The company installed controls consisting of sensors and computer software, which automatically modulated compressor discharge and suction pressures to improve the coefficient of performance and to better adjust compressor operation to changes in refrigeration system cooling demand. The upgrade led to annual energy savings of 367,000 kWh as well as reduced operations and maintenance costs through more efficient system operation . The reported payback period, which included both electricity bill savings and reduced operations and maintenance costs, was around 2.6 years. Floating head pressure control. Floating head pressure control can be a particularly effective control strategy for reducing compressor energy consumption. Floating head pressure control allows compressor head pressures to move up or down with variations in ambient wet-bulb temperature, saving energy compared to fixed head pressure operation. However, additional energy is required for the condenser fan, which must be balanced with compressor energy savings. It is also important not to allow head pressure to go too low, as certain system demands might require minimum head pressures . Hackett et al. estimate a typical payback period of less than one year for floating head pressure control systems. A U.S. DOE sponsored energy audit at the Odwalla Juice Company’s facility in Dinuva, California, estimated that the use of floating head pressure control on the facility’s seven ammonia compressors would save the company nearly $108,000 per year in energy costs . Total estimated electricity savings were around 1 million kWh per year at a payback period of only six months. Birds Eye Walls, a UK based manufacturer of frozen foods, nft growing system implemented refrigeration controls that allowed for floating head pressure in its Gloucester, England, facility in 1994.

The controls led to a 30% lower head pressure on average, allowing the company to save around £150,000 in refrigeration costs annually . At an initial investment cost of less that £30,000 , the payback period was less than three months. Indirect lubricant cooling. Direct injection of refrigerant is an inefficient method for compressor cooling that can decrease the overall efficiency of screw-type compressors by as much as 5% to 10% . An indirect system is a more efficient option for lubricating and cooling screw-type compressors, in which a heat exchanger is used in conjunction with cooling tower water, a section of an evaporative condenser, or a thermosyphon system to cool compressor lubricant. Raising system suction pressure. In two-stage compressor systems, a simple way to save energy is to raise the suction pressure and temperature of the low-stage compressor when ambient temperatures decrease. It has been estimated that energy savings of about 8% can be realized in two-stage systems when suction temperatures are raised from -30 °F to -20 °F . Adjustable-speed drives on compressor motors. Adjustable-speed drives can be used in conjunction with control systems to better match compressor loads to system cooling requirements. The Industrial Refrigeration Consortium reports that ASDs used on compressors below a part-load ratio of about 95% will deliver performance equal to a fixed speed compressor but with lower electricity requirements. However, at near full load, ASDs are approximately 3% less efficient than fixed speed drives due to electrical power losses associated with the ASD controller. Adjustable-speed drives are thus most beneficial for refrigeration systems with large differences between required and installed condenser capacities . Galitsky et al. have estimated average refrigeration system energy savings of 10% from the use of ASDs on compressors. Naumes, Inc., an Oregon based company specializing in fruit growing, processing, storage, and juice production, recently upgraded their ammonia-based refrigeration system with computer controls and ASD compressors for more efficient matching of cooling demand and system load.

The new system saved the company a reported 741,000 kWh per year, with total annual energy savings of around $37,000 . The simple payback period was estimated at just over two years. As part of a planned expansion for its dairy facility in Portland, Oregon, WestFarm Foods installed a new compressor with a 350 hp ASD, which allowed the remaining system compressors to either be off or working efficiently at 100% load. Other upgrades included new refrigeration system controls and ASDs on the system’s evaporator fans. The totalsystem upgrade reduced annual refrigeration system energy consumption by nearly 40% and annual operating costs by around $75,000 . At an investment cost of $310,000, the payback period was estimated at roughly four years; however, energy efficiency investment incentives from Portland General Electric as well as a 35% tax credit from the Oregon Department of Energy helped reduce the final payback to around one year. In 2003, Oregon Freeze Dry, a manufacturer of freeze-dried fruits, vegetables, and other specialty foods, installed ASDs on its refrigeration system screw compressors at its Albany, Oregon, facility. The company also decided to replace an undersized eight inch suction line with a new 12 inch line. The energy savings of the ASD and suction line installations amounted to nearly 2 million kWh per year , while energy cost savings amounted to $77,700 per year . Compressor heat recovery. Where economically feasible, rejected heat can be recovered from compressors and used in other facility applications, such as space heating or water heating. Further details on this measure are provided in Chapter 10. Dedicating a compressor to defrosting. It has been reported that if one compressor of a large system can be dedicated to running at the pressure needed for the defrost cycle, while the other compressors can be run at lower system pressures, that the resulting energy savings can often justify the cost of the dedicated compressor .

Keeping condensers clean. Condensers should be checked regularly for dirt, ice buildup, or plugged nozzles, which can reduce heat transfer rates and thus raise the condensing temperature. Furthermore, water-cooled and evaporative condensers should be kept free of hard water or bacterial buildup, which can cause fouling, scaling, and clogging that can also lead to increased condensing temperatures. In general, a one degree Celsius increase in condensing temperature will increase operating costs by 2% to 4% . Badly corroded condensers should be replaced as soon as possible. Automatic purging of condensers. Periodic purging of evaporative condensers is needed to remove non-condensable gases , which can reduce refrigeration system efficiency by increasing system head pressure and impeding condenser heat transfer . Automatic purging systems can help refrigeration systems operate efficiently by ensuring purging occurs on a regular basis. Automatic purging systems can also reduce the refrigerant loss and labor costs associated with manual purging. Excel Logistics Ltd., an operator of cold storage facilities in the United Kingdom, installed a five-point automatic refrigeration purging system at their Glasgow, Scotland, facility in 1989. Previously, the company purged its system manually on a weekly basis, which was time consuming and often led to refrigerant loss. The automatic purging system featured computer controls and five different refrigeration system purge points: one at each end of thereceiver, one on each of the two condenser outlets, and one on the hot gas line. The company reported that the automatic purging system led to a 15% reduction in compressor energy use and £8,800 in annual energy savings . The simple payback period, nft hydroponic system including both energy and maintenance cost savings, was 10 months. Reducing condenser fan use. Sometimes condenser fans are operated continuously, even when the refrigeration system’s compressor isn’t running. This practice wastes energy. Wherever possible, the operation of condenser fans should be coupled to the operation of the system’s compressors to ensure that the fans are only run when needed. Reducing condensing pressure. This measure is similar to floating head pressure control for compressors . To reduce the energy required to compress refrigerant, condensing pressures and temperatures should be set as low as possible. Computer controls can be installed on condensing systems to minimize condensing temperatures and pressures based on ambient wet-bulb temperatures, as well as to optimize the use of condenser fans and water . Lowering the condensing temperature can reduce compressor energy use by around 2% to 3% for every degree Celsius of temperature reduction . Use of axial condenser fans. Air-cooled or evaporative condensers generally do not need high-pressure air, and thus axial fans are well suited for this application. Adjustable-speed drives on condenser fans. For refrigeration systems with large differences between installed and operating condensing capacity, the use of ASDs on condenser fans can lead to significant energy savings compared to fixed-speed condenser fans. Prior to installing ASDs, however, it is important to establish the extent to which the condensing pressure can be floated. On systems where floating head operation is stable, ASDs can lower condenser fan energy consumption by up to 40% compared to operating a fixed-speed condenser fan in on/off fashion .

Cycling of evaporator fans in cold storage. It is often possible to maintain adequate temperature in cold storage areas without continuously running evaporator fans. Where feasible, evaporator fans can be turned off or ramped down periodically using timers or variable-speed control systems to save electricity while still maintaining proper cold storage temperatures. The cycling of evaporator fans should be managed carefully, however, to avoid stratification and to ensure that solenoids are cycled properly . In 1996, Stahlbush Island Farms, a grower, canner, and freezer of fruits and vegetables in Corvalis, Oregon, installed timers to cycle the evaporator fans of its cold storage unit. Prior to the installation of the timers, evaporator fans were run close to 24 hours per day. By cycling the evaporator fans, the company was able to save around 133,000 kWh of electricity per year because the fans ran for fewer hours and the fan motors released less heat into the cold storage unit . The annual savings were estimated at $4,500 and, with a one-time implementation cost of $1,000, the simple payback period was around three months. Adjustable-speed drives on evaporator fans. Similar to ASDs on condenser fans, for refrigeration systems with excess evaporator capacity, the installation of ASDs can lead to significant energy savings compared to fixed-speed fans. The cost effectiveness of ASDs, however, depends on the number of hours the evaporator fans can be run under part-load conditions. In an analysis of a -20° Fahrenheit freezer with seven evaporators, the use of ASDs on evaporator fans at a load ratio of 50% required 20% lower power than fixed-speed fans under the same operating conditions . The U.S. DOE has supported the development of a simple evaporator fan controller for medium temperature walk-in refrigeration units, which is capable of varying fan speed is reported to reduce evaporator and compressor energy consumption by 30% to 50% . The controller regulates the speed of evaporator fan motors to better match cooling demands in the refrigeration cycle. The U.S. DOE estimates typical payback periods of one to two years. As of 2000, the controller had been installed in 300 refrigeration units and had led to cumulative energy savings of around $80,000. According to BC Hydro , evaporator fan controllers are not good candidates for freezers that run under 28° Fahrenheit, have compressors that run continuously, have evaporator fans that run on poly-phase power, and have evaporator fans of types other than shaded-pole and permanent-split-capacitor. Demand defrost. Evaporators should be defrosted only when necessary, as opposed to on timed schedules where defrosting occurs regardless of need. Defrosting cycles should ideally be based on coil pressure readings, where an increase in pressure drop indicates that frost is present on the coils and that defrosting is necessary . Water defrosting. Water defrosting is said to be more efficient than hot gas defrosting . In water defrosting, water is sprayed manually over the evaporator coils to remove frost. However, water defrosting must be managed properly to ensure that the water does not freeze on the evaporator coils.Compressed air generally represents one of the most inefficient uses of energy in U.S. industry due to poor system efficiency. Typically, the efficiency of a compressed air system—from compressed air generation to end use—is only around 10% . Because of this inefficiency, if compressed air is used, it should be of minimum quantity for the shortest possible time; it should also be constantly monitored and weighed against potential alternatives. Many opportunities to reduce energy consumption in compressed air systems are not prohibitively expensive; payback periods for some options can be extremely short. Energy savings from compressed air system improvements can range from 20% to 50% of total system electricity consumption .

Packaging processes are generally powered using a combination of electric motors, solenoids, and compressed air actuators.The typical processes employed in fruit and vegetable canning are depicted in Figure 3.1. For both fruits and vegetables, inspection, grading, and washing are generally the first processing steps. Vegetables are then typically peeled if needed, subjected to size reduction to obtain the proper form, and blanched to inactivate enzymes. Immediately after blanching, vegetables are typically cooled in a water bath to prevent overcooking. For some vegetables, a heated brine solution is added at the filling stage, which generally consists of salt, sugar, and water. After washing, fruits may be cored and/or peeled, depending on the variety, and washed again to remove peeling residues. Fruits are then subjected to size reduction to obtain the desired form. Some canned fruit products, such as applesauce, are then cooked. Heated syrup or fruit juice is often added to fruits at the filling stage. After filling, the canned fruits and vegetables are exhausted, sealed, sterilized, and cooled before proceeding to final packaging operations.Figure 3.2 depicts representative process flows for the combined manufacture of canned diced tomatoes and canned tomato juices, pastes, and sauces. After inspection and grading, tomatoes are typically washed in a series of agitated water flumes. Next, color sorting is done either manually or automatically to remove green tomatoes, which are subsequently sent to pulping. The red tomatoes are then subjected to steam peeling, followed by manual sorting to remove tomatoes that have not been sufficiently peeled, hydroponic gutter which are also sent to pulping. Peeled red tomatoes are then diced and filled into cans using rotary brush fillers.The canned diced tomatoes are then exhausted, sealed, sterilized, and cooled before proceeding to final packaging operations.

The pulper is used to crush green and unpeeled tomatoes as well as pulping waste from the dicer. After pulping, the tomato slurry proceeds to the evaporator for concentration into juice, puree, and paste . Tomato purees are then typically mixed with other ingredients to create tomato sauce. Prior to filling, evaporated tomato products undergo continuous sterilization. Once filled the canned tomato juices, pastes, and sauces are sent to final packaging operations.The typical processing steps involved in fruit juice canning are depicted in Figure 3.3. After inspection, grading, and washing, juices are extracted from the fruits using mechanical expression or extraction methods. The juice is then often filtered to remove unwanted pulp, deaerated to remove excess oxygen, and deoiled. Next, the juice is pasteurized in a continuous fashion. For fresh juice manufacture, the pasteurized juice is immediately cooled and filled into a container before proceeding to final packaging operations. For canned juice manufacture, the pasteurized juice is hot filled into a container, which is subsequently exhausted, sealed, sterilized, and cooled before proceeding to final packaging operations.Energy represents a significant operating cost to the U.S. fruit and vegetable processing industry. In 2002, the industry spent nearly $810 million on purchased fuels and electricity, or roughly 4.5% of the industry’s total cost of materials . Of this, $370 million was spent on purchased electricity and $440 million was spent on purchased fuels . Electricity is used throughout the typical fruit and vegetable processing facility to power motors, conveyors, compressed air systems, and pumps, as well as building lighting and heating, ventilation, and air conditioning systems . Another major end use of electricity in the industry is refrigeration, which is used for process cooling, cold storage, and freezing applications. For all end uses, the U.S. fruit and vegetable processing industry consumed a total of 6.7 terawatt-hours of electricity in 2002, or nearly 10% of the electricity consumed by the entire U.S. food industry .

