomato growers (both in-person and online), where approximately 72.72%

of the responders were located in Crete, whereas the remaining ones were located in the

region of Peloponnese. The rationale of using Crete as the case study is because Crete,

followed by Peloponnese, is the leading region in greenhouse vegetable production in

Greece [10].

Proceedings 2024,94, 16. https://doi.org/10.3390/proceedings2024094016 https://www.mdpi.com/journal/proceedings

Proceedings 2024,94, 16 2 of 3

The second step was to design an LP-FM. Speciﬁcally, we assumed a representative

greenhouse beef tomato grower whose objective was to choose their annual deci-hectare

amount of fertilizers, chemical substances for pest management, the number of plants,

and water consumption, such that her annual per deci-hectare gross margin was to be

maximized, subject to both technical and ﬁnancial constraints. The choice of these inputs

(decision variables) was selected based on the answers given by the interviewed growers.

Also, the upper and lower limits of the constraints were determined by the answers given

by the growers.

The third step was to estimate the production coefﬁcients. To do so, an approximated

linear production function was used. The result of this estimation was used afterwards to

the LP-FM to determine the optimal input use under the ‘current situation’ (or business-as-

usual scenario). These values serve as a comparison between the current situation and our

hypothetical scenarios.

The ﬁnal step was to implement three hypothetical scenarios on the impact of climate

change-induced multiple stress on both the production and ﬁnancial efﬁciency of a ‘conven-

tional’ production system: a low, a moderate, and a high impact scenario. In each of these

three scenarios, further assumptions were made on the production and ﬁnancial efﬁciency

of a production system that utilizes new technologies and innovations that exhibit higher

tolerance to climate change compared to ‘conventional’ one.

3. Results

The main results of our analysis can be summarized as follows. First, the adoption of

new technologies and innovations can compensate greenhouse tomato growers, even in

cases where the production efﬁciency of these technologies and innovations is close to the

‘conventional’ one.

Second, cost considerations might be important, especially when the production

efﬁciency of these new technologies and innovations is close to the ‘conventional’ one.

Third, we did not ﬁnd any signiﬁcant difference in input use between ‘conventional’

production and production that utilizes new technologies and innovations. However, if

the grower is constrained to produce a certain level of yield, then the adoption of new

technologies and innovations that are more tolerant to climate change is likely to entail

environmental improvements in terms of less input use, as well.

Finally, the yield been the produced crops in the latter cases exceeds that under the

former one in almost every simulation. This result highlights potential social beneﬁts

because the adoption of new technologies and innovations can ‘secure’ a potential food

supply under severe climate change conditions.

4. Conclusions

In this article, we tried to explore whether the adoption of new technologies and

innovations can compensate greenhouse tomato growers for their proﬁt losses due to

climate change-induced multiple stress. The answer is yes, but the cost of adaptation

should also be considered. Importantly, our analysis highlights that the adoption of new

technologies and innovations can cover any excess demands for tomato. Thus, it might be

down to policymakers to incentivize the transition to sustainable agriculture, especially if

‘securing’ food supply is their primal objective.

However, some limitations should be spelled out. First, our sample size is small,

which may reduce the robustness of our estimated coefﬁcients. Secondly, we gathered

information by performing in-person interviews and by email. In most cases, growers did

not keep a detail logbook regarding their production activities and the costs associated

with them. Thus, our data are likely to exhibit some level of noise. The implication of these

two limitations is that we exhibit high p-values, meaning that the estimated coefﬁcients

should be interpreted with caution. Finally, we focused our analysis on the identiﬁcation of

only four inputs. However, factors like labor, energy, and electricity consumption could be

important as well. Thus, an extension of this study is left as an area for future research.

Proceedings 2024,94, 16 3 of 3

Author Contributions: Conceptualization, G.N.D. and K.T.; methodology, G.N.D. and K.T.; software,

G.N.D.; formal analysis, G.N.D.; resources, D.S. and K.T.; data curation, G.N.D. and D.S.; writing—

original draft preparation, G.N.D.; writing—review and editing, G.N.D., K.T. and D.S.; supervision,

K.T. and D.S.; project administration, D.S.; funding acquisition, D.S. All authors have read and agreed

to the published version of the manuscript.

Funding: This research was supported by PRIMA 2018-11 within the project ‘VEGADAPT: Adapting

Mediterranean vegetable crops to climate change-induced multiple stress’, a Research and Innovation

Action funded by the Greek General Secretariat for Research and Innovation (GSRI) and supported

by the European Union.

Institutional Review Board Statement: Not applicable.

Informed Consent Statement: Informed consent was obtained from all subjects involved in the

study.

Data Availability Statement: The raw data can be found at https://doi.org/10.5281/zenodo.8325730

(accessed on 7 September 2023). Also, we used a slightly modiﬁed version of the GAMS code that

can be found at https://doi.org/10.5281/zenodo.7024627 (accessed on 26 August 2022).

Acknowledgments: We would like to express our sincere thanks to Dimitrios Kremmydas for his

invaluable insights and guidance during the design of the linear programming farm model.

Conﬂicts of Interest: The authors declare no conﬂicts of interest. The funders had no role in the

design of the study; in the collection, analyses, or interpretation of the data; in the writing of the

manuscript; or in the decision to publish the results.

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