Wert-Berater, Inc. is an independent greenhouse and controlled-environment agriculture feasibility study consultant preparing lender-grade analyses for commercial greenhouses, hydroponic operations, vertical farms, and other CEA projects. Our studies evaluate crop yield per square foot, production cycles, crop mix, energy load, utility rates, labor, input cost, market pricing, retailer or wholesale offtake, facility capital, stabilization, debt-service coverage, and downside sensitivity. 4,000+ engagements since 1998 covering $41.2 billion in evaluated project value.
Controlled-environment agriculture trades weather risk for energy cost and capital intensity. The grower gains year-round production and yields per square foot no field can match, and accepts in exchange a heavy fixed cost base that must be carried whether or not the crop sells well. Feasibility therefore turns on two numbers held together: yield per square foot per year at a realistic price, and the delivered energy cost of holding the environment that produces it. A project that is right about yield and wrong about energy is not feasible.
Methodology uses documented operating results from comparable facilities running the same crop and system type, USDA NASS floriculture and specialty-crop data, USDA Agricultural Marketing Service terminal and shipping-point price series for the crop and season, university Cooperative Extension controlled-environment production budgets, and the utility tariff schedules actually applicable to the site. Where the operation has production history it governs. Equipment-vendor yield and energy projections are treated as claims requiring independent corroboration.
Every Wert-Berater financial model is fully linked with no hardcoded values, so any reviewer can stress any input. Deliverables comprise a complete narrative report and the linked Excel model, with ten-year pro forma, sensitivity analysis at ±5, 10, and 15 percent, interest-rate stress from +0.5 to +3.0 percent, and ratio analysis benchmarked against comparable CEA operating data and published extension budgets.
CEA projects are financed through a range of structures and the study is written to the one that applies. USDA Rural Development programmes reach rural controlled-environment enterprises in defined circumstances, as the firm’s own USDA Business & Industry greenhouse engagement demonstrates; Farm Credit System institutions and Farm Service Agency programmes lend to horticultural production; SBA programmes may apply where the enterprise qualifies as a small business rather than as primary agricultural production; and conventional lenders set their own coverage standard, commonly but not universally 1.20x. Eligibility is determined by the lender and the agency on the applicant’s facts, and we do not assume a programme applies to a given project.
Wert-Berater completed a $17,350,000 controlled-environment greenhouse feasibility study in Radium Springs, New Mexico in 2025 under USDA Business & Industry, evaluated under 7 CFR 5001.203(i), where the study found the project financially feasible with repayment capacity demonstrated for all scheduled USDA-guaranteed debt. That engagement is directly on point for commercial greenhouse credit: it required converting a horticultural production plan into defensible year-round throughput, pricing a substantial energy and capital load, and documenting the result to agency standard. It sits within a broader record of 4,000+ engagements since 1998 covering $41.2 billion in evaluated project value. Independence is non-negotiable: determinations follow the evidence and are not revised under pressure.
A greenhouse or CEA feasibility study determines whether a specific structure, growing a specific crop mix, in a specific climate and utility market, selling into a specific channel, services proposed debt. The analysis is driven by two linked quantities — production per square foot per year and the cost of maintaining the environment that delivers it — and by the honesty of the offtake evidence behind the price.
Yield per square foot per year is the revenue engine of a CEA project and the assumption most frequently overstated. It is built from documented results achieved with the same crop, in the same system type, under a comparable light and climate regime — not from a design specification and not from a growth-model calculation. Where the sponsor has an operating record, it governs. Where the project is new, the projection is anchored to independently verifiable performance at comparable facilities and held below the comparable mean through the establishment period.
The annual figure is a product of yield per cycle and cycles per year, and both are examined. Cycle length depends on the crop, the cultivar, and the light and temperature regime actually provided; turns per year must also account for changeover — harvest, clean-down, and replant — which consumes days that a naive division of 365 by cycle length ignores. Where the crop is harvested continuously rather than in discrete cycles, the model reflects the ramp to full production and any seasonal variation in rate.