The major end use of fuels in the typical fruit and vegetable processing facility is in boiler systems for the generation of steam, which can be used in a wide variety of process heating, water heating, and cleaning applications . Although coal, residual oil, and distillate oils are sometimes used as fuels , currently natural gas accounts for over 90% of all fuels consumed by the U.S. fruit and vegetable processing industry . Thus, in discussions of both the end uses of fuels and the energy efficiency opportunities available for fuels in U.S. facilities, the remainder of this Energy Guide focuses exclusively on natural gas.In 2002, the U.S. fruit and vegetable processing industry consumed around 6.7 TWh of electricity, which equates to roughly 23 trillion Btu of final energy . The frozen fruit, juice, and vegetable manufacturing sub-sector was the industry’s largest consumer of electricity—due in large part to its extensive use of electricity for refrigeration—accounting for roughly 45% of the total electricity consumed by the industry in 2002. The fruit and vegetable canning sub-sector was the next largest user of electricity , followed by the dried and dehydrated food sub-sector and the specialty canning sub-sector . At least half of the industry’s electricity was expected to be consumed in the Western United States . The use of on-site electricity generation appears to be quite limited in the U.S. fruit and vegetable processing industry. In 2002, only 5% of the industry’s electricity was generated at individual facilities . The use of on-site generation was confined almost exclusively to the fruit and vegetable canning sub-sector, where the extensive use of steam in blanching, evaporating, pasteurizing, and sterilizing applications makes combined heat and power systems particularly attractive. The U.S. fruit and vegetable processing industry consumed an estimated 78 TBtu of natural gas in 2002.

The fruit and vegetable canning sub-sector was the industry’s largest consumer of natural gas, accounting for nearly one half of all industry natural gas consumption in 2002 . The frozen fruit, juice, and vegetable manufacturing sub-sector was the next largest user of natural gas, consuming an estimated 21 TBtu of natural gas in 2002, followed by the dried and dehydrated foods manufacturing subsector and the specialty canning sub-sector . At least one half of the industry’s natural gas was expected to be consumed in the Western United States . Table 4.1 summarizes the electricity and natural gas use of the U.S. fruit and vegetable processing industry. In total, the industry consumed an estimated 101 TBtu of final energy in 2002. Combined, the fruit and vegetable canning sub-sector and frozen fruit, juice, and vegetable manufacturing sub-sector accounted for around 75% of the industry’s total final energy use. Figures 4.4 and 4.5 depict the end uses of energy in these two important sub-sectors.The energy consumed by steam-based processes at individual canneries depends heavily on the type of equipment employed, the product manufactured, and equipment configurations. For example, steam blanchers have been reported to consume anywhere from 0.37 kg steam/kg product to 0.94 kg steam/kg product . Water blanchers have been reported to consume anywhere from 0.22 kg steam/kg product to 0.52 kg steam/kg product . Another major consumer of energy is the washing of incoming fruits and vegetables, which, depending on the facility, can use either hot water or ambient water and generally involves a high degree of mechanical agitation. For washing systems that use hot water, water efficiency measures and measures for recovering energy from hot water can be key strategies for reducing process energy consumption. For further details on water efficiency, see Chapter 15 of this Energy Guide. Table 4.3 shows energy intensity data for key processes used in juice canning. The two washing operations—incoming product washing and container washing—are seen to be the most energy-intensive processes involved, together consuming 434 Btu/lb of hot water. Thus, as for fruit and vegetable canning, water efficiency and heat recovery are likely to be key energy saving strategies in juice canning. The pasteurization process is the most significant consumer of steam, followed by the heat sterilization process. Tables 4.2 and 4.3 suggest that for most canneries, steam and hot water represent by far the most dominant uses of process energy in the facility, while process electricity use is generally of lesser significance.Representative process energy intensities for frozen fruit manufacture are provided in Table 4.4. As for canneries, hydroponic nft channel the processes of washing and blanching are likely to be the largest consumers of steam in a typical fruit freezing facility. However, unlike canneries, it can be seen that electricity use is as significant as steam use in the facility, primarily due to the electricity intensity of the freezing process. While the energy intensity of freezing at individual plants can vary widely based on the technology employed—typical energy intensity values for freezing technologies range from 250 Btu/lb to 1,750 Btu/lb —in general, freezing will be the most energy intensive operation in fruit freezing facilities by a significant margin.Similarly, the freezing process is the most energy intensive operation in the manufacture of frozen French fried potatoes, as can be seen in Table 4.5. After freezing, the next largest consumer of energy in frozen French fried potato manufacture is typically the frying process, which consumes a significant amount of direct fuel to heat the frying oil. Table 4.6 provides representative process energy intensity data for the manufacture of frozen concentrated citrus juice, one of the most significant product outputs of the U.S. fruit and vegetable processing industry . As in fruit freezing facilities, the freezing process accounts for the largest share of electricity use in frozen concentrated juice manufacturing facilities. However, the concentration process is the most energy intensive process by a significant margin, consuming an estimated 900 Btu of steam per pound of citrus juice concentrate. Thus, in addition to freezing, the concentration process is likely to be one of the most attractive opportunities for energy efficiency in the typical frozen concentrated juice facility.Lastly, representative process energy intensity data for dehydrated mashed potato manufacture are provided in Table 4.7. Peeling, precooking, and cooking are estimated to be very energy intensive processes. However, the most energy intensive process by far is the drum drying process, which consumes an estimated 6,000 Btu of steam per pound of dehydrated mashed potatoes. In fact, the drying process is one of the most energy intensive processes employed in the entire U.S. food processing industry, with typical energy intensity values ranging from around 1,500 Btu per pound of water in the product to over 28,000 Btu per pound of water in the product .Many opportunities exist within U.S. fruit and vegetable processing facilities to reduce energy consumption while maintaining or enhancing productivity. Ideally, energy efficiency opportunities should be pursued in a coordinated fashion at multiple levels within a facility. At the component and equipment level, energy efficiency can be improved through regular preventative maintenance, proper loading and operation, and replacement of older components and equipment with higher efficiency models whenever feasible. At the process level, process control and optimization can be pursued to ensure that production operations are running at maximum efficiency. At the facility level, the efficiency of space lighting, cooling, and heating can be improved while total facility energy inputs can be minimized through process integration and combined heat and power systems, where feasible. Lastly, at the level of the organization, energy management systems can be implemented to ensure a strong corporate framework exists for energy monitoring, target setting, employee involvement, and continuous improvement. The remaining chapters in this Energy Guide discuss some of the most significant energy efficiency measures applicable to fruit and vegetable processing at the component, process, facility, and organizational levels. This focus of this Energy Guide is on energy efficiency measures that are proven, cost effective, and available for implementation today. Whenever possible, measure descriptions include case studies of fruit and vegetable processing plants that have successfully implemented the measure, both in the United States and abroad. Many case studies include specific energy and cost savings data as well as typical investment payback periods. For measures where data are not available for fruit and vegetable processing facilities, this Energy Guide presents case study data from other sub-sectors of the food industry and occasionally from non-food industries to illustrate typical measure savings. Lastly, for most measures references to the technical literature and online resources are provided, which can be consulted for further information. For individual fruit and vegetable processing facilities, the actual payback period and savings associated with a given measure will vary depending on facility activities, configuration, size, location, and operating characteristics. Thus, the values presented in this Energy Guide are offered as guidelines.

AtbZIP11 transcript levels are upregulated by both light and sugars, which contribute to photoassimilates availability as a result of photosynthesis. When carbohydratesupply is sufficient, sucrose-mediated repression of AtbZIP11 translation would be initiated. In this way, AtbZIP11 activity could keep carbohydrate homeostasis in plant . In contrast, the expression levels of AtbZIP1 and AtbZIP53 were induced after extended night treatment and repressed by sugars application . In strawberry, bZIP11 was induced by red and blue light, while bZIP53 homologue was depressed. In addition, sucrose treatment did not significantly affect bZIP53 at transcriptional level . These findings indicated that bZIP S1 members differentiated in response to some factors. All of bZIP S1 transcriptional factors have the SIRT-responsive uORFs, so researchers proposed a novel SIRT-bZIP technology to enhance sweetness especially for some plant species rich in sucrose . In our study, strawberry bZIP11 overexpressing in tomato indeed increased the TSS and SS content and SS/TA ratio, which provided an applicable method for improvement of strawberry and other fruit quality in the future. However, constitutive overexpression of FvbZIP11 caused a growth impairment, which have been observed in tobacco , Arabidopsis , banana . An explanation of this phenotype was that bZIP11 presumably severely affected carbohydrate partitioning via a mechanism that might include direct regulation to cell-wall invertase and sucrose transporter expression . To avoid growth impairment, Sagor et al. overexpressed SlbZIP1 and SlbZIP2 under the control of the fruit-specific E8 promoter. The growth and morphology of the resulting transgenic tomato plants were comparable to those of wildtype plants. Most fruit-specific promoters currently available have been isolated from tomato, but these promoters probably are inappropriate to be used in non-climacteric fruits, like strawberry . Hence, round planter pot identification of a suitable promoter could facilitate the function analysis of a specific gene involving fruit development and help to specifically improve fruit quality.

The rise of agriculture c. 7000 BC ensured a stable food supply, allowing human civilizations to develop and populations to grow . The challenge of feeding a growing population is exacerbated by climate unpredictability, with drought and temperature increases, leading to decreased crop yield . Tomato is by far the most widely grown vegetable crop worldwide . The narrow genetic base of most crops, combined with selection for performance under optimal conditions, has reduced the genetic variability in environmental stress responses, and the modern cultivars of tomato are no exception . The wild relatives of tomato have the genetic ability to adapt to extreme habitats, and many heirloom cultivars also retain this ability as a result of directed breeding with wild species, and less selection for commercially valuable traits . Heirloom tomatoes are defined as varieties, which have been passed down through multiple generations of a family . Improvement in tomato has focused on flowering, fruit traits, and disease resistance probably as a result of a perceived negative correlation between fruit size and sugar content . Thus, potential impacts of other factors on yield and fruit quality are relatively ignored . In a previous study by Chitwood et al. , a meta-analysis on a set of introgression lines linked leaf complexity and leaflet shape in tomato to fruit sugar content measured on the same lines by other researchers . This correlation showed that plants with complex and rounder leaflets also had increased fruit sugar content . Because leaves are the primary site of photosynthesis, it is possible that leaf shape changes may impact photosynthetic capacity and therefore result in different sugar content and yield in fruits. In addition to photosynthesis, sugar transport, and distribution to sinks are other potential sites of regulation in leaf function as source tissue. While sugar transport in plants is well described, distribution among different sink tissues is not fully understood .

We analyzed tomato cultivars with varied yield and fruit quality, photosynthetic capacity, leaflet shape, and other vegetative traits and found that leaflet shape was strongly correlated to overall fruit quality assessed as a composite measure of BRIX and yield , with rounder leaflets positively correlated with higher BY values. Photosynthesis, on the other hand, had a negative correlation with yield. Based on our analysis, leaf shape seems to play an important role in the distribution of photo assimilates. Additionally, we performed phylogenetic network analysis on 23 cultivars, including eight identified as having the rounder Potato Leaf Morph , known to be caused by a mutation in the C-locus , to determine their breeding histories and identify any potential selection for this trait.Eighteen heirloom tomato varieties identified as having a range of fruit types, including cherry and beefsteak tomatoes, and several intermediate types, were analyzed. These tomato varieties also differed in fruit production timing from early to late, and the type of leaf morphology. These cultivars were selected based on leaf shape as described in Tatiana’s TOMATO base and The Heirloom Tomato . Tomato seeds were treated, germinated, and field planted as previously described . In both the 2014 and 2015 seasons, plants were laid out in a randomized block design and were planted and grown in soil, with furrow irrigation once weekly.Gas exchange measurements were done in the field on attached leaves after the plants had recovered from transplanting. Measurements were made weekly from week 10 to week 15 , on week 17 , and weeks 18– 21 , on c. 60 plants each week, on three plants per cultivar wk–1 . Measurements were made on leaves from the upper and lower portions of the plants to eliminate positional bias within the plant, and measured for three leaves per plant. The A , gst , transpiration, and ɸPS2 of a 6 cm2 area of the leaflet were measured using the LI-6400 XT infrared gas exchange system , and a fluorescence head .

