Apple (Malus domestica) and pear (Pyrus communis) yield prediction after tree image analysis

Yield forecasting depends on accurate tree fruit counts and mean size estimation. This information is generally obtained manually, requiring many hours of work. Artificial vision emerges as an interesting alternative to obtaining more information in less time. This study aimed to test and train YOLO pre-trained models based on neural networks for the detection and count of pears and apples on trees after image analysis; while also estimating fruit size. Images of trees were taken during the day and at night in apple and pear trees while fruits were manually counted. Trained models were evaluated according to recall, precision and F1score. The correlation between detected and counted fruits was calculated while fruit size estimation was made after drawing straight lines on each fruit and using reference elements. The precision, recall and F1score achieved by the models were up to 0.86, 0.83 and 0.84, respectively. Correlation coefficients between fruit sizes measured manually and by images were 0.73 for apples and 0.80 for pears. The proposed methodologies showed promising results, allowing forecasters to make less time consuming and accurate estimates compared to manual measurements. Highlights The number of fruits in apple and pear trees, could be estimated from images with promising results. The possibility of estimating the fruit numbers from images could reduce the time spent on this task, and above all, the costs. This allow growers to increase the number of trees sampled to make yield forecasts.Yield forecasting depends on accurate tree fruit counts and mean size estimation. This information is generally obtained manually, requiring many hours of work. Artificial vision emerges as an interesting alternative to obtaining more information in less time. This study aimed to test and train YOLO pre-trained models based on neural networks for the detection and count of pears and apples on trees after image analysis; while also estimating fruit size. Images of trees were taken during the day and at night in apple and pear trees while fruits were manually counted. Trained models were evaluated according to recall, precision and F1score. The correlation between detected and counted fruits was calculated while fruit size estimation was made after drawing straight lines on each fruit and using reference elements. The precision, recall and F1score achieved by the models were up to 0.86, 0.83 and 0.84, respectively. Correlation coefficients between fruit sizes measured manually and by images were 0.73 for apples and 0.80 for pears. The proposed methodologies showed promising results, allowing forecasters to make less time consuming and accurate estimates compared to manual measurements. Highlights The number of fruits in apple and pear trees, could be estimated from images with promising results. The possibility of estimating the fruit numbers from images could reduce the time spent on this task, and above all, the costs. This allow growers to increase the number of trees sampled to make yield forecasts

Quantification of capillary water input to the root zone from shallow water table and determination of the associated Bartlett pear water status

The Alto Valle of Rio Negro and Neuquén is an intensive irrigated fruit producing area. The existence of a shallow water table modifies the water content in the soil profile. It is important to distinguish the effect and estimate the amount of water capillary rise in order to enhance the irrigation management and allow the crop to achieve its maximum yield and development in non-stress conditions. The aim of this trial was to quantify and associate water content of soil profile with water status of pear trees, using different methods. In a Bartlett pear orchard planted on 2003, surfaced irrigated, the following variables were measured during the 2017-2018 growing season: soil water content at three depths (0.20 m, 0.40 m, 0.60 m) and water table level (WTL). Additionally, soil profile and texture class were described. Evapotranspiration (ETm) and vapor pressure deficit (VPD) were calculated with data of the automatic weather station. Stomata conductance (Gs) was measured with a leaf porometer in three different moments of the growing season. Moisture stress index (MSI) was calculated from all Sentinel 2A images available for the season. The capillary water input into the root zone from a shallow water table is evident in the continuous records of sensors. This phenomenon keeps soil water content within the readily available water range. The Gs measures showed that the crop water status was appropriate and that values were high compared to those referred to deciduous trees. The MSI values obtained were between the limits of a well-irrigated crop. These results agree with the non-restrictive condition observed in the soil water balance.Sociedad Argentina de Informática e Investigación Operativ

Quantification of capillary water input to the root zone from shallow water table and determination of the associated Bartlett pear water status

The Alto Valle of Rio Negro and Neuquén is an intensive irrigated fruit producing area. The existence of a shallow water table modifies the water content in the soil profile. It is important to distinguish the effect and estimate the amount of water capillary rise in order to enhance the irrigation management and allow the crop to achieve its maximum yield and development in non-stress conditions. The aim of this trial was to quantify and associate water content of soil profile with water status of pear trees, using different methods. In a Bartlett pear orchard planted on 2003, surfaced irrigated, the following variables were measured during the 2017-2018 growing season: soil water content at three depths (0.20 m, 0.40 m, 0.60 m) and water table level (WTL). Additionally, soil profile and texture class were described. Evapotranspiration (ETm) and vapor pressure deficit (VPD) were calculated with data of the automatic weather station. Stomata conductance (Gs) was measured with a leaf porometer in three different moments of the growing season. Moisture stress index (MSI) was calculated from all Sentinel 2A images available for the season. The capillary water input into the root zone from a shallow water table is evident in the continuous records of sensors. This phenomenon keeps soil water content within the readily available water range. The Gs measures showed that the crop water status was appropriate and that values were high compared to those referred to deciduous trees. The MSI values obtained were between the limits of a well-irrigated crop. These results agree with the non-restrictive condition observed in the soil water balance.Sociedad Argentina de Informática e Investigación Operativ

Quantification of capillary water input to the root zone from shallow water table and determination of the associated Bartlett pear water status

The Alto Valle of Rio Negro and Neuquén is an intensive irrigated fruit producing area. The existence of a shallow water table modifies the water content in the soil profile. It is important to distinguish the effect and estimate the amount of water capillary rise in order to enhance the irrigation management and allow the crop to achieve its maximum yield and development in non-stress conditions. The aim of this trial was to quantify and associate water content of soil profile with water status of pear trees, using different methods. In a Bartlett pear orchard planted on 2003, surfaced irrigated, the following variables were measured during the 2017-2018 growing season: soil water content at three depths (0.20 m, 0.40 m, 0.60 m) and water table level (WTL). Additionally, soil profile and texture class were described. Evapotranspiration (ETm) and vapor pressure deficit (VPD) were calculated with data of the automatic weather station. Stomata conductance (Gs) was measured with a leaf porometer in three different moments of the growing season. Moisture stress index (MSI) was calculated from all Sentinel 2A images available for the season. The capillary water input into the root zone from a shallow water table is evident in the continuous records of sensors. This phenomenon keeps soil water content within the readily available water range. The Gs measures showed that the crop water status was appropriate and that values were high compared to those referred to deciduous trees. The MSI values obtained were between the limits of a well-irrigated crop. These results agree with the non-restrictive condition observed in the soil water balance.Sociedad Argentina de Informática e Investigación Operativ