Quality grade-out is modeled explicitly. Gross production and marketable production are different numbers, and the difference is revenue. The model applies a grade-out consistent with the operation’s demonstrated performance or with comparable operating evidence, and treats improvement in grade-out as a projection requiring support rather than as a given.
Energy is the cost that most often determines whether a CEA project works, and it is modeled at the site rather than by benchmark. The analysis builds a load profile from the structure’s thermal characteristics, the climate the site actually experiences month by month, the environmental set points the crop requires, and the lighting regime specified. That profile is then priced against the utility’s actual tariff, including demand charges, time-of-use periods, and seasonal rate structures where they apply.
Demand charges deserve particular attention because they are frequently omitted from sponsor projections. A facility with substantial supplemental lighting can establish a peak demand that carries a charge independent of consumption, and in some tariffs that charge is a material share of the total energy bill. Similarly, a heating load calculated on average winter temperature will understate the cost of the coldest weeks, when the facility must hold set point against the largest differential.
Because energy is both large and volatile, it receives its own sensitivity treatment. The model tests the project against sustained increases in energy price and reports the rate at which coverage fails, which for an energy-intensive facility is often a more binding constraint than crop price. Where a project proposes on-site generation, cogeneration, or renewable supply, that is modeled as a separate investment with its own capital cost and its own performance assumptions rather than as an assumed reduction in the energy line.
The choice of production system determines the shape of both the capital budget and the operating cost structure, and the study models the system actually specified. A passive or semi-closed glasshouse, a fully closed vertical system, and a hoop structure with minimal control are different businesses with different cost bases and different achievable yields; borrowing yield assumptions from one while using the capital cost of another produces a projection that cannot occur.
Lighting is examined for its capital cost, its replacement cycle, its electrical demand, and its heat contribution, since supplemental lighting adds a cooling load in warm periods while offsetting heating in cold ones. HVAC and dehumidification are modeled for the crop’s transpiration load rather than as a generic building system, because in a densely planted facility moisture removal is a continuous and substantial energy demand. Equipment replacement cycles are carried in the pro forma rather than deferred, since lighting, environmental controls, and irrigation components have economic lives materially shorter than the structure and shorter than a long amortisation.
Labor is modeled from the hours the crop actually requires through its cycle rather than as a percentage of revenue. Transplanting, training, pruning, scouting, harvest, and packing each carry distinct labor demands, and for many high-value CEA crops the harvest and packing operation dominates. The model builds the requirement per cycle and converts it to a full-time-equivalent schedule across the year, which for a continuously harvested crop is steady and for a batch crop is sharply peaked.
Availability is assessed alongside cost. A facility requiring a substantial seasonal labor draw in a tight rural market carries an execution risk that a wage assumption does not capture, and the study identifies it. Wages are modeled at the rate the operation must actually pay in its own labor market, including payroll burden, and any automation proposed to reduce labor is treated as a capital investment with its own cost and its own realistic effect rather than as an assumed saving.
Channel determines price, and the difference between channels is large enough to decide feasibility on its own. Product sold to a retail chain, to a wholesaler, to a foodservice distributor, or direct to consumer realises materially different net prices and carries materially different packaging, delivery, and service costs. The model prices the product in the channel it will actually move through, net of packaging, freight, and any category or promotional allowance the channel requires.
Offtake evidence is graded. A supply agreement specifying volume, specification, term, and a pricing mechanism is strong evidence. A letter of intent is weak evidence. An expression of interest from a buyer who has not committed to volume is not a basis for projecting revenue. Where projected revenue depends on a channel the operation has not yet supplied, the base case excludes it and the dependency is stated. Retail programmes in particular carry requirements — food-safety certification, consistent year-round volume, service levels, and category pricing — that a start-up may not be able to meet in its first year, and the study tests whether the operation can actually perform against the agreement it proposes to rely on.