Light within the chamber was provided by the fluorescence head at 1500 µmol m2 s 1 photosynthetically active radiation , and the chamber air flow volume was 400 µmols s 1 with the chamber atmosphere mixed by a fan. CO2 concentration within the chamber was set at 400 µmols mol 1 . Humidity, leaf and chamber temperature were allowed to adjust to ambient conditions; however, the chamber block temperature was not allowed to exceed 36°C. Measured leaflets were allowed to equilibrate for 2–3 min before measurements were taken, allowing sufficient time for photosynthetic rates to stabilize with only marginal variation. The amount of intercepted PAR was measured in four orientations per plant and an average PARi calculated. PARi was measured by placing a Line Quantum Sensor onto a base made from ¼” PVC piping, and a Quantum Sensor approximately 1 m above the plant on the PVC rig. Measurements from both sensors were taken simultaneously for each sample using a Light Sensor Logger . This allowed variation in overall light intensities such as cloud movement to be measured and accounted for in the total PARi.After gas exchange measurements, three plants per cultivar were destructively harvested each week. The final yield and fresh vegetative weight of each plant harvested was measured using a hanging scale in the field. Five leaves were collected at random from the bottom and top of the plant to capture all canopy levels, round pot for plants and approximately nine fruit were collected for BRIX measurements. FW was used owing to the large number of plants and measurements being done in situ in the field setting. All measurements were made in kg. To measure the BRIX value of the tomatoes, the collected fruit was taken to the laboratory where the juice was collected and measured on a refractometer . The yield and BRIX for each plant were multiplied together to get the BRIX 9 yield index , which gives an overall fruit quality measure, accounting for variations and extreme values in either measurement. It should be noted that while BRIX is used as a standard quality measure, BY is a composite value that folds in yield to assess weight of soluble solids per plant and is being used to measure commercial quality and not consumer quality . BY measurements were done for both the 2014 and the more detailed 2015 fields. These data were compared to test for reproducibility of results .The leaf complexity measures included all leaflets present on the leaf. Subsequently, primary leaflets were used for imaging and analysis of shape and size as previously described , and the images then processed in IMAGEJ . The images were cropped to individual leaflets maintaining the exact pixel ratio of the original image, and then cropped again to only include the single leaflet using a custom Java script written for FIJI . Single leaflet images converted to a binary image as black on a white background, and smoothed to allow for the exclusion of any particulates in the image were then processed in R using MOMOCS, a shape analysis package. Leaflet images were imported and then aligned along their axes so that all images faced the same direction. They were then processed using elliptical Fourier analysis based on the calculated number of harmonics from the MOMOCS package. Principal component analysis was performed on the resulting eFourier analysis and the principal components were used for subsequent analysis. Traditional shape measures such as leaflet area, circularity, solidity, and roundness were done with the area measurement based on pixel density. These measures were compared with the PCs to determine the characteristics captured by each PC. The PC values were used for all subsequent leaflet shape and size analyses. Total leaf area for each plant was measured by imaging the whole plant and a 4 cm2 red square and then processed in the EASY LEAF AREA software .Five plants per line were used to analyze leaflet sugar content. The plants were grown under the same conditions as field plants with the following exceptions. Plants remained in the glasshouse after transfer to 1 gallon pots. All plants were watered with nutrient solution and grown until mature leaves could be sampled. Using a hole punch, a disk with an area of 0.28 cm2 was taken from the leaflets and extracted from the disks using a modi- fied extraction method from the Ainsworth laboratory . Leaf disks were placed in 2 mM HEPES in 80% EtOH and heated to 80°C for 20 min and the liquid collected and stored at placed in 2 mM HEPES in 50% EtOH and heated, collecting the 20°C. The entire process was repeated twice. They were then liquid and storing at 20°C followed by another 2 mM HEPES in 80% treatment. The collected liquid was then used to measure the amount of sugar present per area of disk. To measure leaf sugar content a working solution of 100 mM HEPES , 6.3 mM MgCl2 , and 3 mM ATP and NADP at pH 7 was prepared. From the working solution, an assay buffer was made adding 50 U of glucose-6-phosphate dehydrogenase , and 295 or 280 µl of the working solution was added to a 96-well plate for sucrose standards or samples, respectively. Standards were added at a 60-fold dilution and samples were added at a 15-fold dilution. Then 0.5 U of hexokinase , 0.21 U of phosphoglucoisomerase , and 20 U of invertase were added to each well and the plates allowed to sit overnight to reach equilibrium. The plates were measured on a UV spectrometer at 340 nm, followed by analysis in JMP .All statistical analyses were performed using JMP software. To determine statistical significance, measurements were modeled using general linear regression model and tested by a one-way ANOVA followed by Tukey’s honestly significant difference, if necessary. These modeled data for all measured values were compiled into a table and used to create a model using partial least-squares path modeling in SMARTPLS 3.0 . Modeled data were used for the statistical analyses as many measurement types varied in number of data points, and therefore a set of generated predicted values of equal size was used to make an equal data matrix . Partial least squares-PM was used to explore the cause-and-effect relationships between the measured variables through latent values. PLS-PM is effective in both exploring unknown relationships and combining large-scale data, such as field, physiological, and morphological data, that otherwise are not well described together .

Our analysis of ripening-related gene expression in Cnr showed striking similarities to WT in the number and functions of genes changing between stages. Moreover, 69.5% of ripening related DEGs in Cnr were shared with WT . These results further support the hypothesis that Cnr is not exclusively a ripening mutant. Instead, Cnr fruit undergoes gene expression changes consistent with WT “ripening.” However, the ripening related changes in gene expression that occur in Cnr are not enough to compensate for the large defects accumulated in the fruit during growth and maturation. In a recent report, a knockout mutation to the gene body of CNR yielded little visible effects on fruit development and ripening , which suggests that the Cnr mutant phenotype may result from more than just a reduced expression of the CNR gene as previously reported . It has also been demonstrated that Cnr fruit have genome-wide methylation changes that inhibit ripening-related gene expression . The developmental defects observed in Cnr are likely caused by these methylation changes, directly or indirectly caused by the Cnr mutation . Thus, to better understand the Cnr mutation, more physiological data at earlier stages of development needs to be analyzed and complemented with more in-depth functional analysis of gene expression alterations at the corresponding stages. In addition, further molecular and genetic studies need to be performed and compared against complete CNR knockout mutants. Our data support that the mutants never produce a burst in ethylene production, even at the OR stage where more ripening phenotypes are observed . The orange-red pigmentation in nor OR fruit and the similarities of rin OR fruit in texture and taste-related attributes to WT RR fruit occur independently of an ethylene burst. These observations evidence that other regulatory mechanisms exist to initiate ripening events outside of ethylene .

Unlike previous reports, our data consistently showed that Cnr presented increased ethylene levels at the MG stage compared to WT . Interestingly, Cnr fruit produced more of the ethylene precursor ACC than WT at the RR stage. Also, rin made equivalent levels to WT fruit. Ethylene biosynthesis is divided into two programs: System 1 produces basal levels of the hormone during development, black plastic plant pots and System 2 generates the climacteric rise in ethylene during ripening . Each of these systems is catalyzed by a different set of ethylene biosynthetic enzymes . It is clear that all mutants show defects to System 2 of ethylene biosynthesis, but they also appear to have alterations specific to System 1. For example, we observed that SlACO3, a System 1- specific ACC oxidase, was higher expressed in Cnr fruit than WT .The role of ABA in climacteric ripening is not as well explored but has been reported to be complementary to ethylene . Previous reports in WT fruit have shown that ABA increases until the breaker stage, just before the ethylene burst . ABA has also been shown to induce ethylene production and linked to the NOR transcription factor . We found that nor and rin fruit did not show decreases in ABA concentration during ripening like WT did . For nor, the constant levels of ABA between MG and RR stages are another example of how fruit ripening events are delayed or inhibited. RIN and ABA have been demonstrated to have an inverse relationship where RIN expression is repressed with the induction of ABA . The significant increase of ABA accumulation in rin during ripening suggests that ABA biosynthesis and metabolism are misregulated in this mutant. rin fruit appear to present a delayed peak in ABA levels compared to WT fruit. Our results support the indirect interaction between the TFs and ABA during ripening. More developmental stages, genetic manipulations, and exogenous hormone treatments are needed to investigate further the trends of ABA accumulation seen in the ripening mutants.

The interactions between the CNR, NOR, and RIN in ripening have been debated in the literature . The TF RIN directly interacts with NOR and CNR, binding to their respective promoters, and therefore has been proposed to be the most upstream TF among the three regulators . Here we provided evidence that the three TFs display at least indirect effects on each other. We have argued that the Cnr mutant shows a wide breadth of defects across fruit development before ripening begins, and thus, we propose the Cnr mutation is acting before NOR or RIN. This further supports the hypothesis made in Wang et al. that Cnr acts epistatically to nor and rin. The gene expression patterns of CNR, NOR, and RIN across ripening stages were decreased or delayed in each of the single ripening mutants. The most substantial variation in gene expression was the downregulation of NOR and RIN expression across all stages in the Cnr mutant . We present for the first time double ripening mutants, homozygous for both loci, that can be used to see the combined effects of each mutation on fruit development and quality traits. We successfully generated the double mutants by establishing reliable and high throughput genotyping protocols for each mutation and evaluating segregation of the mutant phenotypes in field trials across multiple growing seasons. We obtained double mutants from both reciprocal crosses but saw no fruit phenotypic differences between them, suggesting that the ripening mutations are not influenced by maternal or paternal effects . Because the nor and rin mutants look so similar, it was hard to visually determine the individual effects of each mutation on the appearance of rin/nor fruit. However, when specific fruit traits were measured, we could detect additive or intermediate fruit phenotypes in this double mutant, supporting the proposed relationship in Wang et al. . Thus, nor and rin appear to influence similar fruit traits and act in coordination.

The Cnr mutation had a significant effect on the Cnr/nor and Cnr/rin mutants resulting in fruit with similar appearance and ethylene production to the Cnr fruit . When analyzing the gene expression profiles of the Cnr/nor fruit, we also observed multiple similarities to the Cnr parent, but also several deviations . Surprisingly, Cnr/nor was also reminiscent of nor, as it displayed few ripening-related gene expression changes, suggesting the inhibition or delay of specific ripening events in nor carried over to the double mutant. Here, we proposed that the Cnr mutation causes defects throughout fruit development while the nor mutation causes defects predominantly in ripening. However, the Cnr/nor double mutant showed additional phenotypic and transcriptional defects before ripening than both mutant parents . These observations indicate that in combination with Cnr, nor may contribute to alterations in early fruit development and the inhibition of ripening progression.Fruit breeders actively selected several morphological and quality phenotypes during the domestication of the garden strawberry , an allo-octoploid of hybrid origin. F. × ananassa was created in the early 1700s by interspecific hybridization between ecotypes of wild octoploid species , multiple subsequent introgressions of genetic diversity from F. virginiana and F. chiloensis subspecies in subsequent generations, and arti-ficial selection for horticulturally important traits among interspecific hybrid descendants. Domestication and breeding have altered the fruit morphology, development, and metabolome of the garden strawberry, distancing modern cultivars from their wild progenitors. Approximately 300 years of breeding in the admixed hybrid population has led to the emergence of high yielding cultivars with large, firm, visually appealing, long shelf life fruit that can withstand the rigors of harvest, handling, storage, and long-distance shipping. Fruit shape is an essential trait of agricultural products, particularly those of specialty crops, owing to perceived and realized relationships with the quality and value of the products. Image-based fruit phenotyping has the potential to increase scope, throughput, and accuracy in quantitative genetic studies by reducing the effects of user bias, enabling the analysis of larger sample sizes, and more accurate partitioning of genetic variance from environments, management, and other non-genetic sources of variation. Many fruit phenotyping approaches rely on the human eye to sort fruit into discrete, descriptive categories for planar shapes. Categories are either nominal, existing in name only, or ordinal, referring to a position in an ordered series or on a gradient. Classification into categories is often labor-intensive and prone to human bias, black plastic garden pots which can increase with task complexity and time requirements. Alternative scoring approaches rely on morphometrics and machine learning to automate classification; e.g., sorting fruit into shape categories in both tomato and strawberry. Unsupervised machine learning methods , unlike supervised methods, are useful for pattern detection and clustering, while supervised machine learning methods are useful for prediction and classification.

