Crop yield prediction is a critical measurement, especially in the time when parts of the world are suffering from farming issues. Yield forecasting gives an alert regarding economic trading, food production monitoring, and global food security. This research was conducted to investigate whether active optical sensors could be utilized for potato (Solanum tuberosum L.) yield prediction at the mid.le of the growing season. Three potato cultivars (Russet Burbank, Superior, and Shepody) were planted and six rates of N (0, 56, 112, 168, 224, and 280 kg ha−1), ammonium sulfate, which was replaced by ammonium nitrate in the 2nd year, were applied on 11 sites in a randomized complete block design, with four replications. Normalized difference vegetation index (NDVI) and chlorophyll index (CI) measurements were obtained weekly from the active optical sensors, GreenSeeker (GS) and Crop Circle (CC). The 168 kg N ha−1 produced the maximum potato yield. Indices measurements obtained at the 16th and 20th leaf growth stages were significantly correlated with tuber yield. Multiple regression analysis (potato yield as a dependent variable and vegetation indices, NDVI and CI, as independent variables) could make a remarkable improvement to the accuracy of the prediction model and increase the determination coefficient. The exponential and linear models showed a better fit of the data. Soil organic matter content increased the yield significantly but did not affect the prediction models. The 18th and 20th leaf growth stages are the best time to use the sensors for yield prediction.

Phosphorus (P) is an element that is potatoes require in large amounts. Soil pH is a crucial factor impacting phosphorus availability in potato production. This study was conducted to evaluate the influence of P application rates on the P efficiency for tuber yield, specific gravity, and P uptake. Additionally, the relationship between soil pH and total potato tuber yield was determined. Six rates of P fertilization (0–280 kg P ha−1) were applied at twelve different sites across Northern Maine. Yield parameters were not responsive to P application rates. However, regression analysis showed that soil pH was significantly correlated with total potato tuber yield(R2 = 0.38). Sites with soil pH values < 6 had total tuber yields, marketable tuber yields, tuber numbers per plant, and total tuber mean weights that were all higher than these same parameters at sites with soil pH ≥ 6. All sites with soil pH< 6 showed a highly correlated relationship between P uptake and petiole dry weight (R2 = 0.76). The P application rate of 56 kg P ha−1 was the best at sites with a soil pH < 6, but 0–56 kg P ha−1 was the best at sites with soil pH ≥ 6.

Yasemin and Anber are the main rice varieties cultivated in Iraq. Anber is the favorite variety in Iraq because of its unique flavor, and Yasemin is the most cultivated variety. Determining the suitable moisture content of both varieties to produce high extraction rate (lowest rice breakage), good rice whiteness, and the best rice quality in terms of cooked properties was the purpose of this study. Moisture content (MC) (10%, 12%, 14%, 16%) of Yasemin and Anber were used, and targeted whiteness (32, 34, and 36) were obtained by using different milling times. Results showed that the best moisture content was 14% for Yasemin variety and 10% for Anber variety in terms of extraction rate. Process time increasing led to reduction of extraction rate and increased rice whiteness. The highest extraction rate of Yasemin and Anber was 56% and 64% with 32 whiteness, respectively. Kernel breakage had opposite relationship with extraction rate. Yasemin and Anber varieties were classified as short grain rice depending on their length. The maximum elongation was at 16% MC for Yasemin variety and at 10% MC for Anber variety, which increased 60% more than uncooked rice. There was no definite pattern observed for increasing rice volume (width and weight). In conclusion, the extraction rate of Yasemin and Anber varieties was increased at 14% and 10% MC, respectively. For cooked properties, 10% MC of Anber was the best in terms of rice elongation, while 16% MC was the best for Yasemin variety.

Undesirable growth of potato (Solanum tuberosum L.) crop under an excessive N fertilizer application is the main obstacle presently. This research was conducted to investigate the response of different potato cultivars; Russet Burbank, Shepody, and Superior, and its qualitative characteristics under a series of N rates. Six rates of N fertilization (0–280 kg ha−1) were applied on 11 sites in a randomized complete block design, with four replications. Sites with ≥30 g kg−1 of soil organic matter (OM) produced total tuber yield, marketable yield, and tuber weight per plant 39.5, 45.2, and 54.9%, respectively, higher than sites with ≤30 g kg−1 of OM. Tubers specific gravity increased by 0.18% in the sites with ≥30 g kg−1 of OM. The total tuber yield for the three cultivars was maximized at 168 kg N ha−1. Marketable specific gravity, starch, and dry matter content were achieved by applying 168 and 112 kg N ha−1 at ≤30 and ≥30 g kg−1 of OM sites, respectively. Russet Burbank produced a higher yield than Shepody and Superior cultivars significantly, but there was no significant difference among them regarding specific gravity. Excessive N application (>168 kg ha−1) decreased potato tuber production and quality.

Applications of remote sensing are important in improving potato production through the broader adoption of precision agriculture. This technology could be useful in decreasing the potential contamination of soil and water due to the over-fertilization of agriculture crops. The objective of this study was to assess the utility of active sensors (Crop Circle™, Holland Scientific, Inc., Lincoln, NE, USA and GreenSeeker™, Trimble Navigation Limited, Sunnyvale, CA, USA) and passive sensors (multispectral imaging with Unmanned Arial Vehicles (UAVs)) to predict total potato yield and phosphorus (P) uptake. The experimental design was a randomized complete block with four replications and six P treatments, ranging from 0 to 280 kg P ha−1, as triple superphosphate (46% P2O5). Vegetation indices (VIs) and plant pigment levels were calculated at various time points during the potato growth cycle, correlated with total potato yields and P uptake by the stepwise fitting of multiple linear regression models. Data generated by Crop Circle™ and GreenSeeker™ had a low predictive value of potato yields, especially early in the season. Crop Circle™ performed better than GreenSeeker™ in predicting plant P uptake. In contrast, the passive sensor data provided good estimates of total yields early in the season but had a poor correlation with P uptake. The combined use of active and passive sensors presents an opportunity for better P management in potatoes.