Price is modeled from published market series for the crop, grade, and season — USDA Agricultural Marketing Service shipping-point and terminal reports where they cover the commodity — rather than from a single current quotation. CEA producers frequently sell into markets where field production sets the price floor for part of the year, so the seasonal pattern matters: a facility whose economics depend on winter premiums must show what it earns in the months when field supply is abundant and prices are lowest.
Market saturation is a genuine and current risk in several CEA categories, where substantial capacity has been added regionally in a short period. The analysis considers announced and recently commissioned capacity within the market the project intends to serve, because a price series that reflects conditions before that capacity arrived may not describe the market the project will enter. Where the crop is one in which several large operations have failed or contracted, that history is treated as relevant evidence rather than ignored.
Vertical and fully closed systems carry a specific analytical hazard: the performance case is often supplied by the party selling the equipment. Vendor yield figures, energy consumption estimates, and labor projections are claims with a commercial interest attached, and they are not accepted as independent evidence. The study corroborates them against operating results at facilities actually running the system at commercial scale, and where such results are unavailable, that absence is reported as a material uncertainty rather than resolved in the vendor’s favour.
The particular exposures of fully closed systems are addressed directly. Energy cost per unit of production is structurally higher than in a glasshouse using natural light, so the crop must carry a price premium sufficient to cover it, and that premium must be evidenced in the market rather than assumed. Capital cost per square foot is high, which raises the yield required to service debt. Stabilization takes longer than sponsors typically project, and working capital must fund the gap. And the technology risk is real: a system dependent on a single vendor for controls, spares, and support carries a continuity exposure the study identifies.
The financial conclusion is a coverage determination under stress. The model produces a ten-year pro forma with sensitivity at ±5, 10, and 15 percent applied to yield, price, and energy cost independently and in combination, plus interest-rate stress from +0.5 to +3.0 percent in half-point increments.
The decisive case for most CEA projects pairs a yield shortfall with an energy-cost increase, because a facility that produces less while costing more to operate loses margin from both directions against a fixed cost base that does not shrink. The model also reflects stabilization honestly: design yield is rarely achieved in the first cycles, and the study shows the working capital required to reach it. Break-even is expressed as the production per square foot required at the modeled price, and as the price required at the modeled yield, so the lender can see how much margin of safety the credit carries. An explicit statement of conditions identifies the information relied upon and the assumptions that would change the finding.
This is an economic and financial feasibility analysis. It does not replace HVAC, structural, electrical, or horticultural engineering, and it is not a growing protocol or a system design. Where a project requires structural engineering, mechanical design, an energy model prepared by a qualified engineer, or a horticultural production programme, those are professional inputs to the economic analysis and the study identifies where it has relied on them.
Related engagements: for field production of the same or rotational crops see crop farming feasibility studies; for post-harvest cooling, storage, and distribution see cold storage feasibility studies; and where a producer proposes to process or brand its own production to capture additional margin, a USDA Value-Added Producer Grant feasibility study addresses that programme directly.
A greenhouse or CEA feasibility study consultant determines whether a specific structure, growing a specific crop mix, in a specific climate and utility market, selling into a specific channel, services proposed debt. The analysis is driven by production per square foot per year and by the cost of maintaining the environment that delivers it.
It also covers crop cycles and turns, grade-out, labor per harvest cycle, offtake evidence and channel pricing, market saturation, capital cost, the stabilization ramp, and coverage under combined yield and energy stress.
From documented results achieved with the same crop, in the same system type, under a comparable light and climate regime — not from a design specification or a growth-model calculation. Where the sponsor has an operating record it governs; where the project is new, the projection is anchored to independently verifiable performance at comparable facilities and held below the comparable mean through establishment.
The annual figure is yield per cycle multiplied by cycles per year, with changeover time deducted. Grade-out is applied explicitly, because gross production and marketable production are different numbers and the difference is revenue.
At the site rather than by benchmark. The analysis builds a load profile from the structure’s thermal characteristics, the climate the site actually experiences month by month, the environmental set points the crop requires, and the lighting regime specified, then prices it against the utility’s actual tariff.