Unsupervised clustering enables the calculation of several measures of model performance and overfitting to balance compression and accuracy. However, the categories derived from these techniques are without order, resulting in the need for a suitable transformation to an ordinal scale more appropriate for quantitative genetic analyses. In this context, ordinal categories give the interpretation of relationship with, or distance from, other shape categories in a series. To enable this interpretation, we developed a method for asserting the progression through fruit shape categories derived from unsupervised machine learning methods. The Principal Progression of k Clusters allowed us to nonarbitrarily determine the appropriate shape gradient for statistical analyses using empirical data. The advantages of PPKC, relative to a manually determined ordinal scale, are that it does not require arbitrary, a priori decisions and is unsupervised, which obviates additional operator bias. Here, we describe approaches for translating digital images of strawberries into computationally defined phenotypic variables for identifying and classifying fruit shapes. Fruit shape and anatomy are complex, multi-dimensional, and, potentially, abstract phenotypes that are often not completely or intuitively described by planar descriptors and individual qualitative or quantitative variables. Beyond the qualitative definitions used in plant systematics, references to fruit shape encompass a wide variety of mathematical parameters and geometric indices that establish quantitative measurements of plant organs . Much like human faces or grain yield, fruit shape and anatomy are products of the underlying genetic and non-genetic determinants of phenotypic variability in a population. Quantitative phenotypic measurements have allowed researchers to uncover some of the genetic basis of fruit shape in tomato, pepper, pear, melon, potato, and strawberry. However, the major genetic determinants of fruit shape remain unclear, or understudied, in octoploid strawberry, in part because researchers have not yet translated fruit shape attributes into holistic, quantitative variables, which may empower the identification of underlying genes or quantitative trait loci through genome-wide association studies and other quantitative genetic approaches. Quantitative features often rely on linear metrics of distance and are generally modified into compound descriptors that remove the effects of size. However, compound linear descriptors often have limited resolution compared to more comprehensive, multivariate descriptors. Elliptical Fourier analysis quantifies fruit shape from a closed outline by converting a closed contour into a weighted sum of harmonic functions . Generalized Procrustes analysis quantifies the distance between sets of biologically homologous, or mathematically similar, landmarks on the surface of an object. Fruit shape can also be described using linear combinations of pixel intensities from digital images extrapolating from analyses generally used to quantify color patterns and facial recognition. Similar pixel-based descriptors have recently been referred to as ”latent space phenotypes” and arise from unsupervised analyses that allow a computer to produce novel, independently distributed features directly from images. Here, we generate a dictionary of 68 quantitative features, including linear-, outline-, landmark-, and pixel-based descriptors to investigate the quality of different features in preparation for quantitative genetic analyses. The ultimate goal of our study was to develop heritable phenotypic variables for describing fruit shape, which could then be used to identify the genetic factors underlying phenotypic differences in fruit shape. The phenotyping and analytic workflow for this study are summarized in Figs 1 and 2. We first describe and demonstrate the application of PPKC, which transforms categories discovered from unsupervised machine learning methods to a more convenient and analytically tractable ordinal scale. We then explore the relationship between machine acquired categories and 68 quantitative features extracted from digital images. Next, we apply random forest regression to select critical sets of quantitative features for classification and use supervised machine learning methods, including support vector regression and linear discriminant analysis , to determine the accuracy of shape classification.

Finetuning of metabolomic traits such as amylose content in rice and sugar content in wild strawberry recently were made possible via CRISPR-Cas9 gene-editing technology. Similar approaches can be taken in cultivated strawberry for flavor improvement, but not before the biosynthetic genes responsible for metabolites production and their regulatory elements are identified. Our pipeline has proven to be effective in identification of novel causal mutations for flavor genes responsible for natural variation in volatile content and can be further applied to various metabolomic and morphological aspects of strawberry fruit such as anthocyanin biosynthesis , sugar content and fruit firmness. These findings also will help breeders to select for genomic variants underlying volatiles important to flavor. New markers can be designed from regulatory regions of key aroma volatiles, including multiple medium-chain volatiles shown to improve strawberry flavor and consumer liking , methyl thioacetate contributing to overripe flavor and methyl anthranilate imparting grape flavor . In the present study, a new functional HRM marker for mesifurane was developed and tested in multiple populations . These favorable alleles of volatiles can be pyramided to improve overall fruit flavor via marker assisted selection. Specific esters are shared with apple , certain lactones are shared with peach and various terpenes are shared with citrus . Syntenic regions and orthologous genes could be exploited for flavor improvement in those species. Additional insights were gained for the strawberry gene regulatory landscape, SV diversity, complex interplays among cis- and trans- regulatory elements, and subgenome dominance. Previously, Hardigan et al. and Pincot et al. showed a large genetic diversity existing in breeding populations of Fragaria × ananassa, plastic grow pots challenging previous assumptions that cultivated strawberry lacked nucleotide variation owing to the nature of its interspecific origin and short history of domestication .

Our work corroborated their findings and showed that even highly domesticated populations harbor substantial expression regulatory elements and structural variants. Over half of the expressed genes in fruit harbored at least one eQTL, and 22 731 eGenes had impactful cis-eQTL. The distribution of trans-eQTL is not random, but rather is concentrated at a few hotspots controlled by putative master regulators . The aggregation of trans-eQTL also was observed in plant species such as Lactuca sativa and Zea mays . Furthermore, we observed a substantial number of trans-eQTL among homoeologous chromosomes, similar to observations in other allopolyploid plant species . In cotton, physical interactions among chromatins from different subgenomes have been identified via Hi-C sequencing , supporting a potential regulatory mechanism among homoeologous chromosomes. However, owing to the high similarity among four subgenomes and limited length of Illumina reads, false alignment to incorrect homoeologous chromosomes could arise, leading to ‘ghost’ trans-eQTL signals. Future studies are needed to scrutinize the homoeologous trans-eQTL and investigate the mechanism behind this genome-wide phenomenon. Higher numbers of trans-eQTL in the Fragaria vesca-like subgenome are consistent with its dominance in octoploid strawberry . By contrast, the highly mixed Fragaria viridis- and Fragaria nipponica- like subgenomes contained much smaller numbers of trans-eQTL. The characterization of naturally-occurring allelic variants underlying volatile abundance has direct breeding applications. First, this will facilitate the selection of desirable alleles via DNA markers. Second, understanding the causal mutations in alleles can guide precision breeding approaches such as gene editing to modify the alleles themselves and/or their level of expression. From a broader perspective, multi-omics resources such as this one will have value for breeding a wide array of fruit traits.

Enhancing consumer satisfaction in fruit ultimately will depend on the improvement of the many traits that together enhance the overall eating experience.In a fruit tree orchard system, individual trees are composed of two genetically different genotypes, one being the rootstock which includes the mass of the tree below the soil surface to a graft union about midway up the trunk. Rootstocks can be selected for pest resistance or tolerance towards adverse soil conditions, and they can also influence vigor and cropping . The second portion of the tree is referred to as the scion and accounts for most of the above-ground mass, usually chosen for fruit production traits . Over the last 40+ years, the University of California has had a peach rootstock development program that has identified several promising size controlling rootstocks which allow for the establishment of new commercially viable orchard systems . New dwarfing rootstocks for peach must be graft compatible, reduce vigor, and not diminish marketable fruit production by reducing fruit size or quality . Previous peach rootstock trials monitored vigor control and grafting compatibility in conventional planting systems however, yield parameters such as fruit size and quantity have not been as thoroughly evaluated using these rootstocks in pedestrian orchard systems . Fruit size is paramount in peach production as larger fruit, free of cosmetic imperfections, have a higher market demand and therefore higher market value . It has been reported that peach fruit produced on trees with size-controlling rootstocks can tend to be smaller in size than fruit on trees with more vigorous rootstocks .Vascular tissue known as xylem is responsible for the movement of water and nutrients in all trees. In trees, every year a new ring of xylem forms surrounding the previous year’s growth and water conduction in the xylem often occurs only in this outermost annual ring . It has been reported that size-controlling peach rootstocks contain a higher proportion of narrow diameter xylem vessels and fewer larger vessels when compared to more vigorous rootstocks in addition to having an increased axial diameter .

Both characteristics create a reduction of hydraulic conductance in the size-controlling peach rootstocks compared to traditional, vigorous rootstocks. Reduced hydraulic conductance, as demonstrated by and , can cause reductions in stem water potential during mid-day hours that can lead to a reduction in vegetative growth .An mean peach fruit’s fresh weight is composed of over 80% water . Thus, it is reasonable to assume a reduced hydraulic conductance created by size controlling rootstocks could hinder fruit size. However, the relationship between fruit growth and water availability is dynamic and depends on the developmental stage of the fruit, the severity of water limitations, and the component of growth being considered . It has been reported that mild water stress applied during the intermediate developmental period of slow fruit growth has no effect on crop yields but significantly reduces vegetative growth in peach . Fruit developmental stages may differ in time of initiation and duration among peach varieties, an example of this would be an early vs. late harvested cultivar as demonstrated by . Fruit growth occurs in stages from fruit set to harvest, in all cultivars, and during the final growth phase of peach fruit is when 65% of a fruit’s dry weight and 80% of a fruit’s fresh weight are accumulated . Available water varies throughout the growing season, including diurnal fluctuations brought on by daily temperature fluctuations , day-to-day changes brought on by a shift in evapotranspiration , and possible seasonal changes brought on by the formation of new xylem . Water conduction in the tree is largely dependent on newly formed xylem each spring and the new xylem cells are smaller in size-controlling rootstocks. It is thought that the spring flush of vegetative growth is limited in trees on size controlling rootstocks compared to growth on vigorous rootstocks because of temporary reductions in root hydraulic conductance caused by smaller xylem vessels. A question that arises from these findings, does the reduction of water conductance in dwarfed peach trees also limit fruit growth?In peach production, fruit size is often manipulated with the use of a management practice known as fruit thinning. With fruit thinning, shortly after fruit set, a portion of immature fruit is removed from the tree to reduce carbohydrate competition among those remaining. It is widely recognized that fruit size is largely influenced by crop load, with larger fruit size obtained as the crop load is reduced . Quality of fruit may also be affected by crop load, low-cropped trees have been shown to produce larger and firmer fruit than those from heavily cropped trees . Although minor in comparison tocarbohydrate demand, big plastic pots fruit size may also be diminished by inducing higher water stress with larger crop loads. An experiment by found that larger crop loads were responsible for reducing midday stem water potential in nectarines.

MacFayden et al., concluded that an increased crop load also increased the fruit water deficit which may reduce fruit growth in peach. According to another study by , rootstocks also influenced the crop load’s effect on fruit size, and more vigorous rootstocks had larger fruits at specific crop loads. The fore mentioned findings relay the importance of better understanding the relationship between fruit size and crop load among vigorous and reduced-vigor rootstocks.While crop load per tree is controlled by thinning, crop load per area is most influenced by planting density. The reduced vigor and overall size of trees on size-controlling rootstocks facilitates the establishment of high-density plantings . The primary principle in establishing an appropriate planting density for an orchard using trees on size controlling rootstocks is that total tree dry matter production and crop yield are related to total light interception . This principle holds for essentially all crops . However, although higher light interception often leads to higher yields, yield may also vary significantly with other environmental stressors such as available water, nutrients, temperature, and amount of time the fruit has for growth . Orchard systems with increased planting densities have also been shown to reach maximum yield capacity earlier than conventional plantings since the trees are able to fill out their allotted space more quickly . In a small trial using the ‘Summer Bright” nectarine cultivar, trees that were pruned to a standard height of 12 to 13 feet or limited to heights of 8 or 9 feet produced similar sized fruit and crop yields. The reasoning for this was that, despite the height difference, both tree shapes had equal planar volume and therefore intercepted similar amounts of photosynthetically active radiation .The goal of this study was to address three production characteristics and their relationship with four different orchard systems. 1) Fruit size: can peach orchard systems using trees on size controlling rootstocks produce fruit of equal size compared to orchard systems with trees on vigorous rootstocks? 2) Fruit count: if crop load per area is similar among size-controlling and vigorous systems is fruit size also similar? 3) PAR interception and yield: is there a difference in the relationship of fruit production vs light interception among orchard systems with vigorous rootstocks and those with size-controlling rootstocks? A better understanding of production capabilities will allow researchers and growers to better estimate the potential of an orchard system on size-controlling rootstocks as a commercially viable option.In April 2015, an orchard system trial was established at the University of California Kearney Agricultural Center, Parlier, CA. The research block consisted of two peach [Prunus persica Batsch] scion cultivars, June Flame and August Flame grafted onto three different rootstock genotypes: HBOK 27 , P-30-135 , and Nemaguard . Controller 6 was used in two of the four training systems . The C-6 V was a high-density planting system with an in-row spacing of 1.2m and trained to the KAC-V perpendicular V pruning system . The C-6 Quad system was pruned to a Quad V where four main scaffolds are selected in each tree and pruned to resemble an open vase, the system also had a larger in-row spacing of 2.4 m . The Controller 9 Quad system was identical to the C-6 Quad system with the only difference being the rootstock. Between-row spacing was 4.6m in all systems using size controlling rootstocks. Nemaguard was used as the commercial standard rootstock with a planting density of 2.4m in-row spacing and 5.5m between-row spacing . Shortly after harvest, orchard systems using size-controlling rootstocks were topped to a height of 2.5m while systems using the Nemaguard rootstock were topped at 3.5m. The four systems were divided into three replications for each of the two scion cultivars making a total of eight unique orchard systems. Each replication consisted of four rows of trees with the northern and southern most rows used as guard rows, the first and last two trees in each data row were also considered guard trees making nine trees in each of the two inner rows the sample size per replication . In total, each cultivar was represented by approximately 54 data trees .

Tertiary models are established based on primary and secondary models and use predicted values of growth parameters from secondary models to predict changes in pathogen density at times and levels of independent variables that have not been tested or used in the model development .The survival of all three pathogens was longest in high-moisture and low-moisture dates at refrigerated temperature. The combination of their high pH values and low aw compared to the other dried fruits may be reasons why the dates have larger D-value than the other dried fruits. Juneja et al found that L. monocytogenes, E. coli O157:H7, and Salmonella spp. were able to survive on dates for 32 days when stored at 4 °C. Furthermore they found that there was no significant difference in any of the pathogens when the dates were treated with antimicrobial washes of peracetic acid or with ethanol . Because of this strong ability for pathogens to survive, Medjool dates should be further explored from a microbial safety viewpoint. The storage temperature had the biggest influence on decimal reduction time in Salmonella. While having the highest D values of the three pathogens in refrigerated dried fruit, Salmonella had the lowest D values in the dried fruit stored at ambient temperature . This shows that temperature has a large influence on the survival time of Salmonella. While thermal death time does increase for all three pathogens when put in colder conditions, the difference in Salmonella is the starkest. For example, according to the models made, the time is would take to reduce Salmonella by 90% in high moisture dates at refrigerated temperature would be 396 days, whereas at ambient temperature it would take 21 days . These results suggest that Salmonella has particularly increased survival at lower temperatures compared to other pathogens. While the specific mechanisms that allow for this survival in low moisture environments are not completely clear, garden pots square temperature most likely has an influence on those mechanisms. Andino and Hanning suggest one possible mechanism that Salmonella spp. may use to enhance its survival at lowered temperatures is cold shock proteins .

Upregulation of these proteins allow Salmonella to adapt to colder environments as temperatures drop, leading to better survival of the pathogen. Looking at the dried peaches , the decimal reduction time of the pathogens were higher when the peaches were inoculated with the dry carrier versus the wet carrier. This suggests that pathogens are more persistent when using a dry carrier to simulate a dry environment. However, a factor that might have influenced the lower D value in the wet inoculated peach is that the initial inoculation strength is several logs higher with a wet carrier than a dry carrier. Due to the higher initial microbial load in the wet inoculated peaches compared to the dry inoculated, there is difficulty in comparing the true impact that the wet and dry carrier had on the decimal reduction time.Dried fruit were inoculated with Salmonella spp., Escherichia coli, or L. monocytogenes to determine how they would survive in two storage conditions. All three pathogens were able to survive in dried fruits and should be taken into consideration when looking at the safety of dried fruit processing. Salmonella had the longest survival potential among all three tested pathogens. This observation is expected as Salmonella is known for its ability to survive in low moisture conditions. The condition that allowed for longer pathogens survival was storage at refrigerated temperature rather than ambient temperature. This is important because many dried fruit processors store their dried fruits at refrigerated temperatures if not being sold immediately. This allows for a longer shelf life of the dried fruit compared to ambient storage, but increases the ability for bacterial survival. This may be due to the intrinsic factors of the dried fruit: pH, aw, and available nutrient. Based on the current data, survival was the longest in the dried fruits that had the highest relative pH and the lowest relative aw. Salmonella inoculated in Medjool dates survived to the very end of the 180-day survival study.

The Medjool dates had the highest pH of all the dried fruits and had some of the lowest aw of the dried fruits. Other intrinsic factors that were not measured could have also played a role in the long survival time in the dates. For instance, dates are known to have a high sugar content, which may have played a role in pathogen survival. Measuring various compounds in the dried fruits might give more insight on why certain dried fruits allowed for longer survival than others. Regardless the reason, pathogen survival was long in Medjool dates, and should be something that those who produce dates consider. Since dates are not dried the same way other dried fruits are, the steps in the date harvesting process should be looked at carefully. While conducting this research, a new potential outbreak associated with Medjool dates was reported . Twenty-eight people in England were infected with Hepatitis A in 2021 and is suspected to be from Medjool dates . The dates have since been recalled due to their possible contamination . In 2018 there was another outbreak of Hepatitis A in Denmark and was believed to be from dates from Iran . There has been no evidence to show that those dates were contaminated with the virus . That potentially makes this 2021 outbreak the first to be associated with a dried fruit not part of a mixed product. With the occurrence of this outbreak, it makes it all the more important to understand when and where potential contamination of pathogens in dried fruits can occur. Although the data generated from our study is based on bacteria, we did see that the survival of pathogens in Medjool dates is longer compared to other dried fruits. Additional research will be necessary to better understand the survival of foodborne virus on dried fruits. As discussed earlier in this thesis, there are many pre- and post-drying treatments that can be applied to fresh or dried fruits. When looking into the available literature, the efficacy of these treatments has not been systematically evaluated. One on-going project in the lab is to summarize the current knowledge about these treatments and their efficacies and develop a study that fills in the knowledge gaps. In the meantime, identifying a surrogate for testing the different pre- and post-drying treatments as well as different drying methods is needed.

Enterococcus faecium NRRL B-2354 has been validated and approved for being used as a surrogate for almond thermal processing validation . However, whether this strain can be as a surrogate for dried fruit related studies or not still needs further evaluation. One on-going test project in the lab is go evaluate the survival of E. faecium NRRL B-2354 in dried peaches and apricots. In this first test trial, E. faecium was inoculated onto two types of dried fruits and its survival at ambient and refrigerated temperatures is being monitored. In addition, the highest temperatures that can be achieved by various dry methods are being monitored and recorded. The efficacy of different pre-drying treatments is also being tested in the lab by using Salmonella-inoculated peaches and E. faecium-inoculated peaches. In summary, the microbial safety of dried fruits is important and needs more research attention. The survivability of common foodborne pathogens on different types of dried fruits and the recalls and outbreaks associated with dried fruits highlight the importance of the validation of pre- and post-drying treatments as well as different drying methods. The findings of this study, square pots along with future work, hopes to provide the foundation needed for the development of food safety plans for dried fruits.Under global warming and climate change, cultivated plants are encountering increased biotic and abiotic stresses, which lead to reductions of plant growth and reproduction and consequently economic losses. The use of plant endophytic bacteria to promote plant growth and increase tolerance of environmental stresses has provided an alternative to standard agricultural practices that has fewer safety concerns. Endophytic bacteria can be defined as non-pathogenic bacteria that colonize the interior of host plants and can be isolated from surface-sterilized plant tissues. These bacteria can obtain a constant nutrient supply from host plants by living inside the plants and having close contact with plant cells. The endophytic bacteria colonization process is usually initiated at wounds and cracks in the roots by a rhizospheric population of the bacteria in the soil. After entering the plant roots, endophytic bacteria can systemically colonize the above ground parts of plants, including stems and leaves.A wide diversity of endophytic bacteria has been discovered in several plant species. Endophytic bacteria communities include five main phyla. Proteobacteria is the most dominant phylum isolated from host plants, which includes α-, β-, and γ-Proteobacteria. Actinobacteria, Planctomycetes, Verrucomicrobia, and Acidobacteria are also commonly identified. The most frequently isolated bacteria genera are Bacillus, Burkholderia, Microbacterium, Micrococcus, Pantoea, Pseudomonas, and Stenotrophomonas, with the two major genera being Bacillus and Pseudomonas. Several factors affect the composition of endophytic bacteria populations, including plant growth conditions, plant age, types of analyzed plant tissues, soil contents, and other environmental factors. Endophytic bacteria can have several beneficial effects on host plants, such as promotion of plant growth and yield, increased resistance to plant pathogens, enhanced tolerance to abiotic stresses, elimination of soil pollutants through the facilitation of phytoremediation, and production of various metabolites with potential applications in agriculture, medicine, and industry. Some endophytic bacteria help host plants acquire increased amounts of limited resources from the environment. This can include enhancing the uptake of nitrogen, phosphorous, or iron by expressing nitrogenase, solubilizing precipitated phosphates, or producing iron-chelating agents in bacteria, respectively. Some endophytic plant-growth-promoting bacteria can increase host plants’ metabolism and nutrient accumulation by providing or regulating various plant hormones, including auxin, cytokinin, gibberellins, or ethylene. Auxin and ethylene are the two major hormones that affect plant growth and development and that are involved in plant-endophytic bacteria interactions. In addition to these four hormones, several endophytes can utilize signaling pathways mediated by salicylic acid, jasmonic acid, and ethylene to initiate induced systemic resistance and protect host plants from phytopathogen infection. A number of endophytic bacteria can also produce various antibiotics, toxins, hydrolytic enzymes, and antimicrobial volatile organic compounds to limit pathogen infection. We previously isolated a plant endophytic bacterium, Burkholderia sp. strain 869T2, from surface-sterilized root tissues of vetiver grass. Strain 869T2 can also live within banana plants, in which it promoted growth and reduced Fusarium wilt disease occurrence. Genomic sequences of the strain 869T2 contain the gene for 1-aminocyclopropane-1-carboxylate deaminase, which may modulate host plant ethylene levels. Strain 869T2 also has genes related to the synthesis of pyrrolnitrin, which may function as a broad-spectrum anti-fungal agent, as well as dioxin-degradation-related genes. Furthermore, strain 869T2 can degrade the toxic dioxin congener 2,3,7,8-tetrachlorinated dibenzo-p-dioxin , mainly via its 2-haloacid dehalogenase. A recent study compared the genome sequences of 31 Burkholderia spp. and reclassified Burkholderia cenocepacia strain 869T2 as Burkholderia seminalis. We also compared the genome sequences of the strain 869T2 with those of five published B. seminalis strains: FL-5-4-10-S1-D7, FL-5-5-10-S1-D0, Bp9022, Bp8988, and TC3.4.2R3. The strain 869T2 shared 93–95% of its genome with the other five B. seminalis strains. Furthermore, strain 869T2 lacked several genetic loci that are important for human virulence. Based on the results of our analysis of the core genome phylogeny and whole-genome average nucleotide identity , strain 869T2 was classified as B. seminalis. B. seminalis is a member of the Burkholderia cepacia complex , which is a group of Gram-negative, aerobic, non-sporulating, rod-shaped bacteria. Bcc consists of opportunistic human pathogens that exist in patients suffering from cystic fibrosis as well as pathogens of many vegetables and fruits, such as onion and banana. Contrary to the pathogenic traits that led to their original discovery, some Bcc bacteria have ecologically beneficial interactions with host plants. The plant endophytic bacterium B. seminalis strain TC3.4.2R3, isolated from sugarcane, can serve as a biocontrol agent to reduce infections with Fusarium oxysporum and the cacao pathogens Moniliophthora perniciosa , Phytophthora citrophtora, P. capsici, and P. palmivora as well as orchid necrosiscaused by Burkholderia gladioli through the production of pyochelin, a rhamnolipid, and other unidentified diffusible metabolites. Another strain of Burkholderia seminalis, strain R456 isolated from rice rhizosphere soils, decreased the occurrence of rice sheath blight disease caused by Rhizoctonia solani.

There are multiple detection methods for Salmonella. Traditional cultural methods for isolation include plating on selective agars and incubating for 24 h at 35 °C . Before plating, naturally-contaminated samples are often enriched with non-selective and/or selective broths such as lactose broth since a low concentration of Salmonella is expected. Standard methods and media used to isolate Salmonella can be found in the FDA Bacteriological Analysis Manual . In conjunction with traditional cultural methods, rapid biochemical or antigen-antibody-based methods can be used for quicker isolation and identification of Salmonella . Salmonella can also be identified through testing a combination of biochemical and serological reactions. Most Salmonella will provide a positive result for glucose , lysine decarboxylase , H2S , lysine carboxylase broth, phenol red dulcitol broth, polyvalent flagellar test, polyvalent somatic test, and methyl red test; and provide a negative result for urease, potassium cyanide broth, malonate broth, indole test, phenol red lactose broth, phenol red sucrose broth, and VogesProskauer test Salmonella can be further identified through phenotyping methods such as serotyping, phage typing, biotyping, and R typing . Finally, Salmonella can be identified through genotyping by PCR or pulse-field gel electrophoresis . PFGE was a highly used method to trace outbreaks, but whole genome sequencing is now the current method used by PulseNet . Whole genome sequencing is a laboratory procedure that determines the order of bases in the genome of an organism in one process . Because millions of bases make up the WGS for every organism, grow bag for tomato it is much more detailed method than Pulse Field Gel Electrophoresis which was the former gold standard method for differentiating among pathogen isolates .