Demand charges, time-of-use periods, and seasonal rate structures are included, since a facility with substantial supplemental lighting can establish a peak demand charge that is a material share of the bill. Energy receives its own sensitivity treatment, and the model reports the energy price at which coverage fails — often a more binding constraint than crop price.
By dividing marketable annual production by the productive growing area actually in crop, not by the building footprint. Aisles, headhouse, packing, and mechanical space are excluded from the productive denominator, and in multi-tier systems the productive area is the total growing surface rather than the floor plan.
The resulting figure is compared against documented performance at comparable facilities running the same crop and system, and any material divergence is examined rather than accepted.
Cycle length is set by the crop, the cultivar, and the light and temperature regime actually provided, and turns per year account for changeover — harvest, clean-down, and replant — which consumes days that dividing 365 by cycle length ignores.
Where the crop is harvested continuously rather than in discrete cycles, the model reflects the ramp to full production and any seasonal variation in rate rather than applying a flat weekly output.
Evidence is graded. A supply agreement specifying volume, specification, term, and a pricing mechanism is strong evidence. A letter of intent is weak. An expression of interest without volume commitment is not a basis for projecting revenue, and where projected revenue depends on a channel the operation has not yet supplied, the base case excludes it.
We also test whether the operation can actually perform against the agreement it relies on. Retail programmes carry food-safety certification, consistent year-round volume, service-level, and category-pricing requirements that a start-up may not meet in its first year.
With particular scepticism, because the performance case is often supplied by the party selling the equipment. Vendor yield figures, energy estimates, and labor projections are claims with a commercial interest attached and are not accepted as independent evidence.
We corroborate them against operating results at facilities running the same system at commercial scale. Where such results are unavailable, that absence is reported as a material uncertainty rather than resolved in the vendor’s favour. Structurally higher energy cost per unit, high capital cost per square foot, longer stabilization, and single-vendor dependency for controls and spares are each addressed explicitly.
From the hours the crop actually requires through its cycle rather than as a percentage of revenue. Transplanting, training, pruning, scouting, harvest, and packing carry distinct demands, and for many high-value CEA crops harvest and packing dominate.
The requirement is converted to a full-time-equivalent schedule across the year — steady for a continuously harvested crop, sharply peaked for a batch crop. Wages reflect the operation’s actual labor market including payroll burden, availability risk is identified where the draw is substantial, and proposed automation is treated as a capital investment rather than an assumed saving.
By solving the model for the point at which cash flow after operating costs exactly meets debt service, then expressing it two ways: the production per square foot required at the modeled price, and the price required at the modeled yield.
Both are reported so the lender can see how much margin of safety the credit carries in each direction. Because CEA carries a heavy fixed cost base, break-even utilisation is typically high, and the study states it plainly rather than reporting only a base-case ratio.
The fee is fixed and quoted within one business day of the initial inquiry. It does not vary with the finding and is never contingent on loan approval. Because scope varies with facility size, crop mix, system type, and the lending programme involved, we quote after a brief intake conversation rather than publishing a schedule.
Standard delivery is ten to fifteen business days from receipt of a complete data room, with rush delivery available. An engagement typically requires facility drawings and equipment specifications, the crop plan and target yields with their basis, twelve months of utility bills or the applicable tariff schedule for a new site, any vendor performance projections with supporting data, offtake agreements or buyer correspondence, construction bids, three years of financial statements where an operating history exists, and the proposed loan term sheet.
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Wert-Berater, Inc. is an independent provider of feasibility studies and other related services. The firm does not provide financing or equity investment advice, and does not arrange, broker, or place debt or equity capital of any kind.
All appraisal assignments are performed by Bruce E. Jones, MAI, ASA-GC, BCA, CMEA, a member of the Appraisal Institute since 2006, a staff member of Wert-Berater, Inc. and owner of Special Purpose Realty Valuation.