The CDC started implementing the use of WGS as its main way tracking foodborne outbreaks in 2013 . They are able to compare genomes from outbreak strains to reference genomes from public data bases such as EnteroBase . Shiga toxin producing Escherichia coli. Shiga toxin producing E. coli is a gramnegative, non-spore-forming bacteria that can cause infection in humans. Like Salmonella, it belongs to the family Enterobacteriaceae. STEC can grow in temperatures ranging from 7 °C to 45 °C but has optimal growth from 35 °C to 42 °C . It can grow in a pH range of 4-10, and requires a water activity of 0.95 or higher . STEC can be carried by many types of animals and is commonly associated with ruminants such as cattle . STEC will be passive in many of these hosts, but can cause disease in humans. Symptoms of infection by STEC include bloody diarrhea, vomiting, and in certain cases hemolytic uremic syndrome . STEC infects humans by using attachment and effacement lesions encoded for on their LEE pathogenicity island . As the name suggests, the main toxins used by STEC are Shiga toxins, which is what leads to cell death in the host. Apart from being the most known disease-causing STEC serotype, E. coli O157:H7 informs most of what is known about STEC . The serotype E. coli O157:H7 was first identified in 1982 and was well studied during that decade . The pathogen rose to infamy in 1993 when a large outbreak occurred across multiple locations of the fast food chain Jack in the Box . The consumption of the chain’s undercooked hamburgers led to illness in more than 600 people . Because of this incident, the way food safety processes are handled, especially the inspection of meat and poultry, have drastically changed . This incident is also the reason why O157:H7 has been so well-studied compared to other STEC serotypes. Among other STEC serotypes E. coli O26 is less likely to cause HUS compared to O157, even though its toxins are similar . Hemolytic uremic syndrome, or HUS, is a severe condition that damages the blood vessels of the kidneys and leads to renal failure.

Once in the body, Shiga toxin can bind to globotriaosylceramide in vascular endothelial cells, and damages those cells by inhibiting protein synthesis. If those cells are part of the kidney, it can lead to HUS . In general, E. coli O157 is more likely to cause severe symptoms than other types of STEC . STEC and may also be of concern in low-moisture foods. While the main reservoir for E. coli O157:H7 is cattle, the pathogen can easily spread through fecal contamination of water and other foods . According to the World Health Organization , this contamination can occur at many stages of growing and processing produce, which has led to increases in outbreaks of the pathogen in fruits and vegetables . Because of the recent outbreaks associated with STEC in low-moisture foods, and the various stages at which contamination can occur, it is important to explore its ability to survive in dried fruit, which can have many processing steps . The detection of STEC can also be culturable or molecular based. Selective media often used for STEC plating include MacConkey agar, violet red bile agar, and Levine’s Eosine methylene blue agar . To differentiate E. coli O157 from other E. coli, sorbitol can be added to the agar since O157 will not usually ferment sorbitol . Because the number of E. coli cells present in food is low, enrichment is very important to make sure that any cells present are detected. Common enrichments forSTEC include brain heart infusion broth, tryptic soy broth, and modified buffered peptone water with pyruvate . For identification in pure cultures, agglutination assays are useful for serotyping . The enzyme-linked immunosorbent assay is becoming more common for identifying STEC. Use of this assay has led to a better understanding of the most common serotypes of STEC. While O157:H7 is the most common STEC serotype associated with disease, there is a decrease in proportion of that serotype when using ELISA compared to culture-based methods . When screening with biochemical tests, most pathogenic E. coli will have negative test results for H2S, urease, arabinose non-fermenting, and indole .

To further determine if pathogenic E. coli is STEC specifically, real-time PCR can be used. The genes that should be targeted during PCR are stx1, stx2, and uidA, with the latter being highly conserved in O157:H7 strains . As mentioned with Salmonella, the main outbreak identification tool used by PulseNet is WGS. It has more differentiation capability than past methods used like PFGE. Abdelhamid et al. looked at a recent outbreak of E. coli O157:H7 from cattle to human and found that WGS was able to distinguish which isolates from the cattle matched the isolates in the infected patients, while the use of PFGE was unable to differentiate between all the isolates tested. Listeria monocytogenes. L. monocytogenes is a gram-positive, non-spore forming bacteria belonging to the family Listeriaceae. It can grow in a temperature range of from -0.4 to 45 °C with optimal growth from 30 to 37 °C and can grow within a pH range of 4.4-9.6, but has optimal growth at 6-8 . L. monocytogenes can grow in foods with a water activity of 0.9 or higher .L. monocytogenes is found in a variety of places, including plants, animals, soil, water, and humans . It can cause listeriosis, which can be a very serious infection in high-risk groups but is unlikely to manifest severely in other groups of people . Foodborne Listeria needs only a few cells to infect and once in the digestive tract Listeria can invade cells and use cell-to-cell transmission to spread to the rest of the body. Symptoms of listeriosis in high-risk individuals can include miscarriage, sepsis, and meningitis, grow bag for blueberry plants while in the rest of the population people may experience only mild gastroenteritis. There is some debate of whether L. monocytogenes poses a significant risk in low moisture foods. There have been no documented outbreaks of L. monocytogenes associated with low-moisture foods and the current prevalence of the pathogen in low-moisture foods is likely low . However, L. monocytogenes can survive for long periods of time in low-moisture foods and there have been recalls associated with L. monocytogenes in these foods, including in dried fruits, nuts, biscuits, and oats . L. monocytogenes is notorious for its ability to grow in cold environments. This is why outbreaks of this pathogen are often found in refrigerated, ready-to-eat foods , as they do not require heating before consumption.

Dried fruits are an RTE and are often stored at refrigerated temperatures by processors, but due to the inability of pathogens to grow at low water activities, L. monocytogenes growth should not be a concern in dried fruits. Pathogen survival is still a concern though, as L. monocytogenes has been shown to have a desiccation tolerance of up to 1 year in certain low moisture foods. For instance, Kimber et al. found that 6 log CFU/gof L. monocytogenes inoculated onto raw almonds did not decline significantly when the almonds were stored at 4 °C for 12 months. Agar used for selective plating of Listeria include Oxford, Modified Oxford, PALCAM, Chromogenic Listeria agar, and lithium chloride-phenylethanol-moxalactam . Selective enrichment can be done with buffered Listeria enrichment broth . Proper subtyping is particularly important in identifying Listeria, as many different strains can have similar phenotypic qualities . The most common serotypes of L. monocytogenes isolated from patients are type 1 and type 4 . There can also be strains that have qualities that are unusual to Listeria that make identification more difficult. The FDA BAM mentions as examples isolates of Listeria innocua that are hemolytic and L. monocytogenes and Listeria welshimeri isolates that are rhamnose negative . When trying to differentiate L. monocytogenes specifically, the species should usually test negative for mannitol and xylose, and should test positive for rhamnose, virulence, and beta hemolysis . Again, sequencing plays an important role in identification of many pathogens such as Listeria. In fact, Listeria was the first bacteria the CDC began using WGS with and has since then spread its use to other organisms including Salmonella and E. coli . Intrinsic factors influencing pathogen survival. Pathogen survival can be influenced by many factors, including aw and pH. In general, the ability of microorganisms to survive common food processes increase when aw is lowered. However, while higher aw promotes growth, high aw also enhances lethality of thermal treatments . The mechanisms for thermal resistance are not completely agreed upon but are shown to be strongly influenced by aw . The lower the aw, the more difficult it is for the number of cells present to decline . For example, Keller et al. found that Salmonella inoculated onto pumpkin seeds became increasingly resistant to thermal inactivation when the aw decreased from its original value of 0.97 to below 0.20. The pumpkin seeds began with a Salmonella population of 7.48 ± 0.57 log CFU/g and dropped to 0.68 ± 0.81 log CFU/g after 6 h or drying at 60 °C . After 6 h, the aw dropped to below 0.20 and no more significant decrease in the Salmonella population was seen during 12 more h of drying at 60 °C . Just knowing the aw alone is not enough information to understand pathogen survival, as water activity is often working in conjunction with other factors such as temperature . pH is also known to have some effect on bacterial survival. While bacteria have a specific pH range in which they can grow, they can survive outside that pH range. Thermal resistance is decreased at lower pH, so pathogens are generally easier to inactivate in more acidic food matrices . Deng et al. inoculated dry infant cereals of pH 4.0 and 6.8 with 6 log CFU/g of E. coli O157:H7. After 24 weeks of storage at 5 °C the cereal with a pH of 4.0 had 3.19 log CFU/g of E. coli, while no E. coli was detected in the cereal at pH 6.8 . The phytochemicals found in dried fruits, including alkaloids, flavonoids, and phenolic compounds, can exhibit antibacterial activity . Jagathambal et al. screened various phytochemicals from dried figs to see if they had any inhibitory effects on various bacteria. The phytochemicals extracted from dried figswere able to inhibit Salmonella spp., Klebsiella spp., Haemophilus spp., and Serratia spp. with a minimum inhibitory concentration of 1.0 mg/mL . Mainasara et al. screened phytochemical from dates to see how inhibitory they could be against pathogens.

Limonene and a-terpinolene were the highest produced monoterpenes, which exhibited the strongest patterns consistently . To investigate the events leading to this accumulation of monoterpenes, we performed a Fisher’s exact test to identify enriched KEGG pathways in the modules. Terpenoid backbone biosynthesis was significantly enriched in the H-II-1 module . Figure 3.4 depicts the MEP terpene backbone biosynthesis producing GPP that leads to monoterpene biosynthesis. A flux of terpene biosynthesis occurred at the end of Stage II and the beginning of Stage III, which indicates precursors for monoterpene metabolism were being synthesized . From the WGCNA, we also identified the top 5% highest connected genes within the module network. In the H-II-1 module, the top highly connected genes included the gene encoding HDR and a limonene synthase in the terpene biosynthesis pathway.Color changes are a characteristic of fruit ripening. To further define ripening in the pistachio hull, we investigated the underlying biological cause of the change in fruit coloration from green-yellow to hues of red-pink observed in the hull during Stage IV . We found a significant correlation between red coloration increase in the hull with the H-IV-1 and H-IV-2 =0.73 modules during ripening. This was further supported by a Fisher’s exact test for enrichments of KEGG pathways in each module. The H-IV-2 module was significantly enriched for the carotenoid biosynthesis pathway. The B-carotene hydrolase was the highest expressed carotenoid gene in this module and is annotated to be involved in the production of lutelin and zeaxanthin. We examined the highest connectivity genes in this module and among them was a phytoene synthase gene with 887 connections, the rate-limiting step in the carotenoid pathway. Because pink coloration often comes from anthocyanins we also looked at anthocyanin biosynthesis in the hull. While expression was present in the phenylpropanoid and flavonoid pathways, grow bag expression was low in the steps exclusive toanthocyanin biosynthesis. We also found a high negative correlation between the hull redness and the H-III-1 module corresponding to a loss of green coloration.

A significant enrichment of photosynthesis genes in the same H-III-1 module , meaning gene expression of photosynthesis genes decreased after Stage III when fruit became less green.Pistachio kernels contain a high proportion of fatty acids and reach their maximum fat content as the kernel matures during ripening . To further understand the composition of the fat content, we measured unsaturated and saturated fatty acids across six time points during Stage III and IV of kernel development . Unsaturated fatty acids made up 87% of the total fatty acids present when the fruits were ready to be consumed . We confirmed that the unsaturated fatty acids were composed of a higher ratio of mono-unsaturated to poly-unsaturated . This ratio changed through time, such that by ripening MUFA were the predominant class of fatty acids present in the fruit. We determined alterations of metabolites within each class of fatty acid contributed to the changes in MUFA and PUFA ratios during maturation . To further understand what causes these alterations, we examined gene expression of kernel in gene modules associated with the increase in fat content. The module-trait relationships indicated that the increase in fat content was highly and significantly correlated with the K-III-1 module, along with K-IV-1, K-IV-2, and K-IV-3 . This same relationship was also evident for these same modules and the proportion of unsaturated fatty acids through time . We performed an enrichment of KEGG pathway annotations in kernel modules and found that fatty acid biosynthesis was significantly enriched in the K-III-1 module . The high expression of biosynthesis genes during Stage III indicates that fatty acids are produced early on at the start of kernel development, and taper off at the beginning of Stage IV . Within this module, 19 genes encoding fatty acid biosynthesis were found including key genes FAB2 and FAD2 which desaturates steric acid into oleic acid and oleic acid into linoleic acid, respectively . The FAB2 and FAD2 genes were the highest expressed genes in the pathway, and were among the top 5% of genes in the module. FAB2 peaked in expression with 12,500 normalized reads at 1508 GDD while FAD2 peaked with 14,700 normalized reads at 1749 GDD.

Consistent with the expression data, the metabolite data also showed that oleic and linoleic acid were the top two produced fatty acids, throughout development. Interestingly, the concentration of linoleic acid decreased over time while oleic acid increased, which was not evident in the expression data.Defining the biological events occurring during pistachio fruit development that lead to traits of interest can allow for breeding and management strategies to improve fruit quality. Further, a high-quality reference genome has been lacking, as previous genomes are incomplete and fragmented. Therefore, in order to facilitate molecular breeding and broaden the understanding of nut tree crop fruit developmental processes, we present for the first time an assembled 561 Mb reference-quality chromosome-scale genome of P. vera cv. Kerman. Based on k-mer distribution analysis with PacBio HiFi reads, the Kerman genome showed a moderate heterozygosity estimate in comparison with other outcrossing highly heterozygous crops, such as pear 1.6% and grape 1.6-1.7% . This is unexpected because the previously-reported heterozygosity levels of pistachio genome were higher, 1% and 1.72% , which was attributed to the nature of outcrossing by wind pollination and dioecy of pistachio trees . In addition, the genome size estimate of 521 Mb in our study was smaller than the first attempt for pistachio genome size estimate with 26.77 Gb whole genome sequencing data using 17-mers . However, later, the genome size estimated with the larger amount of data using 21-mers was rather similar in size to our assessment . In the final genome assembly, the Kerman genome size was larger than the estimated size but smaller than previously published genome assemblies of different pistachio cultivars, Batoury and Siirt and Bagyolu . Although the size variation of the estimated and assem-bled pistachio genome assemblies could be explained by possible genome size variation across different cultivars as documented in other plant genomes, it is likely that pseudoduplication in the assemblies, especially from the highly repetitive regions in chromosome arms in the case of pistachio, is the primary cause of assembly size variation . In 2015, Sola-Campoy and colleagues characterized massive enrichment of 180 bp repeat on one arm of 11 chromosomes in pistachio, which was also observed in the Kerman genome .

The largest region with dense distribution of 180 bp repeats reached about 9 Mb in chromosome 7, where no protein-coding gene was annotated . These extremely repetitive regions could have been the major issues of accurate pistachio genome assembly and chromosome construction. Although Omni-C reads are known to offer uni-form coverage across the genome without RE sites over represented, it was observed that the overall coverage of Omni-C reads was significantly lower in those regions in Omni-C analysis, likely due to the limitation of mapping capability . Therefore, more careful validation on those regions is needed to improve the pistachio genome. The annotation of intact and fragmented transposable elements in the Kerman assembly resulted in about 11% higher genome coverage than the estimated repetitiveness . As discussed in genome size and estimate, this is likely caused by the pseudo-duplication in the assembly or misestimation due to exceptionally repeat-dense regions in chromosome arms. Among 65% of repetitive regions, nearly 49% of the genome was composed of LTRs, which have been widely known as the dominant TE groups in plants and can play a major role in adaptation and evolution by introducing novel genetic material. The protein-coding gene annotation shows high completeness based on BUSCO assessment with almost 99% . However, minor improvements can still be made by filtering out false-positive gene models and recovering missing BUSCO genes. Macrosynteny patterns between Pistacia vera cv. Kerman, Mangifera indica , and Citrus sinensis provided evidence that P. vera has not experienced a lineage-specific whole genome duplication event , unlike the recent WGD which occurred in the mango genome as described in . The synteny between mango and pistachio genomes and the similarity between their fruit morphology and growth patterns provides an interesting evolutionary comparison within the Anacardiaceae family.During the growing season, pistachios undergo a unique asynchronous development of the kernel and maternal tissues. The hull and shell develop together in the first months, marking Stages I and II , grow bag gardening while embryo development takes place during Stages III and IV. In contrast to previous reports, we found that shell hardening continues to take place with kernel growth starting in late June at approximately 1000 GDD through late August at approximately 2000 GDD . The asynchronous developmental pattern between the fruit and embryo has not been well described in the literature for other tree crops. While peaches appear to exhibit a similar pattern in seed development, this trait does not seem to have been studied in a crop whose seed is consumed . Carbohydrate dynamics in the tree may offer some explanation of the asynchrony. Carbohydrates reserved from the prior year are utilized by the tree to produce buds and develop fruit in early spring, through Stage I . The lull in fruit growth identified as Stage II may serve as a transition between a net carbon loss and a net carbon gain in photosynthesis leading to the growth of the kernel. The RNAseq experiment assessed genetic changes through time and tissue type during fruit development. The shell and hull have the most similar gene expression patterns . This was obvious in the expression of hormone-related gene expression. The shell and hull tissues exhibited very similar expression patterns for each hormone biosynthesis pathway, while the kernel expression patterns were distinct . Interestingly, the hull and shell total gene expression became more similar over time . This contrasts with the morphology of the tissues, which early on in development are physically fused together and appear to become increasingly different through time as shells become woody and split, and the hull and shell tissues separate during ripening . The similarity in gene expression may be due to both tissues undergoing terminal developmental programs. This occurs earlier in the shell when the tissue reaches its peak firmness at the beginning of Stage IV, while in the hull this occurs at the end stages of Stage IV as ripening finishes. Shell lignification was previously reported to start as early as May-June, falling in Stage I-II . While the secondary cell walls become lignified, the shells are green and flexible at this point. However, as described above, the texture of the shell continues to change through Stage III leading to a woody tissue that then splits . The shell tissues appear to senesce and be fully lignified at around 2100 GDD, as RNA content became very low in shell tissues after this point. Our gene expres-sion analysis found a proportion of the genes involved in the phenylpropanoid pathway leading to monolignols to be expressed highest at Stage II followed by a sharp decline, marking the initial lignification . The genes exhibiting this pattern were among the highest expressed homologs; however, other copies of the genes displayed patterns with peak expression later on during Stage III or IV indicating lignin was still being produced, contributing to the increased firmness of the shell. This suggests that the lignification process does not complete until the shell reaches peak firmness, as has been described in walnuts . While continued lignification may be a factor leading to shell firmness changes, other factors such as cell wall modifications likely also contribute, but require further investigation. Overall, understanding the composition and alterations in the shell tissue will be important to ascertaining the underlying mechanisms leading to shell split for a higher quality nut.Although ripening has not previously been well explored in fruit tree crops, early reports suggest that pistachios are non-climacteric fruit . We confirmed ethylene is not produced in a climacteric pattern during ripening and remains at constant low levels, as shown through biosynthesis gene expression . In conjunction with this we found evidence that abscisic acid may be involved in regulating ripening in pistachio. NCED is the rate limiting enzyme in ABA biosynthesis . We found that a primary copy was expressed in the shell and hull tissues right before ripening changes began to occur, i.e., the transition between Stage III and Stage IV. This corresponded to an increase in ABA signaling genes such as, PYLs, PP2C, SNRK2, and ABFs, suggesting ABA is active at the onset of ripening .

Moving forward, we intend to generate a range of populations based on both phenotypic and genomic selection from this yield evaluation trial. These will then be evaluated alongside other elite material for DMY to assess if there has been any improvement. Due to the lengthy breeding process of perennial forages, it will take several years to determine whether these methods have been successful. To improve the predictive ability of the model moving forward a combination of evaluating a greater number of families and improving the quality of phenotypic data through better modeling will be imposed. Increasing the size of the training population could be facilitated without a significant increase in costs by using modern high-throughput phenotyping tools, such as dronebased remote sensing. With decreasing costs of genotyping, improved computational software and the availability of genomic resources , genomic selection is becoming increasingly available to more resource limited breeding programs like alfalfa. There is still much research required to assess whether actual yield gain can be achieved; however, these studies provide a baseline for future studies to investigate potential yield improvement.Yield is the most important trait for profitable forage production, yet the rate of genetic gain for dry matter yield in perennial forage crops is lower than the main cereal crops and has been essentially zero in alfalfa over the past 30 years . Limited resources, low heritability, square black flower bucket significant genotype by environment interaction and long selection cycles limit the rate of genetic gain in perennial forages in comparison to many annual food and feed crops .

Improvement of perennial forages is typically carried out through recurrent phenotypic selection with or without progeny testing to accumulate desired alleles at high frequency in a population . Ideally the number of families to be evaluated is very large, particularly with the advent of modern breeding methodology such as genomic selection. In reality, breeders must strike a balance between the available resources and the size and scope of breeding trials. Phenotypic evaluation of perennial forage traits requires significant investment of land, labor, and capital. Forage DMY and dormancy in alfalfa are two crucial traits that require significant resources to phenotype. The standard test for fall dormancy in alfalfa requires height measurements for each trial entry 25-30 days after the final harvest, often across multiple environments and years . To accurately assess forage yield, experimental units must be harvested, dried,and weighed to estimate dry matter content across multiple harvests and years, resulting in up to 40 total harvests over the lifetime of a trial . Further complexity is added to the breeding of perennial forages considering the diversity of evaluations trials often used, ranging from single plant evaluations to transplanted rows, seeded rows, or solid seeded swards. The choice depends on the traits of interest, the number of genotypes or families being evaluated, seed quantity, and the capital and labor resources available to the breeder, with most programs using a combination of sown and transplanted trials . Transplanted family rows are the most common as they are a cost-effective method of evaluating large numbers of trial entries for traits with high heritability. They are commonly used to screen populations for resistance or tolerance to various pests and diseases, investigating growth habit, dormancy, flowering time, and forage quality . In the past, forage yield has often been selected indirectly based on evaluation of vigor on spaced plants or short family rows . Although a useful method for evaluating other important, highly heritable traits, a poor correlation exists between these assessment methods and yield in a commercial setting . Large sown plots are commonly used for variety trials.

These trials require large quantities of seed, cover a large area, and provide phenotypic data for relatively few trial entries. In a breeding program, these trials are typically used to compare advanced breeding populations to released cultivars for key traits such as stand establishment, DMY, forage quality, flowering time, and dormancy. Although useful for obtaining phenotype data that well represents a commercial forage operation, it is usually not feasible to evaluate hundreds of families in this way. Transplanted mini-sward plots provide a compromise between family rows and large sown plots. They seek to provide a better estimation of forage DMY than family rows without the need for large quantities of seed or significant land area that large sown plots require. In these trials asmall number of plants are planted close to one another to mimic the competition observed in commercial forage stands. In recent decades, remote sensing has been widely adopted in agricultural research , offering a plethora of non-destructive vegetative data with massively reduced labor requirements. Remote sensing has the potential to address the lack of yield improvement in alfalfa and increase the rate of genetic gain for yield in other perennial forages by enabling breeders to greatly increase the size of trials without the associated increase in labor costs. This is particularly important for breeding programs looking to use genomic selection, where the size of the training population is a key component of predictive ability . Remote sensing techniques have been shown to enable accurate estimation of biomass yield in alfalfa at the field level , and at the large plot level in breeding trials . However, its accuracy has not been widely reported across the range of plot types used in forage breeding or for estimating fall dormancy in alfalfa. The overall objective of this research project was to assess the accuracy of drone-based remote sensing versus traditional phenotyping for forage biomass yield and alfalfa fall dormancy across a variety of plot types used in perennial forage breeding. The goal is to give breeders the ability to evaluate a wider range of material without the associated increase in labor and costs. In addition, we aim to provide recommendations for researchers looking to incorporate similar technology into their breeding programs.

This experiment was carried out across several trials previously established as part of the UC Davis forage breeding program located on the UC Davis Plant Sciences Farm in Davis, CA on a Yolo silt clay loam . It is a Mediterranean environment with hot, dry summers, cool winters and moderate annual rainfall which falls predominantly in the cooler months from November-March . Soil tests were conducted prior to planting to adjust P, K, and pH according to soil test recommendations. The trials consist of three alfalfa breeding trials and a forage grass variety trial.The trial consisted of 72 released cultivars, experimental cultivars, germplasm populations, and eleven standard test check cultivars . Plants were germinated in 128-cell flats in the greenhouse in February before transplanting to the field in April 2018. This experiment consisted of four replications laid out in a randomized complete block design. Plots consisted of a single row of 25 plants spaced 30 cm apart with a 90 cm gap between plots and 60 cm spacing between rows. Fertilizer was applied to maintain P and K at appropriate levels for a high yielding alfalfa stand, with weeds and insect pests monitored and control measures applied when necessary. Plants were initially watered using sprinkler irrigation until fully established, following which they were flood irrigated to satisfy full evapotranspiration requirements.This trial contained 80 half-sib families of an experimental population UC2588 that had been selected for tolerance to lygus feeding. We had had sufficient seed of each family to plant solid seeded plots. This experiment was established following the NAAIC standard procedures for variety yield trials . It consisted of two replications laid out in a randomized complete block design with ten rows and twenty ranges. Plots were 1 m x 3 m and were drilled using a small plot planter at a seeding rate of 15 kg ha-1 with 1.5 m gaps between ranges. UC Impalo was sown as a border between ranges and around the exterior of the trial. As with the 2018 dormancy trial, crop nutrient demand, weeds and pests were monitored and adjusted when necessary. Sprinklers were used immediately after sowing to get the trial established, square black flower bucket wholesale followed by flood irrigation to meet water demand.This trial included a total of 198 entries of which 193 were half-sib families from two closely related elite UC Davis populations derived from various UC Davis germplasm that underwent selection for root rot and other stresses in El Centro and Davis, California. In addition, three cultivars: Highline, UC Impalo and CUF 101 were included as repeated checks and the remaining two entries were balanced bulks from each of the two populations . The trial was sown in the greenhouse in March 2020 and transplanted two months later in early May at two locations on the UC Davis research farm in Davis, California. Each site has the same layout consisting of two replicates with 7 rows and 29 ranges for a total of 203 plots per rep, 812 plots overall. Plots consisted of 24 plants laid out in a regular 4 × 6 grid with 20 cm spaces between plants. There was a 30 cm space between rows and a 110 cm space between ranges to allow room for mechanical harvesting.

This trial was managed as a high-yielding alfalfa stand, soil tests were conducted each year, with amendments made accordingly. The trial was established using sprinkler irrigation, which was switched to flood irrigation after plants were well established. Irrigation water was added to roughly match crop ET. Weeds were managed by a combination of manual removal and herbicides, and insect pests were monitored and controlled with insecticide application as necessary, primarily for alfalfa weevil control in spring.A grass variety trial containing 88 cultivars was sown in October 2020. Plots are 1.5 m x 4.5 m and were drilled using a small plot planter. Table 1 outlines the seeding rates used for each species. The trial was separated by species with two blocks of tall fescue, two blocks of orchard grass, one block of timothy and reed canary grass, and the remaining species in the final block. Each block contained four rows of plots with 14 ranges. The blocks are separated by borders of either tall fescue, timothy, or orchard grass to allow irrigation pipes to be laid across the field without lying on top of the plots. This trial was irrigated by sprinklers on a weekly to biweekly basis as needed to approximate ET demand. N, P and K levels were monitored, and fertilizer applied when necessary. N was applied at 100 kg ha-1 in spring and again after first harvest.Plant height measurements for the alfalfa fall dormancy standard test were measured following the protocol outlined by Teuber et al. . Twenty-five days after the final fall harvest, the natural plant height was measured on each of the 25 plants per plot. Natural plant height was deemed to be the distance from the soil surface to the top of the tallest stem as the plant stands in the field . The measurements were then averaged over the whole plot to generate a single data point for each plot. Biomass yield data were collected using a small self-propelled plot harvester. Harvests occurred in alfalfa when the field had reached 10% bloom with the first harvest usually occurring in late March/April and the final harvest in October. For alfalfa trials, subsamples were taken during each harvest, weighed wet, dried for at least 4d at 60C, and weighed dry to adjust moisture percentage. Several subsamples were taken from each replication as composite samples from all entries, rather than for every entry, and the average dry matter was used to adjust the wet weights. In the grass trial, harvests occurred when the most plots of tall fescue and orchard grass had reached the late boot stage, with the first harvest in April and subsequent harvests every 6-8 weeks for a total of four harvests per year. All species were harvested at the same time for logistical reasons, even though this was likely not ideal for individual species . All forage was clipped uniformly at 7.5 cm, weighted, and removed from the trial area. Subsamples were taken from every plot in the grass trials, weighed wet, dried for at least 4d at 60C, and weighed dry to adjust moisture percentage.Prior to remote sensing data collection, the borders surrounding the trial and between plots were mown. Drone flights and preliminary image processing were conducted following methods modified from Parker et al. .

Women reported working, on average, less than 10 days a month during five months compared to 15 to 21 days per month during the peak season. Although a significant proportion of the individuals surveyed lived in or close to towns, roughly 85% of the jobs reported by this sample of workers were in agriculture. Females had somewhat greater packing shed employment experience than males. Surprisingly, women had higher average daily earnings than did men. Women worked more frequently on a piece rate basis , which paid more than comparable wage employment, and women were employed primarily during the peak season, when earnings were highest.Most workers lived in households with several workers. Twenty-five percent of the females surveyed and half of the males provided more than 50% of their household’s annual income. Only a third of the females who were widows or separated were their household’s major earner . Still, interviews indicated that many women had been able to separate from their husbands and/or live apart from their parents because of income obtained as a temporary fruit laborer. Although female-headed households tended to have lower incomes than male-headed households, many female heads of households spoke with satisfaction that their work allowed them to support themselves. Worker’s household characteristics influenced the number of days employed each year. Figure 3 shows that married men worked the most, especially if they had young children, approximately 275 days per year. Single males worked much less, about 170 days. Men who were separated or widowed worked an amount intermediate between these levels. The significant affect of marriage on the number of days worked suggests that marriage affected the motivation to work and that search effort was an important determinant of employment.

Women averaged significantly fewer days worked per year than men did. Some women worked more than 220 days per year, flower buckets wholesale but no female category had such a high average. Women also showed less variation in the number of days worked with respect to their household situation, at least as here categorized, and the variation shown was directly reversed from that of men. For example, married women with young children worked the least of individuals in the sample, while single women who were not living with their parents worked the most of all female categories. There is thus evidence that married women with young children had a higher reservation wage than other workers. However, women lacking income from a husband or parents worked substantially even when they had young children.Female labor force participation varied greatly by season, declining sharply from February to May, remaining low through September, and then rising steadily to February. Labor force participation was less variable for males. Daily earnings varied seasonally more in agricultural than in non-agricultural jobs, especially for jobs held by women. Women tended to earn more than men in agricultural jobs during the peak season, but less during the slack season, while the situation was reversed for non-agricultural jobs. As agricultural wages declined, a rising proportion of workers was employed in non-agricultural jobs . While female temporary workers face greater wage variation than men and vary their labor participation more, they also suffered substantially more unemployment . The female unemployment rate exceeded 50% during five months. Male unemployment was also high, but averaged only about half as much. 4.1. Labor Market Participation Equation and Expected Earnings Jarvis and Vera Toscano explored adjustment in this market to identify whether seasonal differences in labor force participation was attributable to the existence of specific ‘barriers’ to employment, differences in preferences or differences in observed worker characteristics.

Specifically, they modeled labor force participation for male and female workers by estimating a random effects probit that allowed for unobserved heterogeneity in preferences. Table 5 reports the results. For women, the estimated coefficients on the explanatory variables were generally highly statistically significant and in line with prior expectations. Few of the estimated coefficients were statistically significant for men, a result consistent with the relatively constant male labor force participation rate.13 Women participated in the labor force less than men did. Female labor force participation increased with age. Since rising education was associated with higher daily earnings, education may have altered the preference for work versus leisure. Marriage reduced labor force participation for females, perhaps due to increased household responsibilities and/or a social-cultural bias against work, but did not affect male participation. Female labor participation declined as the number of the worker’s children aged 0-5 years increased, but this effect was reduced if another adult female lived in the household, suggesting that childcare was gender specific and indicating the importance of childcare for female labor force participation. Men and women were more likely to participate during the peak season and less during the slack season as compared to the transition months of April and October through December, a result probably linked to expected earnings. Jarvis and Vera Toscano examined the sensitivity of labor force participation decisions to changes in expected earnings using a probit equation that included the same regressors plus estimated earnings . The coefficient on expected earnings was positive and significant and the other coefficients were closely similar to those obtained cols. 1 and 2. Though labor force participation for men and women responded strongly and positively to the expected wage, the female participation rate varied substantially more because females tended to have a higher reservation wage. Still, female unemployment was generally much higher than male unemployment .

Although wages varied greatly by season, Jarvis and Vera Toscano found they did not vary sufficiently to fully equate the supply and demand of labor and achieve zero unemployment. Four factors were advanced to explain this high unemployment. First, frictional unemployment was high as a result of individuals entering and/or leaving the labor force, changing jobs, and searching for employment in a spatially dispersed market where jobs were relatively short lived and search costs relatively high. Second, many or all firms may have paid an efficiency wage or piece rate to motivate workers, thereby causing the unemployment rate to remain above zero even during periods when labor demand is high. Third, the average reported wage in agriculture lay above the average reported wage in the non-agricultural sector throughout the year. Thus, waiting for an agricultural job could easily have been the better strategy for most workers even when few agricultural jobs were available. Fourth, some workers, especially females, may incorrectly report having been in the labor force and actively seeking work. Alternatively, they may have considered themselves in the labor force, but searched only within a small, local area, where there were few jobs.The average wage rose by about 50% from the slack season to the peak season, a surprisingly large variation. To understand the determinants of changes in daily earnings over the one-year period, Jarvis and Vera Toscano estimated an earnings equation where the dependent variable was the log of average daily earnings and the regressors included both supply and demand side factors. Human capital variables such as education and experience were hypothesized to influence worker productivity and earnings, while monthly dummies reflected the net influence of seasonal fluctuations in agricultural labor supply and demand. Wages were hypothesized to vary in response to the worker’s decision to seek either piece rate or wage employment, and either non-agricultural or agricultural employment. Such choices were assumed dependent on a worker’s willingness to supply effort and preference for factors such as work environment and a shorter commute time to work. Since dummy variables were used to measure the effect of working at a piece rate as opposed to a wage, flower harvest buckets the other coefficients measured the effect of the respective independent variables on the daily wage. Consistent estimates of the earnings function were obtained using the two-step estimator proposed by Vella and Verbeek. The results for both men and women are reported in Table 6. The earnings of both men and women increased with schooling, suggesting that education significantly increased labor productivity in agricultural work, although the higher return was probably partly due to the innate ability that allowed individuals to successfully complete additional schooling. Experience had a significant positive impact on female daily earnings in jobs throughout the year; the analogous coefficient was not significant for males. The square of experience had a significant negative coefficient, indicating that rising experience had a non-linear effect.

A dummy variable was also used to measure the earnings effect of working on a piece rate basis. A piece rate system was frequently used to motivate and remunerate temporary agricultural workers in the fruit sector and a substantial theoretical literature indicates that the piece rate system should increase worker’s productivity and workers’ incomes . There have been few empirical studies. The estimated coefficient on the piece rate dummy indicates that piece rate jobs in this case earned a daily premium of about 12 percent relative to wage jobs. A dummy variable was also used to measure the effect of working in the agricultural as opposed to the non-agricultural sector. Agricultural work paid substantially more, particularly for women . Men’s wages in this sample were about 18 percent higher when working in agriculture, while women’s wages were about 37 percent higher. Agricultural jobs were probably even more attractive than shown for women since there were few piece rate jobs available in non-agricultural work. As earlier noted, women’s average daily earnings were higher than men’s average daily earnings . Women working as temporary agricultural laborers were thought to earn relatively high wages in the Chilean fruit sector , and the results in Jarvis and Vera-Toscano supported that view. Nonetheless, women earned substantially less than men did in wage employment once earnings were adjusted for observed and unobserved characteristics. The estimated gender wage differential was about 25 percent. Although females had higher average daily earnings than men, women earned less than men when working for a wage, but not when working for a piece rate. Jarvis and Vera-Toscano suggested that these results indicated discrimination in the wage market. There may be less possibility of discrimination when workers are employed at piece rate since pay is directly linked to productivity. The large magnitude of the gender wage differential suggests an area for further analysis.Newman and Jarvis found that women were highly informed about many aspects of the packing shed jobs that they accepted, e.g., shed-related characteristics that affected workers’ productivity, fringe benefits, and the expected duration of the job. Women’s willingness to accept work at a specific piece rate was strongly influenced by these characteristics. Piece rates for the same tasks were found to vary by as much as 100%among different packing sheds and these differentials were well explained econometrically by the observed heterogeneity among workers and firms. For example, most processing sheds provided workers with some combination of fringe benefits that included meals, snacks, transportation to and from work, childcare, interest-free loans, and higher quality bathrooms. Supervisors and managers in different sheds treated created different quality work environments. According to the theory of equalizing wage differentials, sheds that provide more and better fringe benefits and/or a better work environment should have paid lower piece rates. This hypothesis was supported by the data. Similarly, Newman and Jarvis hypothesized that firms’ investments in technology, improved plant organization, or the ability to process grapes that were in better condition would raise worker productivity. Further, so long as workers were aware of firm-influenced productivity differences, such higher productivity should lead to lower, not higher piece rates. To the extent that firms possessed improved technology that allowed their workers to achieve higher productivity or were better organized and could provide a constant flow of good quality grapes to workers, allowing workers to process more boxes per time period, the firm should pay a lower piece rate. This followed from the assumption that each worker should earn an income consonant with her opportunity cost in equilibrium. If a firm’s characteristics allowed its workers to produce more output, ceteris paribus, worker competition for the jobs at the firm should have caused the piece rate to decline until its workers’ incomes were equal to what they would earn elsewhere. This hypothesis was also supported by the econometric results. Workers could easily ascertain the piece rates paid by different firms, but the effect of firm characteristics on a worker’s productivity should have been harder topredict.